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  • Email Marketing Basics: Open Rates, Click Rates, and What Actually Matters

    You sent your first campaign. Your email platform is showing you a dashboard full of numbers. Open rate. Click rate. Bounce rate. Click-to-open rate. Unsubscribe rate. Conversion rate. Delivered. Unique opens. Total opens.

    Most of it is noise. A few of these numbers actually tell you something useful.

    This guide breaks down what each metric means, what good looks like in 2026, and more importantly, which ones you should actually care about and why.

    First, a Necessary Warning About Open Rates

    Before getting into any numbers, there’s something that changed the entire conversation about email metrics in 2021 that still trips people up.

    Apple launched Mail Privacy Protection in September 2021 as part of iOS 15. Here’s what it does: when someone uses Apple Mail, it automatically pre-loads your email content, including the tracking pixel that records “opens,” regardless of whether the person actually read your email. The email might sit unread in someone’s inbox for three weeks, and Apple still fires that open tracking pixel.

    Apple Mail accounts for roughly 46-50% of all email client usage. This means a significant chunk of the “opens” your dashboard shows you didn’t actually happen in any meaningful sense.

    The practical result: open rates are inflated across the board and have been for several years now. Platforms report average open rates of 39-43% across their user bases, but the real engagement behind those numbers is lower. Open rate is still useful as a directional indicator, but it’s not the reliable signal it used to be.

    This is why the industry has shifted toward prioritizing click rate, click-to-open rate, and revenue per email as the metrics that actually tell you something real about campaign performance.

    With that said, let’s go through each metric properly.

    Open Rate

    What it is: The percentage of recipients who “opened” your email.

    How it’s calculated: (Unique opens / Emails delivered) x 100

    Industry averages in 2025-2026:

    • Overall average across all industries: 39-43% (inflated by Apple MPP)
    • Non-profit and religious organizations: 52-55% (highest performing sectors)
    • Health and fitness: around 47%
    • Consulting: around 46%
    • Software and web apps: around 39%
    • E-commerce: around 30-33% (lower due to high volume and promotional nature)
    • Manufacturing: around 32%

    What it actually tells you: Whether your subject lines are working and whether you’re landing in the inbox at all. If your open rate drops suddenly, something changed. Maybe your subject line quality declined. Maybe your sender reputation took a hit and you’re going to spam more often. Maybe your list went stale. Open rate is a directional warning system, not a precise engagement measure.

    What a “good” open rate looks like: Above 30% is solid in most industries. Above 45% is strong. But given the Apple inflation issue, use this number as a trend indicator rather than an absolute score. If your rate is consistently trending down over time, that’s meaningful. If it jumped 15% overnight, that might just be a spike in Apple Mail users on your list.

    How to improve it:

    • Write subject lines that are specific, curiosity-driven, or tied to something the subscriber actually cares about
    • Keep subject lines under 50 characters so they don’t get cut off on mobile
    • Use a recognizable sender name (a real person’s name tends to outperform a brand name)
    • Send at consistent times so subscribers build a habit of expecting your emails
    • Clean your list regularly (more on this below)

    Click Rate (CTR)

    What it is: The percentage of all recipients who clicked at least one link in your email.

    How it’s calculated: (Unique clicks / Emails delivered) x 100

    Industry averages in 2025-2026:

    • Overall average across all industries: around 2-2.1% (MailerLite data from 3.6M campaigns)
    • ActiveCampaign customers average 6.21% (higher due to platform’s automation and personalization tools)
    • Non-profit: around 2.9%
    • Consulting: around 2.4%
    • Authors/publishing: around 2.75%
    • Software and web apps: around 1.15%
    • E-commerce: around 1%

    What it actually tells you: Whether people found your email compelling enough to take action. Click rate is a much more reliable measure of actual engagement than open rate because it requires a human to actually interact with the content. Apple can’t fake a click.

    If your open rate looks fine but your click rate is low, the problem is in the email body, not the subject line. Your content isn’t delivering on the promise your subject line made, or your call to action isn’t clear enough, or you’re asking people to do too many things at once.

    What a “good” click rate looks like: 2-5% is a reasonable range for most industries, though this varies significantly by email type. A promotional blast to your whole list will typically get lower clicks than a targeted behavioral trigger email sent to a specific segment.

    How to improve it:

    • Have one primary call to action per email, not five
    • Make the CTA button specific (“Download the template” not “Click here”)
    • Put your most important link high in the email, not buried at the bottom
    • Segment your list so recipients are getting content relevant to them specifically
    • Use plain text emails occasionally. They often outperform designed HTML emails in click rate because they feel more personal

    Click-to-Open Rate (CTOR)

    What it is: The percentage of people who opened your email AND then clicked a link.

    How it’s calculated: (Unique clicks / Unique opens) x 100

    Industry average: Around 5.3-6.8% overall, though this varies widely by industry and email type.

    Why this metric matters more than open rate or click rate alone:

    CTOR is the metric that best reflects the quality of your email content. Here’s why.

    Open rate tells you if your subject line and sender reputation got people to open. Click rate tells you if your content drove action, but it’s diluted by the total list size. CTOR isolates the question: of the people who actually opened and read my email, how many found it compelling enough to click something?

    This is the metric that’s least affected by list size and delivery issues. A high CTOR means your content is doing its job for the people who see it. A low CTOR despite a decent open rate means your subject line is drawing people in but the content isn’t delivering.

    ActiveCampaign, which reported a 6.21% average click rate for its customers across 2025 (notably higher than industry average, attributed partly to their deliverability tools and personalization features), uses CTOR as a primary indicator of content quality in their benchmark reports.

    What a “good” CTOR looks like: The average is around 5-7%. Hitting 10%+ on a given campaign means the content really resonated with the segment you sent it to. Under 3% is a signal to look at what your content is promising versus delivering.

    Unsubscribe Rate

    What it is: The percentage of recipients who opted out of your list after receiving an email.

    How it’s calculated: (Unsubscribes / Emails delivered) x 100

    Industry benchmark: Below 0.5% is considered acceptable. Below 0.2% is considered excellent. Above 0.5% is a warning sign.

    What it actually tells you: Whether your content is delivering on what people expected when they signed up. Spikes in unsubscribe rate usually mean one of three things:

    1. You sent something that felt off-brand or unexpected for your audience
    2. You increased your sending frequency and your subscribers don’t feel the value justifies it
    3. Your list includes a lot of old subscribers who’ve lost interest and finally got around to opting out

    A steady background rate of 0.1-0.3% unsubscribes per campaign is completely normal and healthy. People’s circumstances change, interests shift, inboxes get overwhelming. Don’t panic about every unsubscribe.

    What you should pay attention to is sudden spikes. If you send a campaign and your unsubscribe rate jumps to 1% or 2%, something specific about that email pushed people away. Was it unexpectedly promotional? Did the topic feel off for what they signed up for? That’s useful feedback.

    A counterintuitive note: A low unsubscribe rate isn’t always good. If people who no longer want your emails just stop opening instead of unsubscribing, you end up with a large segment of disengaged subscribers dragging down your engagement metrics and hurting your deliverability. People unsubscribing who genuinely aren’t interested is actually healthy list hygiene. Encourage it by making the unsubscribe process easy.

    Bounce Rate

    What it is: The percentage of emails that couldn’t be delivered.

    Two types:

    Hard bounces happen when an email address permanently doesn’t exist or the domain is invalid. Think typos (gmail.cmo), abandoned email addresses, corporate addresses from people who left the company. Hard bounces should be removed from your list immediately. Most platforms do this automatically.

    Soft bounces are temporary failures. The recipient’s mailbox is full, their server was briefly down, the message was too large. Most platforms will retry soft bounces several times before flagging them.

    Benchmark: Your overall bounce rate should be below 2%. If it climbs above that, your list has quality problems that need to be addressed before they damage your sender reputation.

    Why this matters for more than delivery: High bounce rates tell your email provider that your list is low-quality. Email providers like Gmail and Outlook use this as one signal to decide whether your emails belong in the inbox or the spam folder. Consistently sending to a list with a high bounce rate is one of the fastest ways to wreck your sender reputation.

    Deliverability Rate

    What it is: The percentage of emails that actually reach recipients’ inboxes (not just “delivered” to their server, but actually landing in the inbox).

    Benchmark: Above 89% is considered good. Above 95% is excellent. Below 80% is a serious problem.

    This one isn’t directly visible in most email dashboards. What platforms report as “delivered” means the email wasn’t bounced back by the server. It doesn’t tell you whether it landed in the inbox, the promotions tab, or the spam folder. Deliverability is the harder-to-measure underlying factor that affects all your other numbers.

    A 94.2% deliverability rate is what ActiveCampaign reported for their platform in 2025 (claimed as the top industry ranking in an independent study). Brevo, MailerLite, and other platforms all compete on this number because it directly affects whether their customers’ campaigns perform.

    The main factors affecting deliverability:

    • Your sender reputation (have you been sending to bad addresses, getting spam complaints, etc.)
    • Authentication setup (SPF, DKIM, and DMARC records properly configured)
    • List quality (how many dead addresses, how many spam traps)
    • Engagement history (are people opening and clicking, or just ignoring)
    • Content (spam-trigger words, too many images, suspicious links)

    Most reputable email platforms handle the technical authentication setup for you. Your job is maintaining a clean list and sending content people actually engage with.

    Conversion Rate

    What it is: The percentage of email recipients who took the specific action you wanted them to take. Bought a product, signed up for a trial, booked a call, downloaded something.

    Benchmark: Average conversion rate across all email campaigns is around 0.08%, but that number is nearly meaningless without context. Top performers hit 0.44% and above. Transactional emails (order confirmations, password resets, shipping notifications) have 8x higher opens and clicks than marketing campaigns. Abandoned cart emails average around 3.33% conversion rates with top brands hitting 7-8%.

    Why this is the metric that actually matters: Everything else in email marketing is a proxy metric. Open rate is a proxy for “did they see it.” Click rate is a proxy for “were they interested.” Conversion rate is the direct measurement of whether email is generating the outcomes your business actually needs.

    The problem is conversion tracking requires connecting your email platform to whatever counts as a “conversion” in your business. If conversions happen on your website, you need to pass that data back to your email platform. Most platforms support this through website tracking scripts, UTM parameters, or direct integrations with ecommerce platforms.

    If you’re not tracking conversions, start there before optimizing anything else. You’re flying blind on the metric that actually counts.

    Revenue Per Email (RPE)

    What it is: The average revenue generated per email sent.

    Why operators care about this more than any other metric: Revenue per email is the clearest expression of ROI at the campaign level. It connects email activity directly to dollars, removing all ambiguity about whether your email program is actually making money.

    Klaviyo’s data from over 183,000 brands in 2026 showed that automated email flows generate nearly 41% of total email revenue from just 5.3% of total sends, with average revenue per recipient almost 18x higher than regular campaigns. That’s the single most important data point for understanding where to focus your email effort.

    Regular campaign: average $0.18 revenue per send. Automated flows: average $2.87 per send.

    The math on investing time in your automation sequences versus sending more broadcast campaigns is not close.

    Industry Benchmarks at a Glance

    Here are the current benchmarks across the metrics that matter, based on 2025-2026 data from MailerLite’s analysis of 3.6M campaigns across 181,000+ accounts and Klaviyo’s 2026 benchmark report across 183,000 brands.

    Overall averages:

    • Open rate: 39-43% (inflated by Apple MPP; use directionally)
    • Click rate: 2-2.1%
    • Click-to-open rate: 6-7%
    • Unsubscribe rate: below 0.5% is good
    • Bounce rate: below 2%
    • Deliverability: above 89% good, above 95% excellent

    Industry-specific open rates (MailerLite 2025 data):

    • Non-profit: 52.38%
    • Health and fitness: 47.81%
    • Consulting: 45.96%
    • Software and web apps: 39.31%
    • E-commerce: 32.67%
    • Manufacturing: 32.65%

    Email type benchmarks (Klaviyo 2026 ecommerce data):

    • Welcome series: highest performing flow by open rate
    • Abandoned cart: ~50% open rate, ~6% click rate, ~3.3% conversion
    • Post-purchase: strong engagement, 4x+ higher average order value on birthday emails
    • Browse abandonment: varies by retailer, generally strong
    • Regular campaigns: ~30% open rate, ~1% click rate

    How to Actually Use This Data

    Benchmarks are context, not targets. Your job isn’t to hit the industry average. Your job is to understand your own baseline and improve it over time.

    Here’s a practical framework:

    Month 1-3 after starting: Just collect data. Send consistently, watch your metrics, don’t optimize aggressively yet. You need a baseline before you can improve it.

    After you have a baseline: Identify your weakest metric and fix that first.

    • Low open rate? Your subject lines, sender name, or deliverability are the problem. Start split testing subject lines.
    • Low click rate despite decent opens? Your content isn’t delivering on what the subject line promised. Simplify your emails, strengthen your CTAs, segment better.
    • High unsubscribes? You’re sending too often, the content isn’t what people signed up for, or you have a lot of old subscribers who’ve lost interest.
    • High bounce rate? Your list needs cleaning. Remove hard bounces immediately, run a re-engagement campaign to identify unengaged subscribers, then remove the truly dead weight.

    The tool choice matters here too. ActiveCampaign‘s customers averaged a 6.21% click rate in 2025, compared to the industry average of around 2%. That gap is partly attributable to better targeting and automation features (the platform’s predictive send time feature alone can meaningfully improve engagement). MailerLite delivers solid performance at lower price points for smaller lists. Klaviyo‘s benchmark data for ecommerce shows their customers significantly outperforming general-purpose email tools for abandoned cart and post-purchase flows.

    Platform choice affects performance. Not just because of features, but because better tools make it easier to do the things that improve performance: segmentation, personalization, behavioral triggers, and clean deliverability infrastructure.

    The Three Metrics That Actually Drive Decisions

    If you’re just starting and the full dashboard feels overwhelming, narrow it down to these three and get comfortable with them first.

    1. Click rate: The most reliable indicator of content quality and engagement that isn’t distorted by Apple’s privacy changes. Watch for trends. If it’s declining over time, your content is getting less relevant to your audience.

    2. Unsubscribe rate: Your early warning system that something is off. Keep it below 0.5%. Spikes tell you to look at what you sent.

    3. Conversion rate / revenue per email: The number that actually ties to your business results. Set this up to track properly from the start, even if it takes a little work to connect the data.

    Everything else provides supporting context. Open rate tells you about subject lines and deliverability. Bounce rate tells you about list health. But those three are where the signal lives.

    Start there, track consistently, and optimize the thing that’s most limiting your results. That’s the whole game.

    This article contains affiliate links. We may earn a commission if you sign up for a service through links on this page, at no extra cost to you. Our opinions are our own.

  • What Is a CRM? Plain English Explanation for Non-Technical Founders

    You’ve heard the acronym enough times that nodding along feels safer than admitting you’re not totally sure what it means. CRM. Customer Relationship Management. Everyone seems to have one or be trying to sell you one.

    Here’s the thing: even in 2026, roughly 22% of sales professionals still aren’t entirely sure what a CRM actually is. So if you’re fuzzy on this, you’re not alone, and it’s worth getting clear.

    This guide explains what a CRM is in plain language, what it actually does day to day, when you need one, and which ones are worth looking at. No jargon, no assumption that you already know the landscape.

    The One-Sentence Version

    A CRM is software that keeps track of all your relationships with customers and potential customers so nothing falls through the cracks.

    That’s it. Everything else is detail.

    The Longer Version (Still Plain English)

    Think about what happens when you’re running a business and you don’t have a CRM. You’ve got a spreadsheet somewhere with customer names and emails. Some notes in your inbox about a call you had with a prospect. A sticky note on your monitor reminding you to follow up with someone this Thursday. A Slack message where a teammate mentioned that a client had a complaint. A Google Doc where you wrote down details from a sales call three weeks ago.

    All of that is customer relationship data. It’s just completely scattered across 10 different places, and no single person on your team can see all of it at once.

    A CRM pulls that into one place. Every person you’re in a relationship with, whether they’re a prospect, a customer, a past client, or just someone who expressed interest once, gets a profile in the system. On that profile, you can see their contact info, every email you’ve ever exchanged, notes from phone calls, where they are in your sales process, what they’ve bought, any support tickets they’ve submitted, and a list of tasks related to them that still need to happen.

    When someone from your team opens that profile, they have the full picture. Not the version of the story that lives in one person’s head, but the actual complete history of the relationship.

    That context changes how you work. Your salesperson doesn’t accidentally pitch someone who already bought. Your support team isn’t starting every conversation from scratch without knowing what the customer has been through. You don’t miss a follow-up because it was in someone’s personal inbox and they went on vacation.

    What a CRM Actually Does: The Core Functions

    Contact Management

    The foundation of any CRM is storing and organizing information about people. Every contact in your system has a record that includes their name, title, company, email, phone number, and whatever else you want to track. You can add custom fields to store the specific information your business cares about.

    This sounds simple, but the power is in how that data gets used. You can filter and segment your contacts in any way you need. Everyone in Chicago who hasn’t purchased in 90 days. Every prospect who came through your website form but hasn’t booked a call. Every customer on your highest-tier plan who’s up for renewal in the next 30 days. A good CRM lets you slice the data however you need it.

    Pipeline Management

    For most B2B businesses, a CRM’s pipeline view is what people use most. It’s a visual board showing where every deal stands in your sales process.

    A typical pipeline looks something like this, from left to right:

    • New lead
    • Contacted
    • Demo scheduled
    • Proposal sent
    • Negotiation
    • Closed won / Closed lost

    Every active deal lives somewhere on that board. You can see at a glance how many deals are in each stage, which ones have been sitting in one stage too long (usually a bad sign), and what the total value of your pipeline is. This is how founders and sales managers actually forecast revenue, not by guessing, but by looking at what’s actually in the pipeline and how deals historically convert from each stage.

    Activity Tracking

    A CRM logs every interaction. Sent an email? Logged. Had a phone call? Log the notes. Scheduled a demo? It’s in the calendar and attached to the contact record. This creates a complete timeline of every relationship.

    HubSpot does this particularly well. When you connect your Gmail or Outlook account, it automatically syncs your email history with your contact records without any manual work. You open a contact profile and you can see every email ever sent, automatically, without ever thinking about it.

    Task Management and Reminders

    This is one of the most underrated parts of a CRM for small teams. You can set tasks attached to specific contacts: “Follow up with this person on Thursday,” “Send contract by end of week,” “Check in with this customer 30 days post-purchase.” The CRM becomes your external memory for the entire relationship history.

    Studies show that 79% of leads never convert because of a failure to follow up. A CRM with task management is the fix for that specific problem.

    Reporting and Forecasting

    Once you have real data flowing into a CRM, the reporting gets genuinely useful. How long does it take a deal to move from demo to close on average? Which lead source generates the highest-value customers? What’s your conversion rate at each stage of the pipeline? Which salesperson is closing the most deals? Which customer segments are churning fastest?

    These aren’t hypothetical questions. They’re things a CRM answers with actual data so you can make decisions based on what’s true rather than what feels true.

    A Day in the Life: How a Founder Actually Uses a CRM

    Here’s a concrete example to make this real.

    You run a B2B software company with five people. You’re the primary salesperson and also doing everything else. Here’s what a normal morning looks like with a CRM in place.

    You open your CRM dashboard. You see a summary: 12 open deals in your pipeline, three of which have been in the “Proposal Sent” stage for more than two weeks with no activity. The CRM flagged them automatically. You send quick follow-up emails to all three, logged automatically.

    You have three tasks due today. One is to follow up with a prospect who asked for a custom pricing sheet last Tuesday. You open their record, see the full history of your conversation, attach the pricing sheet, and send it directly from the CRM. Logged.

    A new inbound lead came in overnight through your website contact form. The CRM automatically created a contact record, assigned it to you, and sent the lead an automated acknowledgment email. You review it, add some notes from a quick LinkedIn search, and schedule a call for Thursday.

    You check your pipeline total: $280,000 in potential deals across 12 active opportunities. Based on your historical close rate, that suggests about $85,000 in likely revenue over the next 60 days. This is the number you share with your investor in this week’s update call.

    The whole morning check-in takes 15 minutes instead of the 45 it used to take when all of this was scattered across your inbox, a spreadsheet, and whatever you could remember.

    When Do You Actually Need a CRM?

    Not everyone needs a CRM from day one. Here are the signals that tell you it’s time.

    You’re losing track of leads. If a prospect expressed interest and you can’t remember where the conversation is or what the next step was, you need a CRM.

    Deals are going cold because nobody followed up. This is the most common early-stage problem. The ROI case for a CRM is often just: “we stopped losing $X per month in forgotten follow-ups.”

    You have more than one person involved in sales. The moment two people are sharing responsibility for customers, you need a shared system. Otherwise you end up with two people reaching out to the same contact with no idea what the other person said.

    You’re trying to forecast revenue. You can’t forecast reliably from a spreadsheet. You need pipeline data to do this properly.

    You’re growing and can’t keep it all in your head. Somewhere around 20-50 active prospects, the mental overhead of tracking everyone becomes genuinely problematic.

    You want to understand your business. Which customers are most valuable? Where do your best customers come from? What makes deals close faster? These are CRM questions.

    On the flip side, you probably don’t need a CRM yet if you’re purely B2C and self-serve (people buy without talking to you), if you have fewer than a handful of active customer relationships, or if your entire business is one-off transactions with no repeat relationship component.

    The Most Common CRM Options for Founders and Small Teams

    The CRM market hit $126 billion in 2026 and is projected to reach $320 billion by 2034, which means there are roughly a thousand options. Here are the ones that actually come up most for early-stage founders.

    HubSpot

    HubSpot is the default recommendation for most early-stage founders, and for good reason. The free plan is genuinely impressive: unlimited users, up to 1,000 contacts, a visual pipeline, email integration with Gmail and Outlook, live chat, a basic landing page builder, and 2,000 email sends per month. For a small team just getting started with relationship management, this is a lot of functionality for zero dollars.

    HubSpot holds 62% of SMB CRM installations, which means the ecosystem of tutorials, integrations, and support resources is enormous. If you have a question, there are probably 50 YouTube videos answering it.

    The tradeoff is pricing at scale. HubSpot’s paid tiers jump significantly. Marketing Hub Professional, where you unlock serious automation, costs $890/month. Sales Hub Professional with the full feature set runs $100/seat/month. These are prices that make sense for funded startups and growing companies, but feel steep when you’re bootstrapped.

    For most founders, the recommendation is: start with HubSpot’s free CRM and stay on it until you either hit hard limits or have the revenue to justify the paid tier.

    Pipedrive

    Pipedrive is built specifically for sales teams that care primarily about the pipeline. The interface is more visual and sales-focused than HubSpot, with less emphasis on marketing features and more emphasis on deal management and activity tracking.

    The key difference from HubSpot: Pipedrive doesn’t have a free plan. It starts at $14/seat/month for the Essential tier, which includes the core pipeline and contact management features. The Advanced tier at $29/seat/month adds email sync and automation.

    Pipedrive tends to appeal to B2B founders who have tried other tools and found them too complex. The pipeline board is extremely clean. The activity reminders are genuinely useful. And the learning curve is gentler than Salesforce or a fully configured HubSpot instance.

    If your main need is “I need to track my deals and make sure I follow up,” Pipedrive is probably the cleanest tool for that specific job.

    Salesforce

    Salesforce is the enterprise standard. It serves 150,000+ customers including 83% of Fortune 500 companies. If you’re at a company that’s already medium-sized and you need something that will scale to hundreds of users with complex customization requirements, Salesforce is the answer.

    For early-stage startups: almost certainly overkill. Salesforce pricing starts at $25/seat/month for the basic Starter Suite, but the plans most growing companies actually use run $75-$165/seat/month. The implementation cost and complexity are significant. Most startups that implement Salesforce before they need it spend more time configuring it than using it.

    The exception: if you’re selling to enterprise customers and your buyers specifically ask “what CRM do you use,” being on Salesforce signals a certain level of operational maturity that can matter in enterprise sales cycles.

    ActiveCampaign

    ActiveCampaign sits in an interesting middle ground. It’s primarily an email marketing and automation platform, but it includes a CRM that works well for small B2B teams. The automation integration between the CRM and email is genuinely seamless, because it’s the same platform.

    The practical use case: you have a B2B product with a mix of marketing emails to a list and individual sales conversations. Instead of running HubSpot for CRM and MailerLite for email and paying for both, ActiveCampaign handles both in one place at a price point that starts around $49/month for the Plus plan.

    The CRM in ActiveCampaign isn’t as polished as HubSpot’s or Pipedrive’s, but it’s functional and the integration with the marketing automation is hard to replicate by stitching tools together.

    Keap

    Keap is worth knowing about for service-based small businesses. Consultants, agencies, coaches, health and wellness businesses, home services companies. It combines CRM, email marketing, appointment scheduling, invoicing, and payments in one platform.

    The breadth is the selling point. Instead of a CRM plus an email tool plus a scheduling app plus an invoicing tool, Keap covers all of it. The tradeoff is cost ($299/month starting price for up to 1,500 contacts) and a steeper learning curve than simpler tools.

    The One Mistake That Kills Most CRM Implementations

    Buying a CRM is easy. Getting your team to actually use it is the hard part. Research consistently shows that 43% of CRM implementations fail due to poor team adoption, and 32% of sales reps spend more than an hour a day on manual data entry in their CRM, often because the setup is too complicated.

    The single biggest mistake: implementing a CRM that’s more complex than your actual needs. When a CRM has 40 custom fields, 15 pipeline stages, and a configuration that took a consultant two months to build, nobody uses it correctly. The data becomes unreliable. The tool becomes a burden instead of an asset.

    The fix is to start with the simplest version that solves your current problem. Most early-stage founders need:

    • A place to store contact information
    • A pipeline to see where deals stand
    • Task reminders for follow-ups
    • Email history tied to contact records

    That’s four things. Pick a tool that does those four things well and don’t add complexity until you genuinely need it.

    HubSpot‘s free plan covers all four. Pipedrive‘s Essential plan covers all four. You don’t need a six-figure implementation to get started.

    CRM vs Spreadsheet: The Honest Comparison

    A lot of founders start tracking customers in Google Sheets and resist moving to a CRM because the spreadsheet “works fine.” Here’s when it actually stops working fine.

    Spreadsheets break down when:

    • Two people need to update it simultaneously (version conflicts, data corruption)
    • You need to send automated follow-ups based on pipeline stage
    • You want to see a visual pipeline view
    • You need to attach email history and call notes to specific contacts
    • You want to report on conversion rates, deal velocity, or revenue forecasting
    • Someone leaves the company and takes their spreadsheet knowledge with them

    Research from the CRM adoption space suggests that businesses dealing with 80-120 active quarterly opportunities see 25% pipeline leakage just from lost visibility when managing in spreadsheets. At that volume, the cost of not having a CRM is real.

    The threshold varies by business. Some founders manage 20 relationships fine in a spreadsheet. Others hit that same wall at 50. But eventually, the spreadsheet breaks, and the cost of rebuilding it as a real CRM at that point is higher than if you’d just set one up earlier.

    The Bottom Line

    A CRM is not complicated technology. It’s a system that makes sure you remember everything important about every person you’re in a business relationship with, and that none of those relationships fall apart because something got lost in the noise.

    The ROI case is strong. On average, businesses see $8.71 back for every dollar they spend on CRM software. Businesses using CRM report 41% increases in sales revenue. Lead conversion rates improve by up to 300% when CRM is used effectively.

    But the ROI only materializes if people actually use it. So pick something simple, configure it to match your actual process, and build the habit of logging things in it. The fanciest CRM in the world is worth nothing if your team keeps notes in their personal Gmail.

    Start with HubSpot free if you’re just getting going and want something with room to grow. Try Pipedrive if you want something sales-focused and clean without the complexity. Add sophistication when your actual business demands it, not before.

    The spreadsheet will break eventually. Better to move before it does than after.

    This article contains affiliate links. We may earn a commission if you sign up for a service through links on this page, at no extra cost to you. Our opinions are our own.

  • Do You Even Need Marketing Automation Yet? A Checklist for Early-Stage Founders

    Every SaaS article you read, every startup podcast you listen to, every investor tweet you scroll past eventually mentions marketing automation. Set up your drip sequences. Build your lifecycle emails. Automate your nurture flows. Get ActiveCampaign. Get HubSpot. Get everything talking to everything else.

    And if you’re an early-stage founder, you’re sitting there wondering: do I actually need any of this right now? Or am I about to spend two weeks setting up software instead of talking to customers?

    The honest answer is: it depends on what problem you’re actually trying to solve. Marketing automation is genuinely powerful when you have the right conditions for it. Adopted too early, it becomes an elaborate procrastination tool dressed up as productivity.

    This guide helps you figure out which camp you’re in.

    What Marketing Automation Actually Is

    Before getting into the checklist, let’s make sure we’re talking about the same thing, because “marketing automation” gets used to mean a lot of different things.

    At its core, marketing automation is software that runs marketing tasks automatically based on rules you define. Instead of manually sending a follow-up email to everyone who signed up, you set up a trigger: when someone joins your list, they automatically get a welcome email. When they don’t open anything for 60 days, they automatically get a re-engagement message. When they visit your pricing page three times without converting, they automatically get an email addressing common objections.

    You define the rules once. The system runs them forever.

    That’s the basic version. More sophisticated automation layers in lead scoring (assigning numerical scores to prospects based on their behavior), multi-channel orchestration (coordinating emails, SMS, and in-app messages based on what someone does), predictive analytics (using historical data to predict who’s most likely to buy or churn), and CRM integration (automatically moving leads through a pipeline based on behavior).

    The tools range from free plans on Brevo and MailerLite that include basic automation, all the way up to platforms like ActiveCampaign, HubSpot, Klaviyo, and Marketo that handle increasingly complex scenarios. The market for marketing automation software is estimated to hit $47 billion in 2026 and is on pace to double by 2028, which tells you how fast companies are adopting this.

    But none of that matters if your business isn’t ready for it.

    The Three Conditions That Make Automation Actually Work

    Before checking whether you need automation, understand what makes it valuable. Automation creates leverage. And leverage only matters when you have something worth leveraging.

    Condition 1: You have a repeatable customer journey.

    Automation is essentially a set of if-then rules. If someone does X, send them Y. This only works if you know what X and Y are. If you’re still figuring out your sales process, who your actual customers are, and what converts them, automation makes you faster at the wrong things.

    The founders who get the most out of automation are ones who’ve already done the process manually, know it works, and now want to scale it. Not ones who are hoping the software will figure out the process for them.

    Condition 2: You have enough volume for rules to matter.

    If you have 50 subscribers and you know them all personally, automation adds almost nothing. You can just email them. The point of automation is handling volume that would be impossible or impractical manually. Most founders start seeing real leverage from automation somewhere around 200-500 active contacts where manually tracking everyone becomes genuinely difficult.

    Condition 3: Your marketing is actually generating leads.

    Automation helps you nurture and convert the leads you have. It doesn’t create leads out of thin air. If your primary problem right now is “we’re not getting enough people in the top of the funnel,” automation is not the fix. Distribution, content, paid acquisition, and word of mouth are the fix. Don’t automate a process that isn’t working yet.

    The Checklist: Should You Set Up Marketing Automation Right Now?

    Work through these questions honestly. At the end, there’s a scoring key.

    Section 1: Your current situation

    1. Do you have at least 100 people on your email list or in your CRM?

    Yes / No

    If you have fewer than 100 people to communicate with, the ROI on setting up sophisticated automation is minimal. You can send personal emails. You can track things in a spreadsheet. The overhead of configuring a platform isn’t worth it yet.

    2. Are you currently generating new leads or subscribers consistently, even if slowly?

    Yes / No

    If the answer is no and you’re trying to figure out how to get your first 50 customers, that’s the problem to solve first. Automation helps with conversion and retention, not top-of-funnel creation.

    3. Have you validated that people actually want what you’re selling?

    Yes / No

    This sounds obvious but it’s not. A lot of founders build automation before they’ve confirmed product-market fit. If you’re still in discovery mode, learning what messaging works and which customer segments respond, automation will just bake your current guesses into a system that runs them at scale. Get the manual learning done first.

    4. Do you currently have any kind of consistent communication with your list?

    Yes / No

    Even if it’s just a sporadic newsletter or a one-time announcement, some history of sending matters. If you’ve never emailed your list, the automation question is premature. Send something first. Learn how your audience responds. Then automate the things that work.

    5. Are leads currently going cold because you can’t follow up with everyone personally?

    Yes / No

    This is one of the clearest early signals that automation is worth setting up. If you have people who expressed interest and then went quiet because you didn’t have time to follow up, that’s real money left on the table that automation can recover.

    Section 2: Your time and resources

    6. Are you spending more than 5 hours per week on repetitive email tasks (follow-ups, welcome messages, responses to common questions)?

    Yes / No

    If yes, that’s the automation telling you it wants to exist. Repetitive communication tasks are exactly what these tools are built to handle.

    7. Do you have time to set up automation properly?

    Yes / No

    This one matters. Setting up a proper welcome sequence, lead nurture flow, and basic segmentation takes real time upfront. Usually 8-15 hours for a simple setup, more if you want to do it well. If you’re in the middle of a fundraise, a major product launch, or any other crunch period, this is probably not the week to configure marketing automation. Rushed setups lead to broken sequences and embarrassing emails going out at the wrong time.

    8. Do you have a clear enough understanding of your customer journey to map it out?

    Yes / No

    You need to know: how do people find out about you? What do they need to see or understand before they’re ready to buy? What objections come up most often? What does the path from first contact to customer look like? If you can’t answer these questions with reasonable confidence, you’re not ready to automate the journey. Map it manually first.

    Section 3: Your business model

    9. Does your business model involve any of the following?

    • Subscription product (SaaS, membership, subscription box)
    • Ecommerce store with repeat purchase potential
    • High-ticket service with a multi-touch sales process
    • Content or newsletter business monetizing through ads or sponsorships

    Yes / No

    If yes: your business model has natural automation leverage points. Subscription businesses have onboarding, retention, and dunning sequences. Ecommerce has abandoned cart, post-purchase, and re-engagement flows. High-ticket services have lead nurture and proposal follow-up. These are proven, high-ROI automation categories.

    If no and you’re doing one-off project work, commodity services, or primarily in-person business: automation is less central to your growth model. It can still help, but it’s not the priority.

    10. Do you already have any automations running, even basic ones?

    Yes / No

    If you already have a welcome email set up or a basic drip sequence, you’ve already started. This question is about whether you should go deeper. If you don’t have even a welcome email yet, start there before anything else.

    How to Score Your Answers

    Count how many times you answered “yes.”

    0-3 yes answers: Not yet.

    You’re probably better off focusing on things that don’t involve software configuration right now. Talk to customers. Figure out your messaging. Get your first 100 subscribers. Send manual emails and learn what gets responses. Come back to automation in 60-90 days when you have more to work with.

    The one exception: even at this stage, set up a basic welcome email. It takes 30 minutes on any free platform and ensures that every new subscriber gets acknowledged automatically. That’s not “marketing automation” in the full sense, but it’s the seed of it.

    4-6 yes answers: Start simple.

    You’re ready to get the basics in place, but don’t overdo it. The right scope for you right now is:

    1. A welcome sequence (3-5 emails, automated, goes out to every new subscriber)
    2. A simple re-engagement sequence for people who’ve gone quiet
    3. Basic segmentation (separate new subscribers from customers)

    Pick a tool that’s easy to set up and has a free or low-cost tier you can grow into. MailerLite is a solid starting point for most businesses in this range. Brevo if you also need CRM functionality. Kit if you’re building an audience-first business.

    Don’t try to build the full Salesforce Marketing Cloud equivalent right now. Get the simple stuff working first.

    7-10 yes answers: Yes, you need this. Set it up properly.

    You have the conditions for automation to generate real leverage. The question now is which platform makes sense for your stage and business model.

    What to Automate First (In Order of ROI)

    If you’ve decided it’s time, here’s the sequence that generates the most value for the least complexity. Build these in order.

    1. Welcome sequence (highest ROI, start here)

    Every person who joins your list should get a series of 3-5 emails over the first 7-14 days. This is consistently the highest-performing email category, with welcome emails averaging around 83% open rates versus 30% for regular campaigns. It’s also one of the simplest things to set up.

    What the sequence should do:

    • Email 1 (immediately): Deliver whatever you promised in exchange for their email. Introduce yourself briefly. Set expectations for what they’ll hear from you.
    • Email 2 (day 2-3): Address the main problem your product or service solves. Be educational, not salesy.
    • Email 3 (day 5-7): Social proof. A customer story, a case study, or a specific result someone got.
    • Email 4 (day 10-14): Soft pitch or call to action. Ask them to try your product, book a call, or take whatever the next logical step is.

    That’s it. Four emails, set up once, running forever. Most platforms including MailerLite and Brevo let you do this for free.

    2. Abandoned cart / incomplete signup recovery

    If you have an ecommerce store or a product with a signup flow, recovering people who start and don’t finish is one of the highest-ROI automations that exists. Abandoned cart emails average around 50% open rates and recover 3-5% of lost sales on average. At scale, that’s significant money.

    For ecommerce, Klaviyo and Omnisend are the standard tools. For SaaS with incomplete signups or trials, ActiveCampaign or any platform with website event tracking works.

    3. Post-purchase or post-onboarding sequence

    Getting someone to buy once is good. Keeping them and getting them to buy again (or activate fully in your product) is better. A sequence that fires after a purchase or signup that helps people get value quickly is one of the highest-leverage automations for reducing churn and increasing lifetime value.

    This is often called an onboarding sequence in SaaS or a post-purchase follow-up in ecommerce. It typically runs 5-10 emails over 2-4 weeks and helps customers get results with what they just bought.

    4. Re-engagement sequence

    Email lists decay. People go quiet. A re-engagement sequence targets subscribers who haven’t opened or clicked anything in 60-90 days and either re-activates them or cleans them off your list. This matters because sending to disengaged subscribers hurts your deliverability metrics, which hurts your ability to reach the people who do want to hear from you.

    Most platforms have this as a pre-built automation template. It’s usually 2-3 emails: “Hey, we miss you, here’s something valuable,” then “Last chance to stay on the list,” then an automatic removal if they still don’t engage.

    5. Lead scoring and sales handoff (when you have a sales team)

    This is the more advanced territory. Once you’re generating enough volume, lead scoring automatically assigns scores to contacts based on behaviors (opened 3 emails, visited pricing page twice, downloaded a white paper = high score). When a score crosses a threshold, the contact gets automatically added to a sales pipeline and a salesperson gets notified to follow up.

    HubSpot and ActiveCampaign are the main platforms where this kind of workflow lives at a price point accessible to growing startups. It’s not a day-one automation, but it becomes very valuable as your inbound volume grows.

    The Tools That Match Each Stage

    Pre-automation / just starting: MailerLite or Brevo on free plans. Get the welcome sequence in place and nothing else.

    Building out the basics (100-500 contacts, simple automations): MailerLite paid ($10/month), Brevo Starter ($25/month), or Kit if you’re a creator. These cover welcome sequences, re-engagement, and basic segmentation without complexity.

    Getting serious (500-5,000 contacts, multiple sequences, basic segmentation): ActiveCampaign Starter or Plus tier is probably the right upgrade at this point. The automation builder is genuinely more powerful than what MailerLite and Brevo offer, and it handles more complex conditional logic without getting prohibitively expensive. Starts at $15/month but the useful plan for automation is $49-79/month.

    Ecommerce-specific: Klaviyo is the clear standard. Their abandoned cart, post-purchase, and browse abandonment flows are built specifically for online retail and outperform general platforms in that context. Omnisend is a strong second option at lower price points.

    B2B with a sales team: HubSpot Marketing Hub plus the free CRM is the most complete option for teams that want email automation and pipeline management in one place. The free CRM plus a MailerLite or ActiveCampaign subscription for email is a cheaper alternative that a lot of scrappy B2B teams use effectively.

    The Mistakes Founders Make When They Set This Up Too Early

    Building complex automations before validating the message.

    The most expensive kind of automation mistake is when a founder spends two weeks building a 10-email nurture sequence and then discovers that the messaging is completely wrong. The sequence runs automatically, sending the wrong message to every new subscriber indefinitely. You don’t find out for months because you’re not watching it.

    Always validate your email content manually first. Send it yourself. See what responses you get. Iterate. Then automate the version that actually works.

    Automating a broken process.

    If your manual outreach is generating no replies and no conversions, making it automated just means you’ll get no replies and no conversions faster and at larger scale. Automation multiplies what’s already working. It doesn’t fix what’s broken.

    Using software complexity as a substitute for strategy.

    This one is sneaky. Spending time configuring automation feels productive. It’s technical work, it involves software, and at the end of it you have something that looks impressive on a screen. But if you don’t have clarity on who you’re talking to, what they need to hear, and what action you want them to take, the sophistication of your automation platform is completely irrelevant.

    Get the strategy clear first. The software is just the delivery mechanism.

    Neglecting the automations after you build them.

    Most founders build their welcome sequence, watch it for a week, and then never look at it again. Automation is not set-it-and-forget-it forever. Offers expire. Products change. Messaging gets stale. Build a quarterly review into your process where you check open rates, click rates, and conversion rates on your key sequences and update them based on what you find.

    The One Automation You Should Set Up Regardless

    Here’s the thing: even if you answered “no” to most of the checklist questions, there’s one automation that’s worth setting up in the next hour, not next month.

    A welcome email.

    Not a sequence. Not a nurture flow. Just a single automated email that goes out the moment someone subscribes to your list.

    It should:

    • Thank them for subscribing
    • Remind them who you are and what you do in one sentence
    • Tell them what they can expect to receive from you
    • Deliver whatever you promised them when they signed up

    That’s it. If you have a free tool like MailerLite or Brevo already set up, you can configure this in under 30 minutes. Welcome emails get the highest open rates of any email category, averaging 68-83% depending on the platform and industry. Every new subscriber you get without this in place is getting a weaker first impression than they could be.

    This is the zero-controversy, no-brainer automation that every single founder should have running before anything else.

    The Bottom Line

    Marketing automation is a force multiplier, not a foundation. It amplifies what’s already working. It handles at scale the communication that you’ve already validated manually. It frees you from repetitive tasks so you can focus on the strategic things that only you can do.

    Used at the right time, it’s one of the highest-ROI investments in your marketing stack. Used too early, it’s a sophisticated way to avoid talking to customers.

    If you scored 0-3 on the checklist: go talk to customers, get clearer on your message, and build your list manually for a while. Come back to this in 60 days.

    If you scored 4-6: set up a welcome sequence and one re-engagement automation. Don’t go further until those are working.

    If you scored 7-10: you’re leaving real money on the table by not having this in place. Pick a platform that fits your business model and budget, and get the foundational sequences built this week.

    The welcome email first. Everything else after.

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  • The Best Free Email Marketing Tools for Startups With Under 1,000 Subscribers

    Here’s the thing nobody tells you when you’re first building your list: you do not need to pay for email marketing software when you’re just getting started.

    Not $50/month. Not $30/month. Not even $10/month. There are genuinely solid free plans out there that will cover you until you’re well past 1,000 subscribers, and picking the wrong one early can cost you time migrating later.

    The catch is that “free” means different things depending on who’s saying it. Some platforms call themselves free but limit you to 14 days. Some give you a free plan that’s so stripped down you can’t actually do anything useful without upgrading. And some are legitimately free with real features that let you run an actual email program.

    This guide is only about that last category. Every tool on this list has a real free tier you can use indefinitely, not just a trial. And every one of them is specifically useful for founders, small business owners, and early-stage teams who are building their first list.

    What You Actually Need at Under 1,000 Subscribers

    Before getting into the tools, it’s worth being clear about what matters at this stage and what doesn’t.

    At under 1,000 subscribers, you don’t need:

    • Advanced predictive analytics
    • Multi-touch attribution reporting
    • Complex conditional logic across 10-step automation trees
    • A dedicated IP address for sending
    • Enterprise-grade CRM integration

    At under 1,000 subscribers, you do need:

    • A reliable way to collect email addresses (signup form or landing page)
    • A welcome email or short welcome sequence that goes out automatically
    • A simple way to send occasional campaigns to your whole list
    • Basic analytics (opens, clicks, unsubscribes)
    • Something you can actually figure out without a tutorial

    That’s the bar. Everything else is nice to have but not necessary at this stage.

    The Free Tier Landscape in 2026

    A few things have shifted recently that are worth knowing before you pick a tool.

    Mailchimp cut its free plan significantly in early 2026, dropping from 500 contacts to 250 contacts with 500 monthly sends. It used to be the obvious starting point for most people. It’s still usable for the very earliest days, but you’ll hit the ceiling fast if you’re actually trying to grow.

    Brevo restructured its free plan around email volume rather than contact count, which is a fundamentally different approach than every other tool on this list. You can store unlimited contacts for free, but you’re limited to 300 emails per day. More on why this matters below.

    Kit (formerly ConvertKit) raised its free plan limit to 10,000 subscribers, which is genuinely remarkable. But automation on the free plan is extremely limited, which undercuts a big part of what makes Kit worth using.

    Sender quietly became one of the most generous free plans on the market: 2,500 subscribers and 15,000 emails per month, with automation included. Most people outside the email nerd community haven’t heard of it yet.

    The Best Free Email Marketing Tools, Broken Down Honestly

    MailerLite: Best overall free plan for most early-stage founders

    Free plan: 1,000 subscribers, 12,000 emails per month

    MailerLite is the tool that comes up most consistently in conversations among founders who’ve tried a few platforms and settled on something they actually like using. The interface is clean without being sparse. The drag-and-drop editor is genuinely good. And critically, the free plan includes automation, which most free tiers gut entirely.

    What you get on free: the full drag-and-drop email builder, automation workflows, landing pages, signup forms and pop-ups, and basic analytics. The limitation is that MailerLite branding shows up in your email footer, you can’t use a custom HTML editor, and templates are locked behind the paid plan. None of that is a dealbreaker when you’re just starting out.

    The paid plan starts at $10/month for up to 1,000 subscribers with unlimited sends, which is among the cheapest upgrade paths in the industry. At 5,000 subscribers you’re paying $32/month. That’s reasonable.

    One thing worth knowing: MailerLite has a notoriously strict account approval process. When you sign up, they review your account and may ask what your business does and how you collected your subscribers. This is annoying if you’re in a rush, but it’s actually a feature masquerading as a bug. Because they keep their platform clean of spammers, their shared sending infrastructure has better deliverability than platforms that let anyone in. Your emails are more likely to land in the inbox.

    Best for: Small businesses, newsletters, creators, and early-stage founders who want a clean tool that actually works without much setup.

    Outgrow it when: You hit 1,000 subscribers or need advanced features like A/B testing and remove-branding options, at which point the $10/month paid plan is an easy upgrade.

    Brevo: Best free plan if your list is growing fast but you send infrequently

    Free plan: Unlimited contacts, 300 emails per day (~9,000/month)

    Brevo’s free plan is structured entirely differently from everyone else, and it’s worth understanding why that matters.

    Most email platforms charge based on how many contacts you store. This means your monthly bill goes up automatically as your list grows, even if you’re not sending more emails. If you add 500 subscribers this month, you pay more next month whether or not you send them anything.

    Brevo charges based on emails sent, not contacts stored. The free plan lets you store as many contacts as you want, forever, for free. You just can’t send more than 300 emails per day (about 9,000 per month). For a startup that sends one weekly newsletter to a list that’s growing quickly but isn’t huge yet, this is the most founder-friendly pricing structure in the market.

    The catch: 300 emails per day sounds like a lot until you actually think about it. If you have 1,000 subscribers and want to send a campaign to all of them at once, you’d need to send in batches over four days. That’s manageable but mildly annoying. If you have 500 subscribers and send once a week, you’ll never hit the limit.

    Beyond the free plan, Brevo has added a lot of functionality in recent years. Full CRM features, SMS and WhatsApp marketing, transactional email (for things like order confirmations and password resets), and a deal pipeline. It’s become a more complete platform than its “email tool” reputation suggests.

    One more thing: the paid plans are competitive. Starter at $25/month removes the daily send limit and Brevo branding. Business at $65/month adds A/B testing, advanced reporting, and a dedicated account manager at higher tiers.

    Best for: Startups with growing lists who send low-to-moderate volume, and anyone who also needs basic CRM functionality in the same tool.

    Outgrow it when: You need to send large campaigns to your whole list at once and the 300/day limit becomes operationally frustrating.

    Sender: Most generous free plan limits in 2026

    Free plan: 2,500 subscribers, 15,000 emails per month, automation included

    Sender is the underdog on this list. Most founders haven’t heard of it, which is surprising given that it has arguably the most generous free tier available right now. 2,500 subscribers and 15,000 monthly sends at no cost, with automation and segmentation included.

    To put that in context: Mailchimp‘s free plan gives you 250 contacts and 500 sends. Sender gives you 10 times more subscribers and 30 times more sends, for the same price (zero).

    The tradeoff is that the platform is less polished than MailerLite and less full-featured than Brevo. The template library has about 60 options, most of which are decent but not exceptional. The drag-and-drop editor works but isn’t as intuitive as MailerLite’s. There’s no native landing page builder on the free plan.

    But if your only constraint is budget and you want to maximize what you can do for free, Sender covers you for longer than almost anything else. Capterra reviewers give it a 4.7/5 across hundreds of reviews, with consistent praise for deliverability and support quality.

    Paid plans start at around $15/month and hit $39.90/month at 10,000 subscribers with SMS features, whitelabeling, and up to three users included.

    Best for: Very early-stage founders who need to maximize free tier limits and are comfortable with a less polished tool.

    Outgrow it when: You want better templates, a landing page builder, or more advanced automation logic.

    Kit (formerly ConvertKit): Best free plan for creators and newsletter operators

    Free plan: Up to 10,000 subscribers, unlimited email sends, limited automation

    Kit is the outlier here because of the sheer size of what they offer for free: 10,000 subscribers with unlimited sends. That’s legitimately remarkable and much more generous than anything else on this list at the subscriber level.

    The catch is that Kit’s automation features are heavily limited on the free plan. You get one automation and one email sequence. That’s it. If you want to build multiple behavioral sequences, tag-based automations, or anything remotely complex, you need a paid plan. Paid starts at $15/month for up to 300 subscribers, which jumps to $49/month at 3,000 subscribers and $79/month at 5,000. Kit’s pricing isn’t cheap once you’re paying.

    What Kit’s free plan is genuinely great for: building a newsletter or content-based audience, collecting subscribers through landing pages, and sending regular broadcast emails to your list. The platform is built specifically for creators (bloggers, podcasters, YouTubers, course creators, newsletter operators), and that focus shows in how well it handles the basics of audience-building.

    The subscriber tagging system is intuitive. The landing page editor is solid. And you can actually sell digital products and paid subscriptions directly through Kit, which is unique and genuinely valuable if you’re monetizing an audience.

    The free plan also requires you to display Kit’s recommended newsletters to your subscribers when they sign up. That’s a bit annoying because it means competitors can appear in your opt-in flow. You can turn this off on paid plans.

    Best for: Newsletter operators, bloggers, podcasters, and anyone building an audience-first business where the free 10K subscriber limit is the headline feature.

    Outgrow it when: You need real automation (more than one sequence), which means moving to a paid plan fairly quickly. If you’re a SaaS or ecommerce company, Kit probably isn’t the right fit regardless of price.

    HubSpot: Best free plan if you also need CRM functionality

    Free plan: 2,000 emails/month, 1,000 contacts (in the free CRM)

    HubSpot’s free plan isn’t really an email marketing plan. It’s a free CRM that happens to include email marketing features. That distinction matters because it shapes how the tool is built and what it’s actually good at.

    The free tier gives you contact storage for up to 1,000 people, 2,000 email sends per month, 20 landing pages, one sales pipeline, live chat, and Gmail/Outlook integration that automatically logs email conversations to contact records. For a B2B founder managing a combination of marketing emails and individual sales conversations, this is a remarkably complete free offering.

    The email marketing features themselves are solid but not exceptional. One basic template, a functional drag-and-drop editor, and basic analytics. No A/B testing, limited automation, and HubSpot branding on your emails. For pure email marketing you’d want MailerLite or Sender instead.

    But if you’re building a B2B business where you need to track individual deals alongside marketing campaigns, the HubSpot free CRM + email combo covers both reasonably well without paying anything. The real power is that everything is in one place: your prospects, your pipeline, your email campaigns, and your customer records all live together.

    The paid marketing tiers start at $20/month for the Marketing Hub Starter, which adds email send limits up to 5x your contact tier, removes HubSpot branding, and adds some basic automation. The Professional tier at $890/month is where the platform gets genuinely powerful but that’s well beyond early-stage territory.

    Best for: B2B founders who want CRM and email marketing in one free tool, and who are managing both individual sales conversations and list-based campaigns.

    Outgrow it when: You need serious marketing automation capabilities, at which point the jump to HubSpot’s paid tiers is steep. At that point, combining HubSpot’s free CRM with ActiveCampaign for email automation is often a better value.

    Mailchimp: Fine for absolute beginners, quickly limited

    Free plan: 500 contacts, 1,000 sends per month

    Mailchimp used to be the default recommendation for anyone just starting out. The free plan was genuinely generous, the brand recognition meant abundant tutorials and third-party integrations, and the interface was familiar enough that even non-technical founders could get going quickly.

    Then they cut the free plan. Hard. In recent years, the contact limit dropped from 2,000 to 500, and sends dropped to 1,000/month. By early 2026, unsubscribed contacts still count toward your billing cap unless you manually archive them, which is a gotcha that surprises a lot of people when they try to figure out why they’re being billed for contacts who aren’t even on their list anymore.

    At 500 contacts, you’ll hit the ceiling within a few months of actively building your list. And the free plan only includes single-step automations, meaning you can set up a welcome email but not a multi-email welcome sequence. For that you need the Essentials plan at $13/month.

    Mailchimp is still a fine tool. The brand is recognized everywhere, integrations are plentiful, and the editor is solid. But for founders starting fresh in 2026, MailerLite or Brevo offer more value at the zero-dollar tier by a significant margin.

    Best for: People who specifically want Mailchimp for its brand recognition or existing integrations, and are okay upgrading quickly.

    Outgrow it when: Pretty much immediately if you’re actively growing your list, at which point the $13/month Essentials plan is the minimum viable paid tier.

    GetResponse: Solid free plan with a webinar twist

    Free plan: 500 contacts, unlimited monthly emails, one landing page

    GetResponse doesn’t get talked about as much as the others on this list, but the free plan is worth knowing about. Unlimited monthly emails to 500 contacts is a strong ratio, and they include a landing page builder and basic automation on the free tier.

    What makes GetResponse interesting, even at this level, is the webinar functionality that shows up in paid plans. If you’re running a business where live events, demos, or educational webinars are part of your sales motion, GetResponse is one of the only platforms in this price range that handles email marketing and webinar hosting natively. The webinar attendee cap starts at 100 on lower paid tiers.

    The editor was recently redesigned and is clean and functional. The automation builder is visual and genuinely easier to learn than some competitors. The template library has hundreds of options.

    Paid plans start at $19/month for the Starter tier (1,000 contacts), which is competitive. The Marketer plan at $59/month unlocks the full automation capabilities.

    Best for: Founders who send content-heavy newsletters and also run live events, demos, or webinars as part of their marketing.

    Outgrow it when: You hit 500 contacts or need more than one landing page and basic automation.

    How to Actually Choose Between These

    The “which one is best” question doesn’t have a universal answer. It depends on your specific situation. Here’s a quick decision framework:

    You’re a B2C or ecommerce founder with a growing list: Go with Brevo. The unlimited contacts on the free plan means you won’t hit a ceiling for a long time, and the multi-channel capabilities (email + SMS) give you room to expand without switching tools.

    You’re a newsletter operator or content creator: Kit is the obvious choice if you want to stay free as long as possible. The 10,000 subscriber free plan is unmatched. Just know that real automation requires upgrading.

    You want the best balance of free features and upgrade path: MailerLite is the safest pick for most early-stage founders. The editor is excellent, automation is included, landing pages are included, and the $10/month paid plan is a painless upgrade when you’re ready.

    You want maximum free limits without caring about polish: Sender is worth trying. 2,500 subscribers and 15,000 sends for nothing is genuinely the most generous free tier on the market in terms of raw capacity.

    You’re B2B and need CRM + email in one place: HubSpot‘s free plan is the move. Don’t think of it as an email tool with CRM features. Think of it as a free CRM that happens to let you send email campaigns.

    You want name recognition and don’t mind hitting limits quickly: Mailchimp is fine. Just know you’ll be upgrading faster than you expect.

    Things to Watch Out For When Signing Up for Free Plans

    A few things trip people up that are worth knowing in advance.

    Hidden contact counting. Some platforms count unsubscribed contacts against your plan limit. Mailchimp is the main offender. If you have 400 active subscribers and 200 unsubscribes, some plans still count all 600 against your limit. Read the fine print before you hit a surprise billing wall.

    Automation gating. The most common way free plans limit you isn’t subscriber count, it’s features. Most platforms give you basic single-step automation on free tiers and require an upgrade for multi-step sequences. If automations are important to you from day one, MailerLite, Brevo, and Sender are the three options that don’t gut automation on the free tier.

    Branding in your emails. Every free plan except HubSpot adds the platform’s branding to your email footer. “Powered by MailerLite” or “Sent with Brevo.” For most early-stage businesses this is fine. If you need clean unbranded emails, that’s a paid feature on every platform.

    Deliverability on day one. When you first create an account, your sender reputation is essentially zero. Most platforms put new accounts through a brief review or warm-up period. MailerLite‘s account approval process is the most thorough but leads to better deliverability outcomes. Don’t be surprised if your first few campaigns have slightly lower delivery rates than the benchmarks you read about online.

    The migration tax. Every platform makes it easy to import your list. What’s harder is rebuilding your automations, recreating your templates, and moving your signup forms if you decide to switch tools later. Pick something you can see yourself staying with for at least 12-18 months.

    What Happens When You Actually Need to Pay

    Most founders hit the ceiling on free plans somewhere between three and nine months after getting serious about building their list. Here’s what the upgrade path looks like for the top picks:

    • MailerLite: $10/month for 1,000 subscribers unlimited sends. $19/month at 2,500. $32/month at 5,000. Very predictable.
    • Brevo: $25/month removes the daily send limit and adds more features. $65/month for the Business plan with A/B testing and advanced reporting.
    • Kit: $15/month for up to 300 subscribers. $49/month at 3,000. $79/month at 5,000. Gets expensive faster than the others.
    • Sender: $15/month for up to 2,500 subscribers. $39.90/month at 10,000. Competitive throughout.
    • HubSpot: $20/month for Marketing Hub Starter. Jumps hard at higher tiers.
    • Mailchimp: $13/month for Essentials (500 contacts). $20/month for Standard. $350/month for Premium at 10,000 contacts, which is not competitive.

    The honest answer: if you’re past 1,000 subscribers and using email strategically, paying $10-25/month is a genuinely good business investment. The ROI math on email is so strong that almost any paid plan pays for itself quickly once your list is actively converting.

    A Note on What NOT to Do

    A few things founders do with email that cause more damage than starting with the wrong free tool:

    Using Gmail BCC to send to your list. If you’re emailing 100 people by putting them all in BCC, stop immediately. Gmail will flag your account, you have no way to track results, there’s no opt-out mechanism (which is legally required), and you’re building nothing durable. Any of the free tools above is better than this.

    Buying an email list. This deserves repeating because people still do it. Buying a list of “10,000 targeted leads” and blasting them is spam. It will crater your sender reputation, get your account suspended on any reputable platform, and generate basically no revenue. Build your list organically.

    Waiting until you have a “real” list to start. The best time to get your email setup in place was before your first subscriber. The second best time is right now. Set up your welcome sequence, get your signup form live, and start building the habit of sending. Even a list of 50 people is worth nurturing correctly from the beginning.

    The Bottom Line

    For most founders building their first email list in 2026, the right starting point is MailerLite or Brevo. MailerLite if you want the cleanest tool with the best editor and a reliable upgrade path. Brevo if your list is growing fast and you want to avoid contact-based pricing for as long as possible.

    If you’re a creator or newsletter operator, Kit’s free tier up to 10,000 subscribers is hard to beat on paper, just know that real automation requires paying.

    If you’re B2B and also running a sales pipeline, HubSpot’s free plan covers both in a way nothing else does for free.

    The tool matters less than using it consistently. Pick one, get your welcome sequence in place, start collecting emails, and send something worth reading. The platform you start on can always be changed later. The list you build stays with you.

    This article contains affiliate links. We may earn a commission if you sign up for a service through links on this page, at no extra cost to you. Our opinions are our own.

  • Email Marketing vs CRM: What’s the Difference and Which Do You Actually Need

    If you’ve spent more than ten minutes researching tools for your business, you’ve probably run into both terms and come away more confused than when you started. Some tools call themselves CRMs. Some call themselves email marketing platforms. Some claim to be both. And a lot of the comparison articles out there assume you already know what each thing does.

    So let’s back up completely and answer this the right way.

    They Are Not the Same Thing

    People conflate these two categories constantly, and it makes sense why. Both involve contacts. Both involve communication. Both live in your software stack and both promise to help you “grow your business.” But they solve fundamentally different problems.

    Here’s the cleanest way to think about it:

    Email marketing is one-to-many. You’re sending a message to a list of people. It might be a newsletter, a promotional offer, a product announcement, or an automated sequence. The goal is to reach a large group of people at once and move them toward some kind of action.

    A CRM is one-to-one. You’re tracking individual relationships. Who did you talk to? When? What did they say? Where are they in the sales process? What’s the next step? The goal is to make sure no relationship falls through the cracks and that every person in your pipeline gets the right attention at the right time.

    Another way to frame it: email marketing manages campaigns, a CRM manages relationships.

    Both matter. They’re just built for different jobs.

    What Email Marketing Software Actually Does

    An email marketing platform is built around one core function: getting messages to a large number of people efficiently and tracking how those people respond.

    The main things these tools give you:

    List management. You store subscriber email addresses, and you can organize them into segments based on shared characteristics (where they signed up, what they’ve purchased, how long they’ve been on your list, etc.).

    Campaign creation. A drag-and-drop builder for designing emails, plus templates so you don’t have to start from scratch.

    Automation. The ability to set up sequences of emails that trigger based on behavior. Someone signs up, they get a welcome email. They don’t open anything for 60 days, they get a re-engagement email. They abandon their cart, they get a recovery email.

    Analytics. Open rates, click rates, unsubscribe rates, revenue attributed to each campaign. The data you need to understand what’s working.

    Deliverability infrastructure. The unglamorous backend stuff that makes sure your emails actually land in inboxes instead of spam folders. This includes managing your sender reputation, handling bounces, and maintaining compliance with email regulations like CAN-SPAM and GDPR.

    What email marketing software is NOT built for: tracking individual sales conversations, managing a pipeline of deals, logging phone calls and meetings, or giving your sales team visibility into where each specific prospect stands in a buying process.

    That’s what a CRM does.

    What a CRM Actually Does

    CRM stands for Customer Relationship Management. At its core, it’s a system that keeps track of every interaction you’ve had with every customer or prospect, so nothing gets lost and you always know what needs to happen next.

    The main things a CRM gives you:

    Contact records. Every person you’re in a relationship with gets a profile: their contact info, their company, their job title, your entire history of communication with them, notes from calls, emails sent and received, deals attached to them.

    Pipeline management. A visual representation of where every deal stands. Someone expressed interest, someone got a demo, someone is reviewing a proposal, someone is about to sign. A good CRM shows you all of this at a glance and flags what’s stalled.

    Activity tracking. Log calls, meetings, and emails so you have a full history. Some CRMs (HubSpot is the best example) sync with Gmail and Outlook and log email conversations automatically without you having to do anything manually.

    Task management and reminders. “Follow up with this person on Thursday.” “Send the contract to this contact by end of week.” The CRM makes sure those things don’t slip.

    Reporting. How many deals are in your pipeline? What’s your average close rate? Which lead source generates the highest-value customers? A CRM answers these questions with actual data instead of guesswork.

    What a CRM is NOT great at: sending mass email campaigns to thousands of people, building automated drip sequences for subscriber lists, or managing the kind of one-to-many communication that email marketing tools are designed for.

    There’s some overlap, especially with newer platforms that try to do both. But understanding the core job of each helps you figure out what you actually need.

    A Real Example of How Each Gets Used

    Say you run a B2B software company. You have two different things happening at the same time:

    The marketing side: You write a weekly newsletter and send it to 3,000 subscribers. When someone new signs up, they automatically get a five-email onboarding sequence over two weeks. You run a promotion once a quarter and send a campaign to your full list. You track which emails get opened, which links get clicked, and what drives trial signups.

    That’s all email marketing. A tool like ActiveCampaign, MailerLite, or Kit handles this.

    The sales side: You have 40 active prospects in various stages of a sales conversation. Sarah at OneSignal got a demo last Tuesday and asked for a pricing sheet. Marcus at Greenfield Capital is reviewing a proposal and you need to follow up Thursday. A new inbound lead from your website filled out a contact form and needs to be called within the hour. You need to track all of this, log every interaction, and make sure nothing falls off your radar.

    That’s CRM territory. A tool like HubSpot, Pipedrive, or Salesforce handles this.

    Now here’s where it gets interesting for founders: depending on what kind of business you’re running, you might need one, the other, or both.

    Which One Do You Actually Need?

    This comes down to your business model and where you are right now.

    You probably only need email marketing if:

    • You’re selling primarily to consumers (B2C)
    • Your sales process is self-serve (people buy without talking to anyone)
    • You’re at early stage with a small list you can manage manually
    • Your revenue comes from volume (lots of small transactions) rather than individual high-value deals
    • You run a newsletter, content business, or creator operation

    In this case, start with something like Brevo or MailerLite if you’re on a tight budget, or ActiveCampaign once you’re ready to get serious about automation. You don’t need a full CRM cluttering up your workflow when your sales process doesn’t involve individual sales conversations.

    You probably only need a CRM if:

    • You’re selling primarily to businesses (B2B)
    • Your sales involve actual conversations (demos, proposals, negotiations)
    • You’re closing individual deals worth $1,000+
    • Your biggest risk is leads going cold because nobody followed up
    • You have a sales team, even a small one

    Pipedrive is a great starting point here, especially if your team is sales-focused and doesn’t need a lot of marketing automation. HubSpot‘s free CRM is worth trying too, specifically because of how well it integrates with Gmail and the quality of the free contact management tools.

    You probably need both if:

    • You’re a B2B company that also does significant content marketing or email nurture
    • You have both a sales team managing individual deals AND a marketing function sending campaigns to a list
    • Your business model involves both high-value contracts and ongoing subscription customers
    • You’re scaling and you can’t afford leads falling through the cracks in either direction

    Most companies that grow past $1M-2M ARR end up running both. The question is when it makes sense to add that complexity.

    The Danger Zone: Using the Wrong Tool for the Job

    This is worth spending a minute on because a lot of early-stage founders make one of two mistakes.

    Mistake 1: Using a CRM as an email marketing tool.

    Some founders put all their contacts in a CRM and try to send marketing emails from it. The problem is most CRMs are not built for this. They don’t have great deliverability infrastructure. They’re not optimized for list segmentation at scale. They don’t give you the automation capabilities that a real email marketing platform provides. You end up with clunky campaigns and mediocre results.

    Mistake 2: Using an email marketing tool as a CRM.

    This is even more common. A founder stores their prospects and customers in Mailchimp or ActiveCampaign and uses it as their de facto contact database. The problem: these tools are not built to track sales pipelines, log individual interactions, or give you deal-level visibility. You lose track of who needs follow-up, deals go cold, and you have no real view into your sales process.

    The overlap exception here is platforms that genuinely do both well. ActiveCampaign has a CRM built in that’s solid for small B2B teams. HubSpot is the strongest all-in-one option if you can justify the cost. Keap is worth looking at for service-based small businesses that want both in one place.

    But for most early-stage founders, the right answer is to pick the right tool for your current biggest problem and add the other one when the need is clear.

    The Tools Worth Knowing for Each Category

    Email Marketing Platforms

    Brevo: Best for budget-conscious founders who need both email and a basic CRM in one. Free plan includes email, SMS, and a contact database. Their pricing is based on emails sent rather than contacts stored, which is rare and founder-friendly.

    MailerLite: Cleanest interface in the category. Great for creators, newsletters, and small businesses that want to get up and running fast. Free up to 1,000 subscribers, $10/month after that.

    ActiveCampaign: The most powerful automation builder in the small-to-mid-market. If you want to build complex behavioral sequences and you’re willing to invest time learning the platform, this is probably the best pure-automation tool available under $100/month. They also have a lightweight CRM included.

    Kit (formerly ConvertKit): The default choice for newsletter operators, creators, and anyone building an audience. The tagging and segmentation system is intuitive. Free plan up to 10,000 subscribers.

    Klaviyo: If you’re running an ecommerce store, this is the standard. Their abandoned cart flows and post-purchase sequences are built specifically for online retail and outperform general-purpose tools in that context.

    Mailchimp: The name everyone knows. Still a fine starting point, though the free plan was cut to 250 contacts in early 2026. Starts to feel limited as you scale.

    CRM Platforms

    HubSpot: The most generous free CRM on the market. Stores up to 1,000 contacts, sends 2,000 emails/month on the free plan, and integrates with Gmail and Outlook automatically. The free version is genuinely good. Paid tiers get expensive quickly but the tool is best-in-class at each level.

    Pipedrive: A sales-focused CRM with a clean visual pipeline. Best for B2B sales teams that want to see exactly where every deal stands without a ton of extra features getting in the way. Starts at $14/seat/month.

    Keap: Built for service-based small businesses (consultants, agencies, health and wellness, home services). Combines CRM, email marketing, appointment scheduling, and invoicing. More expensive than pure-play tools but covers a lot of ground.

    Salesforce: The enterprise standard. Overkill for most startups and small businesses, but if you’re at a stage where you have a real sales team and need serious customization and reporting, it’s the platform that everything else eventually integrates with.

    What Most Founders Actually Do

    Here’s the real-world picture: most founders start with just an email marketing tool because it’s cheaper, simpler, and solves the immediate problem of “I need to communicate with people on my list.”

    Then one of two things happens. Either they add a CRM when they realize they’re losing track of sales conversations (usually happens around the time they hire their first salesperson or start closing bigger deals). Or they switch to an all-in-one platform like HubSpot or ActiveCampaign that handles both well enough for their stage.

    The worst thing you can do is spend three months evaluating tools instead of just picking one and starting. The best email marketing platform is the one you’re actually using. The best CRM is the one your team actually logs things in.

    If you’re under $500K ARR and primarily B2C or self-serve: start with Brevo or MailerLite, get your email program running, and revisit the CRM question when sales conversations become a real part of your process.

    If you’re B2B from day one with an actual sales motion: start with HubSpot’s free CRM and add a proper email marketing layer (either HubSpot’s paid marketing tools or a separate platform like ActiveCampaign) once you’re generating enough leads to justify it.

    What Happens When You Combine Them

    When your email marketing and CRM are connected, some genuinely powerful things become possible.

    The biggest one is context. Without integration, your marketing team knows who opened an email but not whether that person became a customer. Your sales team knows who they talked to but not what emails that person received before they reached out. You have two incomplete pictures and nobody has the full story.

    When the tools talk to each other, a salesperson can pull up a contact record and see every email that person received, which ones they opened, which links they clicked, and what they looked at on your website before booking a call. That context changes the entire conversation. Instead of starting cold, you’re starting with “I noticed you were looking at our enterprise pricing page last week, did you have questions about that?”

    The other major benefit is the handoff automation. When a lead reaches a certain score in your email marketing platform (based on opens, clicks, and behavior), they can automatically get pushed into your CRM as a qualified lead and trigger a task for a salesperson to follow up. No manual work, no leads slipping through the cracks, no “I thought you were handling that” moments.

    Most of the platforms in this space now offer native integrations or built-in versions of both tools. HubSpot is the most seamless because they built the CRM and the marketing platform together from the start. ActiveCampaign‘s CRM is lighter but works well for smaller teams. Brevo has added CRM features over the past year that make it a reasonable one-stop option for early-stage businesses.

    Signs You’ve Outgrown Your Current Setup

    Sometimes you don’t know you need to add a tool until things start breaking. Here are the signals to watch for.

    You need a CRM when:

    • You have more than 20-30 active prospects and you’re losing track of who needs follow-up
    • A deal fell through because nobody followed up for three weeks and you only realized it after the fact
    • You hired a second person on the sales side and now two people need visibility into the same pipeline
    • You’re trying to forecast revenue and you have no reliable data to work from
    • Customers are complaining about being contacted by multiple people at your company who don’t know what the other already said

    You need a proper email marketing platform when:

    • You’re sending campaigns from Gmail to a BCC list of 50 people (please stop doing this)
    • You have more than a few hundred contacts and you’re managing them in a spreadsheet
    • You have no welcome sequence and new subscribers just go cold
    • You keep meaning to set up automated follow-ups but haven’t because the tools you have don’t support it
    • You’re running promotions and you have no way to track whether they generated any revenue

    You need both when:

    • You’re doing content marketing and inbound lead generation at the same time as outbound sales
    • Different team members are responsible for marketing and sales and they need separate but connected tools
    • You’re starting to think about customer lifetime value and retention, not just acquisition

    The Pricing Reality

    One of the things that makes this decision frustrating is the way these tools are priced. Both categories have gotten significantly cheaper over the last few years, which is good. But the pricing models are different enough that they’re hard to compare directly.

    Most email marketing platforms charge based on the number of contacts on your list. The more subscribers you have, the more you pay. This makes sense because their core cost is email delivery volume. MailerLite charges $10/month for up to 1,000 subscribers, $19/month up to 2,500, and so on. ActiveCampaign starts at $15/month for basic plans but the automation features that actually make it worth using are behind the $79/month Pro tier.

    Brevo is an exception here. They charge based on emails sent per month rather than contact count, which is genuinely founder-friendly if you have a large list but don’t email frequently. You can have 50,000 contacts and pay nothing as long as you stay under their daily send limit on the free plan.

    CRMs typically charge per seat (per user per month). HubSpot‘s free CRM is a genuine exception since you can have unlimited users for free. Pipedrive starts at $14/seat/month. Salesforce starts at $25/seat/month for basic features, but the plans most companies actually need run $75-$150/seat/month.

    The all-in-one platforms that do both email marketing and CRM tend to charge per seat or per contact and bundle everything. HubSpot’s Marketing Hub starts at $20/month but you need the Professional plan at $890/month to unlock the automation features that make it competitive with standalone email tools. ActiveCampaign bundles a CRM for free at most tiers. Keap starts at $299/month for up to 1,500 contacts, which is expensive but covers CRM, email, SMS, and payments in one place.

    The honest advice: don’t over-invest in tooling at the start. Pick the cheapest option that solves your current problem and upgrade when you hit real limitations. Thousands of successful businesses were built on MailerLite and a free HubSpot CRM. You don’t need enterprise software to make enterprise money.

    A Quick Decision Framework

    If you’re still not sure which direction to go, answer these four questions:

    1. Do you have individual sales conversations with prospects before they buy? Yes: you need a CRM. No: email marketing alone might be enough for now.

    2. Do you have more than 500 people you want to communicate with regularly? Yes: you need a real email marketing platform, not Gmail. No: you can get away with simpler tools short-term.

    3. Is your sales cycle longer than a week? Yes: you definitely need a CRM to track where things stand. No: self-serve email marketing might cover you.

    4. Do you have both a marketing function and a sales function that need to stay aligned? Yes: you need both tools connected. No: one tool that does both reasonably well might be enough.

    Most early-stage founders answer “no” to question 1 and “yes” to question 2. That puts you squarely in email marketing platform territory to start. Add the CRM when individual sales conversations become a core part of how you close business.

    The Bottom Line

    Email marketing and CRMs are not competing tools. They’re complementary. Email marketing handles the one-to-many communication that turns strangers into prospects and prospects into customers. CRMs handle the one-to-one relationship management that closes deals and keeps customers around.

    Most businesses need both eventually. But you don’t need both on day one.

    Figure out which problem is actually costing you money right now. Are you losing people because they sign up and then forget about you? That’s an email marketing problem. Are deals going cold because nobody followed up? That’s a CRM problem. Start there, solve that, and add the other piece when it earns its place in your stack.

    This article contains affiliate links. We may earn a commission if you sign up for a service through links on this page, at no extra cost to you. Our opinions are our own.

  • The Lattice Success Story: They Watched a Fast-Growing Startup Lose Its Culture at 100 Employees and Built a $3 Billion Platform to Fix That

    Something happens to a lot of fast-growing companies around the time they cross 100 employees.

    Below that threshold, culture is largely self-managing. The founding team is still close enough to most decisions that their values propagate through direct example. People know each other. New hires get absorbed into an existing dynamic through proximity and osmosis. The CEO is visible. Feedback flows through hallway conversations. Goals are known because everyone is in the same room when they’re set.

    Then headcount doubles and doubles again. The founder can no longer have lunch with every new hire. Managers are managing for the first time, with no training and no framework. Employees don’t know how their day-to-day work connects to company strategy. Performance reviews, if they happen at all, are annual conversations that employees dread and managers put off. OKRs get written down in a planning session, approved by leadership, and then quietly forgotten until the next quarter.

    Jack Altman and Eric Koslow watched this happen at Teespring, the print-on-demand e-commerce platform where they both worked in the early 2010s. Teespring was growing fast, revenue and headcount together, and as the company crossed 100 and then 150 employees, the culture got genuinely hard. People didn’t know how their work connected to company goals. Managers weren’t equipped. Feedback was inconsistent or absent. The things that made working at a small startup energizing were harder to find at the larger company Teespring was becoming.

    Altman and Koslow looked at this problem and didn’t see it as inevitable. They saw it as a product gap.

    Princeton, AngelList, and the Question Nobody Had Solved

    Altman had studied economics at Princeton and spent time at AngelList in various venture capital-adjacent roles before Teespring, picking up operational and investor perspective across early-stage companies. He had seen, from multiple angles, how the “people problem” at scaling companies played out and how rarely anyone had real infrastructure to address it.

    His brother is Sam Altman, who at the time was president of Y Combinator and is now CEO of OpenAI. The Altman name carries weight in the startup ecosystem, but Jack’s founding story for Lattice is not primarily a story about connections. It’s a story about a problem he observed firsthand and couldn’t stop thinking about.

    In 2015, Altman and Koslow incorporated Lattice in San Francisco. They went through Y Combinator’s Winter 2016 batch, with backing from Thrive Capital in an early seed round. The first product launched in May 2016: a goal management tool.

    OKRs on a Shelf and the Pivot to Continuous Reviews

    The initial product addressed the OKR problem that both founders had experienced directly. Companies would run planning sessions where leadership aligned on quarterly objectives and key results. Everyone would nod. The objectives would be documented. And then, reliably, the document would sit untouched until the next planning cycle.

    The problem wasn’t the framework. OKRs are a reasonable way to align organizations around shared priorities. The problem was that there was no infrastructure making them visible or actionable on a day-to-day basis. Goals set in a Google Doc with no ongoing tracking or team-level visibility didn’t change behavior.

    Lattice’s goal management tool made OKRs live in a system where employees could see how their individual objectives connected to team and company goals, update progress, and have that progress visible to their manager in regular check-ins.

    But in talking to customers and prospects during 2016, Altman and Koslow kept running into a related and arguably bigger problem: the performance review.

    The annual performance review was in the middle of what they described as an identity crisis. Companies had largely concluded that once-a-year evaluations were bad: they were backward-looking, they were often primarily a mechanism for calibrating compensation rather than developing people, they were conversations that both sides dreaded and managers routinely avoided scheduling until HR forced them to, and the feedback they contained was so delayed from the events it referenced as to be nearly useless for improvement.

    Companies knew the annual review was broken. They did not know what to replace it with.

    Lattice’s answer was continuous performance management: structured 1:1 meetings between managers and their direct reports on a regular cadence, ongoing feedback loops rather than bottlenecked annual events, visibility into goals and progress throughout the year rather than a single retrospective, and when a formal review did happen, a record of actual documented conversation rather than a manager trying to recall eight months of interactions.

    In 2016, Lattice became one of the first software solutions built specifically for continuous performance review. The timing was not accidental: the conversation about killing annual reviews was accelerating, companies like Adobe had publicly dropped their annual review process and described the results positively, and the HR practitioner community was actively looking for alternatives. Lattice had one.

    Dog-Fooding the Product and Growing Through Customers

    Altman was explicit about one deliberate product strategy: Lattice used its own software for everything it was selling to customers. Every performance review, every 1:1 meeting template, every OKR cycle at Lattice ran through Lattice. The people team was the internal customer, and the engineers and product managers building the software could see real frustrations from colleagues using it daily.

    This created feedback loops that external customer conversations couldn’t replicate. When something was genuinely clunky, someone inside the building felt it and said something at a meeting the product team attended. When a feature shipped that made something meaningfully easier, the internal team noticed before any external case study could be written.

    By April 2019, when Lattice raised a $15 million Series B led by Shasta Ventures, the company had 1,200 customers including Reddit, Slack, Coinbase, and Glossier. The same round confirmed that the company had reached cash flow break-even for the first time in Q1 2019, which in the SaaS world of 2019 was unusual. Most performance management software companies were burning cash aggressively to grow.

    The 60-person company serving 1,200 customers at break-even was a different statement about the business than what the fundraising narrative of the era usually produced.

    The Pandemic and the $3 Billion Valuation

    The conditions of 2020 and 2021 were complicated for most businesses and clarifying for Lattice.

    Remote work, which COVID transformed from optional to mandatory almost overnight, surfaced every problem that Lattice had been built to solve. The informal culture machinery of a co-located office, the hallway conversations, the lunchtime visibility into what colleagues were working on, the ambient sense of shared purpose that came from being physically present together, all of it disappeared. What remained was whatever intentional infrastructure companies had built for connecting employees to each other and to the company’s goals.

    Companies that had already invested in performance management systems, structured feedback processes, and documented goal tracking found those systems more valuable than before. Companies that had relied on the office as their culture infrastructure discovered they had very little underneath it.

    Lattice grew five times in revenue between the start of the pandemic and early 2023. The platform expanded from its performance management core into employee engagement surveys, eNPS tracking, career development pathing through the Grow product, compensation management, and data analytics.

    In March 2021, Lattice raised at a $1 billion valuation. Ten months later, in January 2022, it raised again: $175 million in a Series F led by Dragoneer, with participation from Tiger Global, Founders Fund, Thrive Capital, and Elad Gil, valuing the company at $3 billion. The valuation had tripled from the prior round in ten months.

    Altman’s framing of the moment captured what had shifted: “We are staring at a box all day now, and we don’t have a manager who comes by and says ‘great job’ and makes us feel appreciated. Systems like Lattice give a process for how we connect and interact and make sure that I know that I am cared for by our manager as a professional and a person.” COVID had created what he called a tailwind. The remote work transition had made explicit what was previously implicit, that connection and feedback and career development didn’t happen automatically and required intentional infrastructure.

    15% Layoffs, Leadership Transitions, and the HRIS Bet

    The reversal came in January 2023. Lattice laid off 15% of its workforce, over 100 people. The company’s revenue had grown five times since the start of the pandemic, but costs had grown faster, in anticipation of continued pandemic-era growth rates that had not materialized as the labor market cooled.

    The same week, the company was also named to the Deloitte Technology Fast 500. Both things were true simultaneously.

    In May 2022, Eric Koslow had stepped down as CTO to start another company, remaining on the board. In December 2023, Jack Altman stepped down as CEO, saying he wanted to “return to his first love: the earliest stages of company-building.” He transitioned to Executive Chairman. He also co-founded OpenStore, a company that acquires and scales Shopify brands, during this period.

    Sarah Franklin became CEO in January 2024, bringing a background as a senior executive at Salesforce, where she had run major product lines and built deep experience in enterprise software. Her appointment signaled the next phase: Lattice was entering a larger market and needed enterprise go-to-market capabilities to match.

    The major product bet announced in late 2023 was Lattice HRIS: a full human resource information system to complement the performance and engagement suite. The thesis was that mid-market companies were managing their people across a fractured HR stack, using one system for employee records, another for performance management, another for compensation, and another for payroll. By adding a native HRIS, Lattice could become the central system of record for everything people-related, rather than one important product that had to integrate with the system of record owned by someone else.

    The mid-market gap Altman identified was real: below a certain company size, all-in-one platforms like Gusto and BambooHR serve well. Above a certain size, Workday and SAP SuccessFactors are the answer. In between, the options are messier and more expensive to integrate. Lattice was aiming at that gap.

    The AI Employees Controversy

    In July 2024, Lattice made a move that became one of the more discussed missteps in HR tech of the year.

    Under CEO Sarah Franklin, on July 9, Lattice announced that it would allow customers to create official employee records in Lattice for AI agents, what the company called “digital workers.” The idea was that companies deploying AI models for actual work, like an AI sales assistant or a code generation agent, could give those agents personnel files, assign them managers, set goals for them, and track their performance through Lattice’s platform. Franklin described it as treating AI responsibly by holding it accountable through the same systems used for human employees.

    The backlash was immediate and severe. Critics argued the announcement was tone-deaf, coming one and a half years after Lattice had laid off 15% of its human workforce. The language of “making history” by treating AI agents like employees landed poorly with workers already worried about job displacement. “Treating AI agents as employees disrespects the humanity of your real employees,” wrote one AI company executive in a widely shared LinkedIn comment.

    Three days later, on July 12, Lattice reversed course. The digital workers feature would not be pursued. Franklin acknowledged it had been a “big misunderstanding” while maintaining that the underlying question of how HR should govern AI usage in the workplace remained important and was “HR’s moment.”

    What the episode revealed was the tension that every HR tech company is navigating: AI is clearly changing work, HR platforms need to address that change, and the specific framing matters enormously. The underlying impulse, giving companies a systematic way to think about AI agents deployed alongside human workers, was arguably forward-looking. The execution and messaging landed in a way that resonated badly with the audience most concerned about AI displacing them.

    $127 Million in Revenue and What Comes Next

    By 2024, Lattice reported approximately $127 million in revenue, up from $91 million in 2023. The customer base sits around 3,700 to 5,000 companies depending on the measure, including Slack, Gusto, Webflow, Intercom, Ramp, and NPR. The company employs roughly 537-600 people.

    The HRIS product, Lattice’s most ambitious product expansion, is its defining near-term bet. If mid-market companies adopt a Lattice HRIS alongside the performance management and engagement suite, the company becomes stickier and more central to how those companies operate. If the HRIS gains traction slowly or fails to differentiate from established competitors like BambooHR, Rippling, and Gusto, Lattice remains a very good point solution for performance management while the larger market opportunity goes elsewhere.

    The company Jack Altman and Eric Koslow started because Teespring’s culture cracked under growth pressure has become the software that tens of thousands of managers use to give structured feedback, track goals, run 1:1 meetings, and conduct performance reviews. The core insight, that culture at scale doesn’t happen by accident and requires intentional infrastructure, turned out to be a durable and large market.

    The OKRs that sat on a shelf are now tracked in Lattice. The annual reviews that companies knew were broken now run on a continuous cadence through the same platform. What Altman called the earliest stages of company-building are where he’s working now, at another company, backed by the $3 billion validation that the problem he identified in 2015 was worth solving.

  • The DoorDash Success Story: Four Stanford Students, a Palo Alto Macaroon Shop, and the Suburban Bet Nobody Thought Would Work

    Tony Xu was nine years old and mowing lawns for money when his family arrived in Champaign, Illinois from Nanjing, China. He and a friend would take on yards in the neighborhood and charge extra if the customer wanted a pattern cut into the grass, like a checkerboard. His mother, Julie Cao, had been a doctor in China. In Illinois she opened acupuncture and medical clinics. She also worked in restaurants when the clinics were slow. Tony washed dishes in those restaurants. He has talked about watching his mother work in interviews over the years, usually as context for why he cared about building something that helped small businesses stay alive.

    The connection between washing dishes at his mother’s restaurant as a kid and building the largest food delivery company in the United States is not a straight line. But it is the kind of background that explains why, when four Stanford students were trying to pick a startup idea in the fall of 2012, Tony Xu was the one pushing hardest toward the restaurant problem.

    The Macaroon Shop on University Avenue

    In the fall of 2012, Tony Xu was in his first year at the Stanford Graduate School of Business. Evan Moore was his classmate. They were working on a project for a class called Startup Garage, which was exactly what it sounds like: a structured excuse to talk to people about problems and see if anything was worth building.

    They were focused on small businesses. Not restaurants specifically, just whatever local merchants were struggling with most. They walked up and down University Avenue in Palo Alto, knocked on doors, and asked owners what kept them up at night. The answers were consistent across a lot of different business types: getting enough customers, having employees show up for shifts, and figuring out how to compete with larger competitors.

    Then they walked into a macaroon shop and the conversation changed.

    The owner, a woman named Chloe, had a binder on the counter full of delivery orders she had never been able to fulfill. Customers had called asking for delivery. She had written down the orders. She couldn’t act on any of them because she had no way to make deliveries happen. The demand was clearly there. The infrastructure to serve it wasn’t.

    Xu and Moore had a moment of recognition when they saw that binder. They called around to a few more restaurants on the way back. Most didn’t offer delivery at all. The ones that did said it was the most operationally painful part of running their business. They were turning away delivery orders constantly. The gap between what customers wanted and what restaurants could provide was enormous, and nobody had built a reliable on-demand solution to bridge it.

    Xu reached out to Andy Fang and Stanley Tang, two Stanford computer science undergraduates he had met earlier. Tang had published a book about making money online when he was fourteen, which gave him a certain credibility among people who cared about building things. Fang was a strong engineer. The four of them decided the restaurant delivery problem was worth pursuing.

    They built a website that same week. It had PDF menus for eight local restaurants, their phone numbers for placing orders, and a very basic interface. The domain was PaloAltoDelivery.com. They drove the deliveries themselves. They did this in January 2013, before they had any funding, before they had any drivers, before they had incorporated. They wanted to know if people would actually pay for this.

    They did.

    Y Combinator and the First Real Crisis

    They applied to Y Combinator and got in for the Summer 2013 batch, which came with $120,000 in exchange for 7% of the company. They incorporated as DoorDash in June 2013. The name was meant to convey speed and directness, someone dashing to your door.

    The product was still very bare. Orders came in, Dashers picked them up and delivered them. The technology was basic and the operational process was improvised. They were doing everything manually and learning what broke.

    The first real test came in September 2013 during a home football game at Stanford. Football games bring a lot of people to campus, and a lot of those people, along with fans watching nearby, apparently decided to order food. DoorDash received more orders that afternoon than they had ever handled, probably around a hundred, and they were not ready for any of it.

    Every single order was late. Some were over an hour behind. The founders were fielding complaints while simultaneously trying to dispatch drivers who were already stretched thin. Xu later described it as one of the worst days in the company’s first few months.

    After the game, the team had a decision to make. They had very little cash left, maybe a week or two of runway. If they refunded everyone, they might run out of money. If they didn’t, they’d have a customer satisfaction disaster on record.

    They refunded every order. Then they stayed up all night baking cookies and delivered them to every affected customer before five in the morning, with a handwritten note apologizing for the experience.

    The cookie delivery has become a famous story in DoorDash’s history. What it actually demonstrates is a specific thing about how the founders thought about operations: they were not going to let a bad experience stand, even when it cost them money they couldn’t afford to spend. That instinct, that a bad experience needed to be personally corrected by the founders rather than handled through a policy, shaped how DoorDash thought about its logistics problems for years.

    The Suburban Bet That Everyone Thought Was Wrong

    By 2014, DoorDash had raised a $2.4 million seed round led by Khosla Ventures and a $17.3 million Series A led by Sequoia. They were growing in Palo Alto and starting to expand to San Francisco and other Bay Area cities.

    The competitive landscape they were entering looked difficult. Grubhub had been operating since 2004 and was firmly established in dense urban markets like New York and Chicago. Seamless had merged with Grubhub in 2013. Postmates was operating in San Francisco. Eat24 was active. Uber was starting to experiment with delivery. The conventional wisdom was that food delivery was fundamentally a city business, that the economics only worked in dense areas where drivers could complete multiple deliveries per hour and restaurants were close enough to customers to keep food hot.

    DoorDash made a decision that most observers at the time thought was wrong. They went to the suburbs.

    The reasoning was not complicated, but it required trusting the analysis over the received wisdom. Suburbs had almost no delivery infrastructure. Restaurants there weren’t set up for delivery at all. Grubhub wasn’t there. Uber wasn’t there. If DoorDash could get in first and build relationships with suburban restaurants and suburban customers, they could own that market without a price war.

    There were also some secondary advantages to the suburban market that the founders had thought through. Suburban orders tended to be larger on average, because families with children ordering dinner spent more per order than single people in city apartments. Suburban customers also had fewer alternatives, which meant they were less likely to churn to a competitor when one showed up. And suburban restaurants, especially chain restaurants like Buffalo Wild Wings and Cheesecake Factory, were often willing to pay for delivery because it opened up a meaningful new revenue stream for them.

    As DoorDash signed deals with national chains in suburban areas, those chains ran their own marketing campaigns advertising that their food was now available for delivery. DoorDash got brand awareness in suburban markets as a byproduct of the restaurant partners’ own advertising.

    This was not obvious genius at the time. The company struggled to raise its Series B in 2015. Xu has said publicly that they had term sheets pulled at the last minute during that round and came close to running out of money. Investors were skeptical of the suburban strategy. On-demand delivery was seen as a city product, and the general sentiment toward on-demand startups in 2015 had soured after a period of overinvestment in the space.

    They got the Series B done eventually and kept going.

    How DoorDash Actually Operates

    One thing that distinguished DoorDash from some competitors was how seriously the founders took the logistics side of the business.

    Xu did not think of DoorDash as a restaurant app. He thought of it as a logistics company that happened to start with restaurants. The target, which he stated publicly in early interviews, was to become the world’s largest software-enabled logistics company, capable of moving anything, not just food. The restaurant focus was a starting point because food was a product people needed delivered multiple times a day, which generated the order density needed to build a reliable delivery network.

    The founders were personally doing deliveries in the early days for the same reason they had been personally doing them since the PaloAltoDelivery days: they wanted to understand what was hard about it from the driver’s perspective, not just from the customer’s perspective. They showed up at restaurants as Dashers. They waited in lines. They dealt with wrong orders. They drove across suburban neighborhoods looking for addresses. They came back to the product and made changes based on what they had learned.

    DoorDash built machine learning models to predict how long each restaurant would take to prepare an order, so Dashers could be dispatched at the right time rather than arriving too early and waiting. They optimized routing so Dashers weren’t driving inefficient paths. They built tools for restaurants to manage their menus and adjust their hours in real time. The logistics technology was not the visible product, but it was what determined whether the delivery arrived in thirty minutes or fifty.

    DashPass launched in 2018 as a subscription service for frequent users. For a monthly fee, subscribers got free delivery on qualifying orders. The logic was borrowed from what Amazon Prime had demonstrated in e-commerce: customers who paid a subscription became more loyal and ordered more frequently. If a DashPass subscriber was going to pay $9.99 per month regardless, they had an incentive to use DoorDash enough to justify the cost. By 2024, DashPass had over 15 million subscribers, and those subscribers ordered substantially more often than non-subscribers.

    The 2019 Inflection and Passing Grubhub

    By early 2019, DoorDash had overtaken Grubhub as the largest food delivery platform in the United States by market share. This was not a slow or quiet transition. Grubhub had been the dominant player for years and had the better-known brand in most cities. DoorDash had been building in suburban markets that Grubhub didn’t take seriously, and by the time Grubhub noticed the threat, DoorDash had established strong enough customer relationships in enough markets to defend its position.

    The ranking flipped partly because DoorDash had expanded aggressively in suburban America while Grubhub stayed focused on its urban strongholds, and partly because DoorDash’s restaurant partnerships with national chains had given it distribution and brand recognition in markets where Grubhub had little presence.

    At that point DoorDash considered deals with both Postmates and Uber Eats, according to Fortune. The conversations didn’t result in anything. DoorDash decided it didn’t need them.

    Then the pandemic happened.

    The Pandemic and What It Did to the Market

    When COVID-19 shut down restaurant dining rooms in March 2020, what had been a strong but competitive food delivery market became something much more concentrated.

    People who had never ordered delivery before started ordering it constantly. People who lived in cities moved to suburbs, often in a hurry, which pushed demand into exactly the market DoorDash had spent years building. Restaurants that had resisted delivery as too operationally complex signed up in weeks because it was the only way to keep any revenue coming in.

    DoorDash’s business more than tripled in 2020. Revenue went from $885 million in 2019 to $2.88 billion in 2020, a 226% increase in a single year. Market share went from under 35% to over 50% by year’s end.

    Matt Maloney, the CEO of Grubhub at the time, later told Fortune that he had a front-row seat to what happened: “I kind of view their whole long bet on suburban delivery as, ‘Holy shit, I had a front row seat to witness this miracle.’”

    The suburban strategy that had been mocked internally and by investors for years had positioned DoorDash perfectly for a pandemic that pushed millions of Americans out of cities and into suburban homes where DoorDash was often the only delivery option that worked reliably.

    DoorDash went public on the New York Stock Exchange on December 9, 2020, under the ticker DASH. The IPO raised $3.37 billion. On the first day of trading, the stock opened at $182 and ran as high as $195, an 86% gain from the $102 offer price. The valuation on the first day hit around $70 billion.

    Three of the four founders, Xu, Fang, and Tang, became billionaires overnight. Evan Moore, the fourth co-founder, had left the company after 17 months and had moved on to other things. He later became an investing partner at Khosla Ventures.

    After the IPO: Building Past Food

    The company that went public in December 2020 was primarily a restaurant delivery platform. The company that exists today is something considerably broader, and that expansion was by design.

    In November 2021, DoorDash announced the acquisition of Wolt, a Finnish food delivery company with strong positions across Europe and the Middle East. The deal valued Wolt at approximately $8 billion and gave DoorDash a meaningful international footprint it had lacked. Wolt operated in 23 countries, mostly in Europe and Central Asia, with particular strength in Scandinavia, Eastern Europe, and Israel.

    The Wolt acquisition was important for a specific strategic reason: DoorDash’s dominance in the United States did not translate to global leadership. Internationally, Uber Eats and Deliveroo had head starts in many markets. Buying an established player rather than building country by country was faster and less expensive in terms of both money and time. By 2023, DoorDash had grown Wolt’s subscriber base significantly and reported over 30% MAU growth in its international markets year over year.

    On the product side, DoorDash pushed beyond restaurant food aggressively. Grocery delivery, convenience store delivery, alcohol delivery, pet food, pharmacy items, and household goods all came onto the platform. The company signed partnerships with Walmart, Walgreens, PetSmart, and other retailers, turning DoorDash’s Dasher network into a general-purpose last-mile delivery service rather than just a food delivery service. DashMart, a company-owned convenience store concept designed for delivery, launched in 2020 and expanded to additional markets.

    The advertising business developed into a meaningful revenue line. Restaurants and brands could pay for sponsored placement in DoorDash’s app, and by late 2024, that advertising segment was running at a $1 billion annual rate. This was a high-margin business that didn’t require additional Dashers or deliveries, it just required DoorDash to have enough consumers on the platform that advertisers cared about reaching them.

    DashPass continued growing. From 15 million subscribers in 2023, the program expanded to 26 million by some estimates by early 2026, and was extended through partnerships with Chase credit cards, Lyft, and other consumer brands that bundled DashPass access as a benefit.

    The Driver Controversy That Followed the Company

    No account of DoorDash is honest if it skips the part about the Dashers.

    The company has faced consistent legal and ethical criticism over how it treats the contractors who actually make the deliveries. In 2017, a class-action lawsuit was filed claiming DoorDash was misclassifying delivery drivers as independent contractors rather than employees, which would have entitled them to minimum wage, overtime, benefits, and other protections. A tentative settlement in 2022 involved DoorDash paying $100 million total, with around $61 million going to over 900,000 drivers. That averaged out to about $130 per driver.

    The same year that settlement was reported, Tony Xu received a compensation package valued at approximately $413 million, which Gizmodo pointed out in coverage of the settlement, making the comparison between what the drivers received and what the CEO received fairly stark.

    In January 2020, reporting revealed that DoorDash had been using customer tips to offset the baseline pay it owed drivers rather than adding the tips on top of base pay. If a customer tipped $5 and DoorDash had guaranteed the driver $7 per delivery, DoorDash would pay $2 and count the $5 tip toward the $7 guarantee. The driver got $7 either way, but DoorDash pocketed the tip instead of passing it through. The company changed the policy under public pressure.

    Separately, DoorDash was criticized for years for not showing Dashers the full tip amount before they accepted a delivery, meaning drivers couldn’t factor tips into their decision about whether a particular delivery was worth the distance and time. This was addressed but slowly.

    These issues are not unique to DoorDash, Uber Eats and Instacart have faced similar criticism around gig worker classification and pay, but they have followed DoorDash more persistently because DoorDash is the largest player in the market. The company’s legal history includes additional disputes over antitrust price manipulation, listing restaurants without permission, withholding sick time, and a data breach in 2019 that exposed information for 4.9 million customers, workers, and merchants.

    The business grew despite all of this, which reflects something real about how delivery consumers and merchants make decisions. They chose the platform that was most reliable, most available, and covered the most restaurants, and for most Americans outside of major cities, that was DoorDash.

    Where It Stands

    By the end of 2024, DoorDash held approximately 60.7% of the US food delivery market by consumer sales, ahead of Uber Eats at 26.1% and Grubhub at 6.3%. That’s not a close race. In Q1 2025, the company reported $3.03 billion in revenue, up 20.7% year over year, and posted a GAAP net income of $193 million, its first sustained period of profitability after years of losses. Marketplace Gross Order Value hit $23.1 billion in the quarter.

    DoorDash also acquired Deliveroo in late 2025, the UK-based delivery platform that had been operating in Britain and several other markets. That deal gave DoorDash a major presence in the UK, the largest English-speaking food delivery market outside the United States, and put it into direct competition with Uber Eats across Europe in a way the Wolt deal alone hadn’t fully accomplished.

    Tony Xu still runs the company. Andy Fang is still CTO. The company debuted on the Fortune 500 in 2024 at number 443.

    The four founders who built the first version of the product out of a Stanford classroom project had made something that didn’t exist before: a functional, at-scale on-demand delivery network covering most of the United States, including the parts of the country that every competitor had decided weren’t worth serving. The business was built in those overlooked places, one suburban neighborhood at a time, while larger and better-funded competitors fought over dense cities and left the rest of the country alone.

    When the pandemic hit and half the country suddenly needed food delivered to their homes, DoorDash was already there.

  • The Duolingo Success Story: Luis von Ahn Had Already Sold Two Companies to Google. Then He Decided to Teach the World Languages for Free.

    Luis von Ahn grew up in Guatemala City going to a private English-language school, and he knew exactly why his mother had sent him there.

    English was the ticket. Not just in Guatemala but across most of the world, being able to speak and read English changed what jobs you could get, what universities would accept you, what economic life was available to you. Von Ahn’s mother understood this well enough to pay for an expensive private school. Most Guatemalan families couldn’t. The people who needed English the most were the ones with the least access to it, and the main reason was money. A decent language course cost hundreds of dollars. A private tutor cost more. The software products like Rosetta Stone cost upward of $500 for a full program.

    Von Ahn filed this observation away and went on to have a genuinely unusual academic career. He studied math at Duke, got his PhD in computer science at Carnegie Mellon, and became a professor there in 2006. Before Duolingo he had already built two products that Google bought. The first was CAPTCHA, the distorted-text test that websites use to tell humans from bots, which he co-developed with Manuel Blum in 2000. The second was reCAPTCHA, a cleverer version of the same idea: instead of showing users random distorted text, it showed them scanned words from old books and newspapers that computers couldn’t read accurately, and used the aggregate human responses to digitize those texts. Every time someone solved a reCAPTCHA, they were helping digitize the New York Times archive or a library of old books. Google bought reCAPTCHA in 2009. Von Ahn has said he sold it for “a lot of money.”

    After the sale he was still teaching at Carnegie Mellon and started thinking about what to build next. The Guatemala observation came back. Language learning was expensive and the people who most needed it were the people least able to pay for it. He thought a free language learning platform could do something meaningful there. His graduate student at the time, Severin Hacker, who was Swiss and had grown up speaking Swiss German, thought so too. The two of them started working on it in 2009 and officially founded Duolingo in 2011.

    The First Business Model, and Why It Had to Change

    The original version of Duolingo was built around a clever economic mechanism that von Ahn had thought up. It was the same basic insight he had used with reCAPTCHA: make something useful to people and use the byproduct of their activity to generate value for someone else.

    The idea was that people learning a language would practice by translating real content from the web. A company that needed documents translated, CNN or BuzzFeed or a law firm, would pay Duolingo for those translations. Duolingo would use that revenue to fund free lessons. Learners got free education. Paying clients got translations. The work the learners did to practice was the same work the clients needed done.

    It was a genuinely elegant concept, and it didn’t work.

    The translation model had two problems. First, translation quality from beginners is inconsistent. You can aggregate lots of translations and use statistical methods to get to something reliable, but scaling that process turned out to be operationally messy. Second, and more importantly, the learner experience that made for good translation practice did not make for good language learning. Teaching someone Spanish so they can accurately translate a CNN article about financial regulation is a different goal than teaching them to have a conversation or understand a movie. The two optimizations pulled in different directions.

    By 2014 or so, Duolingo had largely moved away from the translation model and toward a straightforward freemium approach: the app was free, with ads showing up between lessons. If you wanted an ad-free experience and a few extra features, you paid for Duolingo Plus, which launched as a paid tier in 2017. The core lessons stayed free.

    Von Ahn has been consistent about this ever since. The product that teaches people languages will always be free. The subscription tier is for people who want a better experience, not for people who want access to the thing at all.

    300,000 People on the Waiting List Before Anyone Could Use It

    When Duolingo launched its private beta in November 2011, over 300,000 people were already waiting for access. By the time the app opened to the public in June 2012, that number had grown to around 500,000.

    This was not the result of a paid marketing campaign. Von Ahn had given a TED talk earlier that year explaining what Duolingo was going to be and why he was building it. The talk spread, people signed up for the waitlist, and by the time the app launched, there was already a substantial audience waiting.

    The early version of the app had five languages: English, Spanish, French, German, and Portuguese. It was gamified from day one. Lessons were broken into short segments. You earned points for completing them. If you got too many wrong answers in a row, you lost a “heart” and had to restart the lesson. A daily streak tracked how many consecutive days you had done at least one lesson.

    The streak turned out to be one of the most important product decisions in Duolingo’s history, though it didn’t look that way at first. Von Ahn has explained the origin of it directly: he and Hacker were trying to learn each other’s languages during the building of the app. Von Ahn was working on Spanish lessons for Hacker, a native Swiss German speaker; Hacker was building German lessons for von Ahn. Every morning von Ahn would come into the office and ask Hacker if he had done his Spanish lesson the day before. The answer was usually no. They needed some automated mechanism to create daily accountability. The streak was that mechanism.

    By the end of 2024, over 10 million Duolingo users had maintained streaks longer than a year. One in five daily active users had a streak exceeding 365 days. A feature invented because two founders kept forgetting to do their homework became the psychological backbone of the product.

    Building the Course Library Without Building All the Courses

    One thing Duolingo got right early was recognizing it could not build every language course itself.

    After the initial launch with five languages, users started asking for more. Obscure languages, minority languages, endangered languages, and in a few cases fictional ones. There was demand for courses in Klingon, in Navajo, in Hawaiian, in High Valyrian from Game of Thrones. Duolingo did not have the internal linguists or resources to build all of these.

    In 2014, the company launched the Duolingo Incubator, a program that let volunteer contributors, native speakers, linguists, and enthusiasts apply to create courses using a tool Duolingo provided. The company would then review and launch the courses built by the community. This expanded the language catalog far beyond what a small internal team could produce, and it brought in communities of native speakers who had a stake in seeing their languages taught well.

    The Incubator also created an interesting dynamic where some languages, like Irish and Welsh, had passionate volunteer contributor bases that produced unusually high-quality courses because the people building them cared deeply about the language’s survival. Duolingo became one of the largest platforms for learning Irish and Welsh, partly because Irish and Welsh speakers were motivated to build excellent courses.

    At the same time, Duolingo was running massive amounts of A/B testing to improve the lessons that already existed. The company treated its user data the way a tech company should: as a signal about what was actually working versus what they assumed was working. They would test different ways of presenting new vocabulary, different frequencies for reviewing older material, different formats for exercises. The product improved continuously based on what the data showed rather than what linguists assumed was the right pedagogical approach.

    This data infrastructure became a real advantage. Duolingo had more data on how people learn languages in an app than any other organization in the world, and they were using it.

    The Green Owl and Its Reputation for Harassment

    Duo, the green owl that is Duolingo’s mascot, has a complicated public image.

    The character sends push notifications reminding users to do their daily lesson. Initially these were polite reminders. Over time, whether by design or by the emergent behavior of Duolingo’s marketing team, the notifications became more aggressive. Memes spread of Duo looking menacing. Jokes circulated that the owl would show up at your house if you missed a lesson. Duolingo’s marketing team noticed this cultural moment and leaned into it, putting out content that played up the owl’s passive-aggressiveness.

    The result was something unusual: an educational app that became a genuine cultural presence. Users made fan art of Duo as a threat. TikTok videos racked up millions of views showing Duo appearing ominously in everyday situations. Duolingo’s social media team adopted an “unhinged” voice that matched the meme, posting content that was deliberately weird and self-aware.

    Von Ahn has described this as Duolingo doing for marketing what it did for product: running experiments, noticing what worked, and doubling down. The Duo character’s viral reputation was not fully planned. It was noticed and then amplified. By 2024, Duolingo’s YouTube Shorts and Instagram Reels views grew over 430% and 450% year over yearrespectively, and AdAge named Duolingo its Marketer of the Year. The owl had become genuinely famous.

    The English Test, and Selling to People Who Actually Had to Learn

    One underappreciated part of Duolingo’s business is the Duolingo English Test.

    The standard English proficiency exam for university admissions is the TOEFL. It costs around $250, takes about three hours, and has to be taken at a certified testing center, which can require travel. For someone in Guatemala, or in a rural part of India, or anywhere that doesn’t have convenient access to a testing center, this is a significant logistical and financial burden. Von Ahn experienced this himself: he had to fly from Guatemala to El Salvador to take his English proficiency exam when applying to American universities.

    Duolingo’s version of the test costs $49, takes 45 minutes, and can be taken from home. By 2021, over 3,000 institutions worldwide, including Duke, UCLA, Columbia, Dartmouth, NYU, and Yale, accepted the Duolingo test in their admissions process. The test generates around 10% of Duolingo’s total revenue and addresses a genuinely different population than the app’s casual learners: people who need to prove English proficiency to get into a university, get a visa, or qualify for a job.

    The Duolingo English Test is not a gamified experience. There are no streaks or points. It is a real standardized test that competes directly with TOEFL and IELTS on price, convenience, and increasingly on acceptance. It represents the other side of what von Ahn built Duolingo to do: not just make language learning accessible, but make the credentialing around language learning accessible too.

    Going Public and Where the Numbers Landed

    Duolingo went public on the Nasdaq on June 28, 2021, under the ticker DUOL, at a valuation of $3.7 billion. By the end of the first trading day, the market cap was sitting around $5 billion.

    At the time of the IPO, the app had around 500 million registered users and roughly 40 million monthly active users. Revenue was $161 million in 2020, growing fast. The subscriber penetration rate, the percentage of monthly active users paying for a subscription, was just above 5%.

    What happened over the next three years was that all of those numbers moved in the right direction at the same time, which doesn’t always happen. Daily active users went from around 8 million at the 2021 IPO to 40.5 million by the end of 2024, a 51% increase in a single year. Monthly active users hit 116.7 million. Paid subscribers reached 9.5 million, up 43% year over year. Subscriber penetration climbed from 5% to around 8.5%.

    Revenue reached approximately $748 million in 2024. Operating margins went from deeply negative to positive: the company posted operating margins of around 8.4% in 2024 after years of losses. The free cash flow margin in Q4 2024 was 42%.

    Duolingo launched Duolingo Max in 2023, a higher-priced tier built around GPT-4 that offered features like Explain My Answer, where users could ask why their answer was wrong and get a detailed explanation, and Roleplay, where users practice conversation with AI characters. Max is priced at around $168 per year versus $80 per year for the basic Super Duolingo tier. By late 2024, Max was in 5 courses across 27 countries and was described by von Ahn as exceeding expectations.

    The AI push extended beyond subscription features. In 2024, Duolingo published 7,500 content units using AI-assisted creation tools, up from 425 in 2021. The company was using AI to write exercises, create audio, and generate practice content at a scale that would have been impossible with only human content creators.

    What von Ahn Still Filters Every Decision Through

    In interviews over the years, von Ahn has returned to the same framing when asked how Duolingo decides what to build.

    He asks whether the feature would help someone in Guatemala learn English.

    It is not a complicated filter, but it has held for fifteen years. When the company debates adding a feature that only works well on expensive hardware, that filter pushes back. When someone suggests a paywall for core learning features, the filter rejects it. When the product team looks at which languages to prioritize, the filter points toward the ones that create the most economic opportunity for learners in developing countries, which is why English-learning courses get disproportionate resources even though Duolingo users learning English are not the company’s most profitable customers.

    By early 2025, Duolingo had 40.5 million daily active users, 116.7 million monthly active users, and 9.5 million paid subscribers. Nearly 2 billion people worldwide are estimated to be learning a language at any given time. Von Ahn’s stated position is that Duolingo has barely scratched the surface of that market.

    The company started because a Guatemalan kid noticed that English courses were too expensive for most people in his country. The kid grew up, invented CAPTCHA, sold reCAPTCHA to Google, became a MacArthur Fellow, and then spent the next fifteen years building the thing he thought the world actually needed. As of 2025 it has been downloaded more than any other education app in history and generates nearly $750 million a year while keeping its core product free.

  • The Figma Success Story: How a College Dropout Spent Four Years Building in Secret and Changed How the World Designs Everything

    Dylan Field was five years old when he got his first acting role, and the lesson he took from it stayed with him for decades.

    The role came because he had two specific skills: he could sit quietly, and he could read. He was successful enough to get agents in the Bay Area and Los Angeles, booking TV commercials and theater work well into elementary school. One of his credits was a TV ad for eToys, the online toy retailer that became a symbol of the dot-com bust. Another was for Windows XP. He eventually stopped acting around puberty, but the thing he had understood about performance, that the best creative work happens when people are completely responsive to each other in real time, would come back around in his late twenties as the founding insight of a $56 billion company.

    Figma is not primarily a story about design software. It is a story about what happens when you start from a premise that your entire industry has quietly agreed is impossible, spend four years building in secret, and turn out to be right.

    Brown University, WebGL, and the TA Who Changed Everything

    Field grew up in Penngrove, California, a small town in Sonoma County. His father was a respiratory therapist, his mother a resource specialist teacher. Not a tech family by background. Field found his way into web development during high school, started building websites for friends, interned at O’Reilly Media, and showed up at Brown University as a computer science student who was still genuinely undecided about what he wanted to do. He took political science classes, thought about law school, briefly considered going back to acting.

    What settled him was meeting Evan Wallace.

    Wallace was a year ahead of Field at Brown, a serious CS student who had already interned at Pixar and Microsoft, and was working as a teaching assistant in the department. He had an unusual area of focus for 2012: browser graphics. Specifically, he had been experimenting with WebGL, a relatively new JavaScript API that allowed browsers to render high-performance interactive graphics using the GPU. One of Wallace’s demos, a rendering of water physics in a browser window, circulated enough that WIRED called it one of the more impressive WebGL demos they had seen.

    Field saw the demo and immediately understood the implication. If you could render GPU-level graphics in a browser, you could build professional creative software that ran in a browser. And if it ran in a browser, the file-sharing and collaboration problems that plagued every existing design tool simply dissolved: anyone with a link could be in the same canvas at the same time, without downloading anything, without versioning conflicts, without emailing files back and forth.

    This was 2012. Sketch, the dominant design tool at the time, was Mac-only desktop software. Adobe‘s Creative Cloud was server-assisted desktop software. The assumption across the entire industry was that design tools required local compute. The idea of doing professional design work in a browser was not taken seriously.

    Field had an upcoming internship at Flipboard. He also had an application in to the Thiel Fellowship, a program created by Peter Thiel that provided $100,000 to young entrepreneurs willing to drop out of college and build something. He pitched the fellowship on a drone software company, which was not what he ended up building, but the application got him the money. He was selected in May 2012, dropped out of Brown, and moved to San Francisco. Wallace finished his degree that spring and followed.

    They had $100,000, no clear product idea, and Wallace’s WebGL demos. They started building.

    Four Years of Building What Everyone Said Was Impossible

    The early period at Figma was not a confident march toward a clear vision. It was an extended experimental phase that frustrated investors, caused early employees to quit, and nearly killed the company before it launched anything publicly.

    Field and Wallace tried several ideas. Drone software. A meme generator. 3D content generation tools. Photo editing with computational features like Poisson blending and image segmentation. None of it stuck.

    When they pitched investors in 2013 and 2014, the response was consistent. Field has described the feedback from those early meetings as investors telling him they didn’t think the team knew what it was building yet. The most direct version came from John Lilly, then a partner at Greylock. Lilly passed on the seed round, telling Field: “I don’t think you know what you’re doing yet.” That line apparently hit hard enough that Field sought out more mentorship and used it as a forcing function to sharpen the product vision.

    Eventually, the team landed on something they kept returning to: interface design tools. The problem was specific and well understood. Designers at technology companies were working in tools like Sketch that were desktop-only, single-user by default, and produced files that had to be shared manually. The version control problem was real. You would spend hours working on a design, then discover you had been editing a version that someone else had superseded two days earlier. Presenting designs to engineers or product managers meant exporting assets and sending them around, a workflow that turned every stakeholder review into a document management exercise.

    Figma’s answer was to build design software the way Google had built Docs: as a live, multiplayer workspace where everyone who needed to be in the file could be in the file simultaneously. Not just designers. Product managers, engineers, marketers, executives. The link was the distribution mechanism. You shared a URL. People clicked it. They were in.

    To get there, Field and Wallace had to solve hard technical problems. Rendering complex vector graphics in a browser with the performance that professional design work required was not a solved problem in 2013. They built much of the rendering engine from scratch, using WebGL and later WebAssembly for performance-critical code.

    They raised a $3.8 million seed round from Index Ventures in 2013. Index partner Danny Rimer had heard about Field through LinkedIn’s then-CEO Jeff Weiner, who described the intern who wanted to start his own company and thought someone should talk to him. Field came in to the Index SF office to pitch, and Rimer wrote the check based on the vision and Field’s obvious drive more than any specific product that existed. Rimer has said he knew from talking to Field that he was someone who would pour everything into bringing it to life.

    The company ran quietly for two years after that. A private beta launched in December 2015. John Lilly, who had previously passed, led a $14 million round in December 2015. The public version launched in September 2016. The first paid product came in 2017.

    The timeline is worth sitting with: four years between founding and public launch. In an industry that preaches ship-early and iterate-fast, Figma spent four years in stealth, building an engine that could do what they had promised.

    The Decision to Stay Free and the Multiplayer Bet

    When Figma launched publicly in 2016, it was free.

    This was not an accident and not a temporary tactic. Field had internalized feedback from an early enterprise customer who told him that they couldn’t scale Figma internally because no one believed the company would still be around in a year. The feedback stung but clarified something: before you can charge, you need users who are embedded in your product. You need advocates inside organizations who have used it enough to fight for budget.

    Figma gave the product away for free and let designers bring it into their organizations organically. A designer at a startup would start using Figma because it was free and easy. They would share a link with a product manager. The PM would click the link, open the design in their browser without installing anything, and immediately understand why this was better. The PM would share it with a developer. The developer would see the developer handoff features and switch from their old workflow.

    The adoption pattern was bottom-up and viral by design. Every link shared to a non-designer was both a product demo and a distribution event. The person receiving the link did not need Figma installed. They did not need an account in most cases. They just needed to click and they were in. Compare this to sharing a Sketch file: you needed Sketch installed, you needed to be on a Mac, and you were looking at a static snapshot rather than the live document.

    Index Ventures has noted that a board meeting eventually pushed Field to start charging. An enterprise customer had given him the same signal: free was preventing expansion because it eliminated credibility. Field took the feedback seriously and the team built a pricing model that converted the free base into a sustainable business. Revenue grew quickly once the pricing was in place because the product was already deeply embedded in organizations through the free period.

    By April 2020, Figma was valued at more than $2 billion. By the end of May 2021, that number had more than quadrupled to $10 billion.

    The Multiplayer Insight Was About More Than Design

    The thing that is easy to miss about Figma’s success is that the real product was not design features. The auto-layout tools, the component libraries, the prototyping capabilities were excellent, but they were not the moat.

    The moat was the decision to treat design as a team activity rather than a solo activity from the very beginning.

    Sketch was for designers. Figma was for product teams. When you built Figma into your workflow, it was not just the design team using it. It was engineers referencing specs directly from the Figma file. It was product managers running reviews inside the live document. It was executives clicking a link in Slack to see the latest version of the product. Every stakeholder who had ever opened a Figma file was a reason for the design team to stay on Figma rather than switch.

    FigJam, launched in April 2021 as a digital whiteboarding tool, extended this logic further. If your company was using Figma for design and FigJam for brainstorming, the organizational surface area of Figma grew beyond the design team entirely. Executives who had never opened a Sketch file were using FigJam for offsites and planning sessions.

    The link-based collaboration model also changed how design moved through the product development process. Instead of design reviews happening through presentations or document handoffs, they happened inside the design file itself. Stakeholder comments lived on the canvas. Designer responses lived on the canvas. The entire history of a design decision was in one place, not distributed across email threads and Slack channels.

    By 2022, the design community’s adoption of Figma had become comprehensive enough that when Adobe announced it was acquiring the company, designers publicly worried about what Adobe would do to the product. That reaction was the clearest possible proof of how deeply embedded Figma had become: the community cared about its fate the way they would care about a utility.

    Adobe’s $20 Billion Acquisition and the Deal That Changed Everything

    On September 15, 2022, Adobe announced it intended to acquire Figma for approximately $20 billion in cash and stock, its largest acquisition to date. Field would remain as CEO. Adobe described it as a chance to reimagine the future of creativity and productivity.

    Adobe’s stock fell 17% the day of the announcement.

    The market’s reaction was a better read on the deal than most of the press coverage. Investors were not confused about why Adobe was buying Figma. Adobe’s own design software, XD, had been losing market share to Figma for years. Adobe was buying the competitor that had been eating its lunch. The regulators who eventually reviewed the deal used the same framework: Britain’s Competition and Markets Authority found that the acquisition would eliminate competition in product design, image editing, and illustration software. The European Commission began its own review in February 2023. The US Department of Justice opened an investigation in November 2022.

    Adobe had described the deal as a way to acquire a complementary product. Regulators read it as a dominant player acquiring its fastest-growing competitor before it could scale further.

    On December 18, 2023, Figma and Adobe announced they were walking away. Adobe cited no clear path to regulatory approval in Europe and the UK. As part of the original agreement, Adobe paid Figma a $1 billion reverse breakup fee.

    Figma emerged from fifteen months of acquisition limbo having received $1 billion, still independent, and with more public awareness than at any point in its history. Adobe, which had quietly discontinued active development of XD when the acquisition was announced, confirmed in early 2024 that it would not be reviving it.

    The regulatory block did something else: it forced the market to think about what Figma was worth without Adobe as the reference point. The answer turned out to be considerably more.

    The IPO and $56 Billion on the First Day

    Field had been direct about the path after Adobe. In an interview with The Verge, he said: “There are two paths that venture-funded startups go down. You either get acquired or you go public. And we explored thoroughly the acquisition route.”

    Figma filed confidential IPO paperwork with the SEC in April 2025. The public S-1 followed in late July. On July 31, 2025, Figma listed on the New York Stock Exchange under the ticker FIG, priced at $33 per share.

    The stock opened at $85 and closed at $115.50, a roughly 250% gain on its first day of trading. The market cap based on outstanding shares hit approximately $56 billion at close, a fully diluted valuation north of $65 billion.

    That number was more than double what Adobe had agreed to pay fourteen months earlier.

    Field had been a 20-year-old dropout when he started Figma, a former child actor who had spent three years at college before a $100,000 fellowship pulled him out. By Forbes’ estimate in August 2025, his net worth had reached $6.6 billion. He owned roughly 9% of the company he had spent thirteen years building.

    Figma reported $1.056 billion in annual revenue in 2025. A company that had spent four years building in stealth before anyone used it had crossed a billion dollars in revenue within a few years of finding product-market fit.

    What the Figma Story Is Really About

    The Figma success story has a specific lesson that gets buried under the acquisition drama and the IPO numbers.

    Dylan Field and Evan Wallace spent four years building something the industry said was impossible. They did not ship fast and iterate. They did not launch an MVP and see what happened. They spent four years getting the technical foundation right because they knew that if the rendering performance was bad, if the collaboration was laggy, if the browser-based experience felt like a compromise compared to desktop software, the whole premise was undermined. The industry would look at their half-baked version, confirm its assumption that design tools belonged on the desktop, and move on.

    They waited until it was good enough that it wasn’t a compromise. Then they gave it away for free.

    The link-based distribution model was not a growth hack. It was the entire thesis about what design should be. If design is a collaborative activity involving engineers, product managers, and stakeholders alongside designers, then the tool that enables it needs to work for all of them without any friction. A URL has zero friction. Anyone can click it. No installation, no account required, no compatibility check.

    The Adobe story validated the thesis from the outside. When the largest company in creative software tried to buy Figma for $20 billion and regulators blocked it on the grounds that Figma was a genuine competitor rather than a complementary product, they were confirming what Figma’s user base had already established: this was not a niche design tool for a subset of the Adobe market. It was the design category itself.

    Field’s first acting role came because he could sit quietly and read. The adult version of that skill was the ability to spend four years building in stealth when everyone around him was shipping, iterating, and pivoting. The patience turned out to be the product.

  • The Atlassian Success Story: Two Graduates, a $10,000 Credit Card, and the Company That Proved You Could Sell Software Without a Sales Team

    In 2001, Mike Cannon-Brookes sent an email to his classmates at the University of New South Wales asking if any of them wanted to start a tech company after graduation. One person replied. Scott Farquhar wrote back.

    That was the entire founding story, more or less. Two students at a Sydney university who had separately decided they did not want corporate jobs, responding to each other’s interest in building something instead. Their stated ambition at the time was not to build a billion-dollar company or change the enterprise software market. It was to match the starting salary of a corporate graduate job, which in Australia in 2002 was around $48,500, without having to work for someone else.

    What they ended up building over the next two decades was one of the largest enterprise software companies in the world. Atlassian hit $4.1 billion in revenue in fiscal year 2024, serves over 300,000 customers including most of the Fortune 500, and listed on the Nasdaq at a $4.37 billion market cap in 2015, making Cannon-Brookes and Farquhar Australia’s first technology startup billionaires. The company did all of this, for the first several years, without a traditional sales team. They didn’t have a pitch deck. They barely had a credit card.

    Actually, the credit card was the only funding they had. $10,000 charged to a personal card. That was the capital Atlassian started with.

    Supporting Other Companies and Hating the Bug Tracking Software

    The first version of Atlassian was not Jira and it was not Confluence. It was a services business: Cannon-Brookes and Farquhar were providing customer support to other companies. They were taking calls at all hours, tracking issues and requests for clients who needed help managing their customer service operations.

    The software they used to track their own work was Bugzilla, an open source bug tracking tool developed by Mozilla. Bugzilla was functional but not easy to use, and for two people running a small operation and trying to keep up with client issues across multiple accounts, it was not meeting their needs. They kept bumping into its limitations.

    So they built their own.

    The tool they built was named Jira, a reference to Gojira, the Japanese name for the 1954 Godzilla film. The naming had no particular meaning; it was a play on Gojira because the founders thought it sounded memorable. Jira 1.0 launched in 2002 as an issue and project tracking tool built primarily for software teams. It was faster than Bugzilla, more configurable, and had a cleaner interface.

    After building it, they made a decision that reoriented the entire company: they realized they were better off selling Jira than providing customer support services. The product was more scalable than a services business, the margins were better, and it solved a problem that was genuinely widespread among software teams. They stopped answering other companies’ support calls and started selling bug tracking software.

    The pricing decision mattered as much as the product decision. Atlassian set Jira’s price at $800 per license for small teams. At a time when enterprise software routinely sold for tens of thousands of dollars per seat through lengthy sales processes, $800 was a price that any software team could justify buying without a formal procurement process. You could put it on a company credit card. You didn’t need to get the VP of Engineering to sign off. You didn’t need to sit through a demo from a salesperson. You just went to the website and bought it.

    Their goal in the early days was to sell one license per week. If they could do that, they could cover their costs and grow.

    They did it without a single salesperson. Every customer found Atlassian through the website, evaluated the product themselves, and paid online. This was the model that Farquhar would later describe, in his farewell letter when stepping down as co-CEO in 2024, as the start of what is now called product-led growth. They didn’t have a name for it in 2002. They just didn’t have money for salespeople and built a product good enough that people would pay for it without being sold to.

    The American Airlines Fax

    The story that best illustrates what was working became part of Atlassian’s internal mythology.

    One morning in 2003, Cannon-Brookes and Farquhar came into their small Sydney office and found an order from American Airlines on the fax machine. A large US airline had seen Jira on their website and bought a license without speaking to anyone at the company. Nobody at Atlassian had called American Airlines. Nobody had sent them a proposal. The sale was entirely inbound.

    They looked at each other and said, roughly: did you talk to them? No, did you? No. So American Airlines just found us on the internet and bought software from us?

    It confirmed something important. The target market for Jira was overwhelmingly in the United States, which was a problem and an opportunity simultaneously. They were a two-person operation in Sydney trying to sell to software teams in San Francisco and New York. Flying there to demo software was not viable. Building a US sales team was not affordable. But if American Airlines could find them through a search engine and buy without any human contact, so could other companies.

    They invested heavily in the self-service purchase experience instead of salespeople. Clear product documentation. An easy trial process. Transparent pricing on the website with no “contact us for pricing” obfuscation. A support system that let customers get help without picking up the phone. The approach was unusual enough that it attracted comment. Most B2B software companies of the era assumed you needed a sales force to close deals above a certain size. Atlassian was proving otherwise, one fax at a time.

    Confluence, the New York Office That Didn’t Last, and ShipIt

    In 2004, Atlassian launched Confluence, a wiki-style team collaboration platform. Where Jira was for tracking work, issues, and bugs, Confluence was for documentation, knowledge sharing, and team communication in written form. A software team might use Jira to track what they were building and Confluence to document how it worked. The two products were complementary in a way that made each more valuable when used together.

    Confluence followed the same pricing model as Jira: low cost, available on the website, no sales team required. The customer base grew across both products as word spread through developer communities and technology teams.

    With most customers in the US and virtually none in Australia, the founders decided they needed a physical American presence. They opened a small office in New York in 2005. Within a year they had realized it was a mistake. The office was too expensive for what it was producing, and the team was stretched thin maintaining operations across two locations separated by fourteen time zones. They closed the New York office and acknowledged it had been an overextension.

    They’ve told this story publicly over the years as an example of making a mistake, recognizing it quickly, and not letting sunk cost push them to compound it. The lesson they took was that making a hard call sooner was better than delaying it. They eventually did establish a US presence, this time in San Francisco, which worked better.

    In 2005, Atlassian started ShipIt, a quarterly hackathon where employees spent 24 hours building whatever they wanted with whoever they wanted, with no constraints on the direction. The results were presented at the end. The format was designed to create dedicated space for experimentation outside the normal product roadmap.

    Some of Atlassian’s most significant products came out of ShipIt sessions. Jira Service Management, which became Atlassian’s fastest-growing product for several years running, started as a ShipIt project. The hackathon format became one of the more copied elements of Atlassian’s culture as the company became better known.

    Eight Years Without Outside Money

    Atlassian ran for eight years without taking money from outside investors.

    The $10,000 credit card debt from 2002 was gone within the first year of selling Jira. After that, the company was funded by its own revenue. They hired slowly. They grew by adding customers who found them online, upgrading to bigger licenses, and spreading Jira through their own organizations. A development team at one company would adopt Jira, that company would grow, the Jira deployment would expand, and Atlassian’s revenue from that account would grow with it.

    By 2010, the company had passed $100 million in cumulative revenue. The revenue model was generating enough cash to fund the business without outside capital, but the founders decided it was time to bring in a major investor, not because they needed the money but because they wanted access to advice and networks for the next phase of scaling.

    In July 2010, Accel Partners invested $60 million in Atlassian. Notably, most of that investment was a secondary transaction: Accel bought shares from the founders rather than putting fresh capital into the company. The founders took some money off the table after eight years of building. The investment valued Atlassian at around $400 million.

    By the time Atlassian filed for its IPO in 2015, annual revenue was approximately $320 million and growing. The company had reached $100 million in annual revenue by around 2012, growing from $255,000 in 2007. The trajectory was consistent and built almost entirely on the back of a product that sold itself.

    The IPO and “Australia’s First Tech Startup Billionaires”

    Atlassian listed on the Nasdaq on December 10, 2015, under the ticker TEAM. The market capitalization at IPO was $4.37 billion, making it one of the larger software IPOs in Australian history and one of the more notable of the year globally. The New York Times, in a piece that Atlassian employees remember with some amusement, called the company “very boring software” because of its focus on bug tracking and project management rather than consumer-facing applications.

    The boring software had made Cannon-Brookes and Farquhar billionaires. They were, by wide acknowledgment, Australia’s first tech startup billionaires: people who had built a technology company from zero to billion-dollar valuation rather than inheriting wealth or making money through real estate or mining, which had historically been where Australian fortunes were made.

    At IPO, the two founders owned approximately 30% each of the company they had started. The IPO had no VC-driven liquidity event structure forcing a quick sale or complex ownership cleanup. They had taken one outside round from Accel in 2010 and had kept their ownership largely intact through to a public listing that gave investors access to a company with thirteen years of operating history, consistent revenue growth, and a product that was genuinely embedded in the workflows of software teams around the world.

    The IPO was the moment Atlassian got properly noticed outside of the developer and enterprise software communities it had served for over a decade. The story of two guys with a credit card and no sales team building a multi-billion dollar software company from Sydney attracted attention. The boring software was suddenly interesting.

    Trello, HipChat, and the One Bet They Got Wrong

    After the IPO, Atlassian had the currency to make acquisitions at scale. The first significant one was Trello, bought in January 2017 for $425 million.

    Trello was a visual project management tool built around boards, lists, and cards. Where Jira was powerful and complex, Trello was simple and visual, aimed at teams doing general project tracking rather than software development. It had nearly 19 million registered users at acquisition and was growing fast. Atlassian’s logic was that Trello served a different user than Jira, primarily business teams in marketing, HR, and operations rather than software engineers, and that bringing Trello into the portfolio extended Atlassian’s reach beyond its technical core.

    The acquisition worked. Trello retained its product identity within Atlassian, kept growing, and opened the platform to users who would never have been Jira customers.

    The bet that didn’t work was the attempt to compete in enterprise chat.

    Atlassian had acquired HipChat in 2012, a team messaging tool that was popular among developers. When Slack emerged as the dominant player in the category after 2013, Atlassian tried to compete with a rebuilt product called Stride. In 2018, after two years of trying, Atlassian admitted it wasn’t working. They sold the intellectual property for both HipChat and Stride to Slack in exchange for a small equity stake in Slack and got out of the chat business entirely. The decision was pragmatic and expensive in terms of the resources spent, but the alternative of continuing to invest in a losing position would have been more expensive. They took the Slack stake, shut down the products, and moved on.

    The HipChat exit illustrated something about how Atlassian made strategic calls. They were willing to try things that didn’t work and willing to stop doing them quickly when the evidence was clear. The New York office. HipChat. Getting out when the data said to get out was a consistent behavior across both good markets and bad.

    The No-Sales-Team Model and Who It Actually Worked For

    Atlassian’s approach to selling software became more interesting after the IPO precisely because the company started to make more money and people studied how it worked.

    The model was simple in concept. Build a product that solves a real problem. Price it accessibly. Make it easy to try and easy to buy online. Let the product spread within organizations as people who like it tell colleagues or switch jobs and bring it with them. Use a marketplace of third-party apps and integrations to extend the product’s functionality and lock customers in through integration depth.

    The customers Atlassian described themselves as targeting were the “Fortune 500,000”: not just the largest companies in the world but any company that needed software for teams to track work. By keeping prices accessible and the buying process frictionless, they could land customers from a startup with five engineers to a multinational with 100,000 employees. The multinational might take years to become a large account, but they would often get there through organic expansion rather than an enterprise sales relationship.

    By FY2017, Atlassian had over 89,000 customers. By FY2024, that number had grown to over 300,000. The revenue per customer had grown steadily as companies bought more products, added more seats, and moved to cloud subscriptions that included ongoing support and upgrades.

    The Atlassian Marketplace, where third-party developers built and sold apps and integrations on top of Jira and Confluence, had passed $500 million in cumulative sales by 2021. More than 5,700 apps in the marketplace meant customers could customize and extend the platform without Atlassian having to build every feature themselves. Customers who had integrated their Jira instance with dozens of third-party tools were not going to switch to a competitor easily; the switching cost was the sum of every integration they would have to rebuild.

    The Cloud Transition and Loom

    The most significant operational challenge of Atlassian’s post-IPO decade was a deliberate and difficult transition: moving the business from selling perpetual licenses for server-installed software to selling cloud subscriptions.

    For most of its history, a company buying Jira would download it, install it on their own servers, and pay a one-time license fee plus annual maintenance. Atlassian called this the Server product. In 2020, the company announced it would stop selling new Server licenses in February 2021 and end support for existing Server installations in February 2024. Every customer needed to move to either Cloud, the hosted SaaS version, or Data Center, a self-managed product for organizations that needed to run their own infrastructure.

    Forcing customers to migrate is operationally painful. Some organizations had run Jira Server for ten years, had deeply customized installations, and resisted moving. Atlassian built migration tools, offered transition pricing, and extended timelines where necessary, but the shift involved years of friction with a significant portion of the customer base.

    The long-term logic was sound. Cloud subscriptions generate higher margins and more predictable revenue than perpetual licenses. A customer on a cloud subscription is more likely to expand their usage and buy additional products than a customer on a server installation who only interacts with Atlassian at renewal time. By FY2024, cloud revenue represented approximately 70% of Atlassian’s total revenue and was growing at around 30% year over year.

    In October 2023, Atlassian acquired Loom for $975 million. Loom was a video messaging tool that let people record short videos of their screen and face instead of sending a long email or scheduling a meeting. For remote and distributed teams, it was a way to communicate complex information asynchronously. Atlassian integrated Loom with Jira so that video recordings could be attached to issues, and built Loom AI features that could turn a video transcript into a Jira task automatically.

    The Loom acquisition was the company’s largest to date and reflected a thesis about remote work: that asynchronous communication tools would become as important to distributed teams as project management and documentation tools. Atlassian had been operating as a fully distributed company itself since announcing its “Team Anywhere” policy in 2020.

    Farquhar Steps Down and What $4 Billion Looks Like

    In April 2024, Scott Farquhar announced he would step down as co-CEO at the end of August, leaving Mike Cannon-Brookes as the sole CEO. Farquhar had been co-CEO alongside Cannon-Brookes for twenty-two years, since the day they founded the company. The co-CEO structure was unusual in the technology industry and even more unusual for lasting as long as it did.

    Farquhar’s farewell letter, filed publicly as an SEC exhibit, described the company’s history with candor about what they had gotten right and what had been hard. He noted that Atlassian had “started what is now known as product-led growth by selling business software online with no salespeople” before the term existed, and that twenty-three years later the company was operating as one of the largest remote-first enterprises in the world.

    He also wrote something that captured the absurdity of what the company had become: rockets don’t launch into orbit without Atlassian’s software. NASA’s Jet Propulsion Laboratory uses Jira. The fax from American Airlines in 2003 had scaled, somewhat improbably, to teams managing space missions.

    In FY2024, Atlassian reported approximately $4.1 billion in revenue, serving over 300,000 customers across more than 190 countries. The market cap, which had peaked above $100 billion during the 2021 software boom and fallen with the broader market, was in the range of $40-50 billion in 2025. The founders, who each owned roughly 20-30% of the company they had started with a credit card, remained among the wealthiest people in Australia.

    In March 2026, Atlassian announced it would lay off around 10% of its workforce as part of a pivot toward AI and enterprise sales, a signal that even the company that had built its identity on not having a traditional sales force was beginning to reconsider what the next phase of growth required.

    The product-led model that Cannon-Brookes and Farquhar invented by necessity in 2002, because they couldn’t afford salespeople and Australian venture capital didn’t really exist yet, had become a widely imitated approach to building software companies. The name had been given to it retrospectively; the practice had been invented in a small Sydney office by two people trying to match a graduate starting salary without working for anyone else.