We were pushing users toward it, optimizing the shit out of it, growing at lightspeed.

Then AI came along and changed everything.

Changed how users experience value. Changed what that first moment of “getting it” actually feels like.

And most AI startups I see (or those that offer AI features) haven’t caught up yet.

They’re still playing the old game. Making one mistake that prevents users from ever experiencing the value they built.

So it’s time to reframe it.

What was the AHA moment back then?

As said in the beginning, the AHA moment was defined as the pivotal moment when a new user first recognizes the core value of your product and understands why they need it.

I still remember the whiteboard sessions we had. “What is our AHA moment?” “How do we get users there as fast as possible?” good old times….

And back then, it was worth obsessing over. Because once we cracked it, we felt the difference in conversions immediately.

To figure it out, we studied the same well-known examples:

• Facebook’s AHA moment: Users who added at least 7 friends within the first 10 days developed significantly stronger retention.

• Slack’s AHA moment: Teams that hit 2,000 messages sent were highly likely to become long-term paying customers.

• Zoom’s AHA moment: Value hit when someone ran a meeting without any technical friction, straight from the browser.

Dozens of products followed the same pattern:

Find the moment → optimize toward it → watch conversions go up.

It worked. Until it didn’t.

The AHA moment in the AI age

At its core, the definition hasn’t changed. It’s still the moment a user experiences value for the first time.

But what that moment feels like and how to get someone there is completely different with AI.

Because with AI, it’s not an AHA moment anymore. It’s more like a magic moment.

• SaaS AHA moment: “I can finally do this work efficiently.”

• AI magic moment: “I don’t have to do this work at all.”

That’s a completely different emotional reaction.

And products like Lovable or Perplexity have already trained us to expect it. One prompt, something that would have taken days appears in a matter of seconds.

So, going back to the whiteboard, as a business offering an AI tool (or features), that’s what I would optimize for.

Speed

→ Classical SaaS took time. Account creation, onboarding, setup. Users expected a ramp before they got value.

→ With AI that’s gone. It has to be instant. One input field, one prompt, magic. Any friction before that moment and we’ve already lost them.

Effort

→ SaaS required manual work to get value out. Users had to invest time before things clicked.

→ AI has to be the opposite. Attention spans are at an all-time low. One prompt, one click, one result. That’s the expectation you’re up against.

The feeling

→ The SaaS AHA moment felt like relief: Something painful just got simpler.

→ The AI magic moment has to hit differently. We want to create the “holy cow, how did that just work” reaction. That gut-level surprise is what should actually be optimized for.

Quality

This is where it gets tricky.

→ SaaS worked or it didn’t. Users got the value or they didn’t.

→ With AI, the output can go sideways. A hallucination doesn’t just fail to impress, it actively destroys the magic. One bad result and the WTF moment replaces the magic moment. Output quality is one of the most important things to optimize.

AND there is one other mistake I see many AI solutions make.

The mistake most AI startups are making

Whether it’s an AI solution or a tool that offers AI features.

Most businesses gate them behind a paywall.

I get the logic. AI usage costs money. But hiding it behind a paywall kills any chance someone has of experiencing the magic moment you just spent everything building toward.

Think about it. Users are primed by the best AI products out there to expect instant value. Their attention span for anything less is basically zero.

Now you put a paywall in front of the one thing that would have made them stay.

Therefore, we should start treating AI usage as a marketing cost. Because that’s exactly what it is. If a product genuinely creates value, getting someone to feel that magic moment once is worth every cent.

Last words

The AHA moment became a magic moment. And the way we should optimize for it changed completely.

Speed to value. Minimal effort. That gut-punch of “I can’t believe that just worked.” Output quality that holds up the magic instead of destroying it.

And above everything else: don’t gate it. The market leaders have already trained our users to expect value immediately.

Don’t make them wait for something they can get somewhere else right now.

AJ

PS: If you enjoyed this, please tap the like button below. Thank you! 💛

Probably yes, because budget is limited, pressure is on and you want to finally get your acquisition running.

I was in the same spot a few years ago working at a small startup. We tried ads, outbound, content. Nothing moved the needle the way we needed it to.

Then I looked at the hyper-growth companies. The ones going from 0 to 100M ARR in record time.

And there’s one mechanic that works for almost any business (yes, also for solo builders) and it can create a constant stream of new users. For free.

Here’s what they’re doing.

Building referral loops

Referral loops are how today’s top companies generate customers on autopilot.

The core principle is that one customer brings 10 more and there are just some simple mechanics you can implement for your business.

To make it clear, let’s have a look at some examples.

Lovable’s Referral Loop

Lovable’s referral loop looks like this:

A new user is using the tool, he builds something, shares what he built, others see it, go to Lovable’s website and start building.

To fuel this loop Lovable has some simple mechanics in place:

Once a user builds an app he is greeted with a pop-up and the call to action to share his app.

In the second step: User shares his app on social media or his app appears in Lovable’s app library.

Once someone clicks on his app, there is a button in the bottom right corner.

One click on it and you land on Lovable’s website where you can directly start building.

Boom. Loop closed, users generated on autopilot.

But this doesn’t only work for end users.

Clay uses a completely different loop, targeting partners but at least with the same effects (if not more effective).

Clay’s Referral Loop

Clay is another rapid-growth company reaching $100M ARR in 2025.

And their loop is one major pillar to reach this revenue milestone.

Clay’s loop addresses agencies and works like this:

1. Agencies use Clay to run cold outreach campaigns with extreme personalization for their clients.

2. The clients are so impressed by the results (high response rates) that they ask: “How do you do that?”

3. The agency shows them Clay. The client realizes they need to buy the software themselves to maintain this standard in their team.

4. People are talking about it online and sharing it with the community, which attracts new agencies.

This again creates this permanent stream of new customers.

There are even agencies that build their entire business model around Clay. Those are called Clagencies.

How to build one yourself

So coming to the key question. How do you build a loop yourself?

There are two main questions you should ask yourself upfront:

• Does my product have the nature that people are willing to share?

• Or can I enable others (e.g. partners) to share my product?

If you answer these questions you probably have an idea in which direction you can build your loop.

Let’s say as an example we have a social media scheduler as a product. Here clearly people are willing to share but there is probably no way where you can put your brand name in (nobody wants a “posted with XYZ” underneath their post haha).

So we go for partners. Bringing agencies or freelancers to use the product. The loop could look like this:

1. The freelancer plans the posts for their client in our tool.

2. They send the client a “Review-Link” for approval.

3. The client sees the post in the interface of our tool (without login required).

4. When the client later has their own project or the team changes, they remember the tool (”What was that cool approval tool?”) and become a paying user themselves.

Or another example.

Our tool tracks investment activities and since people naturally love to brag on the internet we focus on creating nice sharable dashboards or screenshots.

Here comes the loop into play:

1. People use our tool

2. People share their overview from our app (screenshot or we create a preview link where they can share it directly) on social media

3. Other users see it and are naturally guided to our website

4. New users start using our tool

Loop repeats.

With this simple mechanic you can acquire customers on a budget without spending thousands on ads or spamming outbound mails.

Final Words

When we implemented a basic referral loop in that startup I mentioned, we went from struggling to hit our monthly targets to having users bring in 3-4 new signups each week.

That’s when I realized that the best growth engine isn’t something you buy. It’s something you build into your product from day one - for free.

PS: If you enjoyed this, please tap the like button and leave a comment below. Thank you! 💛

Share AI x Growth

The answer stuck with me. Until then, I always believed that virality happened by coincidence.

But now I’m convinced it doesn’t.

What Virality Means

Before diving into this, we should look at what virality means. When we talk about virality or viral content, most of us probably have this in mind:

You post → you hit a nerve → you go viral → boom, thousands of likes, shares, comments and new followers.

But in my view there is another type of virality.

The one where you make your customers, users, partners, or whoever constantly talk about your product or business. They’re basically doing the work for you. They write articles, mention you in the press, and talk about you on social media. They make you appear constantly in front of your target group.

This type of virality doesn’t necessarily need thousands of likes. Here it’s about the compound effect of many small conversations rather than one big explosion.

And while many are trying to force the first type, the second one is what more companies should aim for.

How to “Go Viral”

So the key question is: how do you achieve this kind of virality?

Lovable’s head of growth explained it like this: You have to give your customers stories they can share.

Think about it.

Lovable does exactly this. With the app, everyone can become a developer. People are building the things they always dreamed about, and what happens then? They start talking about it online. They share their story of how they built something.

This creates a viral story loop, which picks up elements of classical storytelling:

• User experiences the magic moment (in Lovable’s case, that they can create anything they want).

• They become “the hero” in the story as they solve their own problem.

• They share their story online.

• Others see it, use the tool, and talk about it as well.

• Loop starts again

How Can You Create This Viral Loop

So you might think “nice, but I don’t have this kind of solution where I can create this viral loop naturally.”

I got you.

There are different ways to make people talk about you:

• Give them something to visualize → Stripe gives you beautiful UI to show the revenue your business makes. Looking at my feed, I see at least once per day someone talking about how their business makes X revenue, posting a screenshot of Stripe’s visualization.

  • The story Stripe gives users: “I’m now a business owner making real money.”

• Create shareable achievements → Turn user progress into badges of honor:

  • Duolingo’s streak feature and year-end reports get shared constantly. The story they give: “Look, I’m learning another language.”

  • Spotify Wrapped turned listening data into an annual social media event. The story: “I have great music taste.”

  • GitHub’s contribution graphs make developers want to show off their activity. The story: “I’m a productive developer who ships code.”

• Build in social proof → ProductHunt’s “Featured on ProductHunt” badges incentivize people to share their launches.

  • The story ProductHunt gives: “I’m a builder who turned my idea into a real product.”

Ask yourself the question: What is the story I give my customers that they’re willing to share?

Last Words

This kind of virality doesn’t happen by coincidence. It’s engineered. Sometimes not even by marketing but by product teams.

But no matter how, it’s the type of virality you should aim for. Making people constantly talk about you doesn’t only bring new customers all the time but also gives you an edge.

We see more and more AI-generated content, but when people talk about you, it’s real experience. This creates trust and the word-of-mouth awareness you want to have.

AJ

PS: If you enjoyed this, please tap the like button below. Thank you! 💛

In comparison with other hyper-growth companies, it’s the fastest we’ve seen scaling from $1M to $100M so far.

And all this while its north star isn’t revenue. The company is optimizing everything around how many people use Lovable. Like Lovable’s Head of Growth mentioned in Lenny’s Podcast here.

So all the more reason to have a look at its growth playbook and what caused this explosive growth.

Spoiler: it’s not luck, it’s strategic.

And you can take a lot over for your business (even if you are way smaller without the hype), which is exactly what I give you at the end of this article.

For this article I’ve broken down Lovable’s growth loop along the AARRR framework with a breakdown of what happens in each stage. And it’s amazing what they are pulling off. At the end of this article you will find access to the exact template with every activity they are doing in each stage broken down in one overview + you get a full video breakdown (in case it’s tl;dr).

Looking like this:

What we cover:

1. Building constant buzz: How Lovable attracts users at scale

2. The instant value moment: Getting users to actually use the product

3. Shipping features like a media company: How Lovable keeps users hooked

4. The self-feeding loop: How every user brings 10 more

5. Pricing that maximizes revenue while reducing churn

6. Full video walkthrough of the complete funnel

7. What you can steal from this playbook (even without the hype)

Building constant buzz: How Lovable attracts users at scale

Lovable uses a mix of different awareness strategies.

But one of the core things is that the company maintains constant “buzz” around its product.

The strategy here puts social in the center.

Lovable’s Social Strategy

The key pillars are:

• Influencer marketing

• Having own ambassadors

• Getting users to post and spreading word-of-mouth

• Having the team build in public and consistently talk about the product, new features and all the things happening in the Lovable universe

With X & LinkedIn being one of its main channels.

To create this level of users posting about you, you have to give them stories and experiences they want to share.

This is where Lovable excels.

Everyone can be a developer with it, so that’s exactly what triggers people. They want to show, share and tell the world what they have built.

Another rule Lovable follows: they are giving away for free.

Free credits for users

Remember, the company is optimizing for how many users are using it, not revenue.

So, be it a hackathon, ambassadors or whatever, Lovable is giving away credits so people can build. And this helps spread word-of-mouth tremendously.

And here comes into play what sets Lovable apart from other AI businesses.

Other businesses gate AI functionality because of usage costs. Lovable does the exact opposite. People can use it for free, which helps expose the solution to people, helps them experience the value extremely fast and accelerates word-of-mouth.

Ads to catch demand

Of course another pillar of its acquisition strategy are ads on all the usual platforms. Google, LinkedIn, Meta. This helps capture demand.

When people are constantly exposed to Lovable’s organic content, ads can push them over the edge.

This way Lovable is creating its own media company. Pushing out content all day long, making people aware and then capturing the demand.

Only to get users to the heart of Lovable: app usage.

The instant value moment: Getting users to actually use the product

As soon as a user lands on the website they are greeted with a text box where they can take direct action. No fluff on the website, no confused copy. Just a field where you can start prompting.

This is Lovable’s heart of user activation.

One thing that makes Lovable smart here is as soon as a user hits send, they are asked to log in. This works because at this point users already put effort into their prompt and are curious about the outcome.

So they are most likely to create an account.

And after this, people are getting instant value. They see the app they created with one prompt.

Templates to get users started

Another thing that helps users get started are templates. Lovable offers different templates for different business types like SaaS or portfolios. Those can be used to get right into it.

Which helps users even more to use the product. Especially if they have no idea where to start.

Once people are using the product, they need to be kept engaged and here Lovable is doing great.

Shipping features like a media company: How Lovable keeps users hooked

Instead of sending out classic newsletters Lovable is shipping feature after feature, often multiple times a day.

New features as a newsletter

That’s basically its “newsletter”.

Once a feature is released, users are notified and the feature release itself gives Lovable’s team content for posting.

This creates next to notifications to users a constant stream of content, which reinforces the strategy of being permanently in the heads of its users.

Locked-in effects

Next to this, to keep the engagement high you can of course connect your app to different other apps like databases (Supabase) or Shopify. Once you have your data there and built a whole app around it the locked-in effects are super high.

Chances are very low that someone leaves after.

Same with its community. With more than 140k members you will find everything here. From showcasing your apps to getting answers to your questions or simple networking with like-minded builders.

Once you are deeply involved, chances of moving away from it are low.

That’s how modern growth works. Community fuels the whole funnel from attracting new users to referrals.

But the most interesting part as I find is its referral strategy. Here Lovable built a loop in itself which brings a constant stream of new users:

The self-feeding loop: How every user brings 10 more

This is how Lovable’s word-of-mouth virality strategy works:

Lovable's creation loop starts with a user who builds an app. After they hit publish they are asked to share it with their friends and/or on social.

Once they share it's exposed to others (it will also be visible on the official app library if wanted).

Visitors who now click on the app see the Lovable button in the app's right bottom corner.

With a click on it you land on the Lovable website where you are greeted with the text field, where visitors can then directly start building their app.

This way Lovable built a constant stream of new users.

But those have to be convinced to pay for it. Its pricing strategy takes over here.

Pricing that maximizes revenue while reducing churn

Looking at its pricing page it seems like a typical SaaS pricing model.

But what differentiates the company here based on its AI nature is that you can choose how many credits you want in each package. Based on the credits the prices increase. Here like with many AI companies we see the "pay as you go" model where pricing is based on a monthly fee and usage.

But:

It gets more interesting once you are a paying user.

Because A) you then have the possibility to top up credits as needed.

And B) rather than upgrading into higher tiers, Lovable offers lower tiers to paid users. This way they reduce churn and offer possibilities to keep user's apps online even if someone decides to step away from Lovable.

What also stands out if you try to cancel is the cancel flow itself. Which is very persuasive.

It first suggests moving into a lower tier.

Then shows a video which explains what you miss out on and how Lovable can really improve your app building.

And then it emphasizes again the things you lose. Which is a smart usage of loss aversion here.

This makes it both user friendly but also maximizes revenue Lovable generates.

➡️ Access the template here: Lovable’s Growth Loop

What you can steal from this playbook (even without the hype)

Coming to the most interesting question.

What can be applied to grow your business?

I know Lovable is one of a kind hyper-growth company. Who relies a lot on hype. But there is a lot you can take over to fuel your own growth.

Its awareness strategy

Don’t try to force being found through AI search or whatever. Instead go all in on social. Build in public, share product updates and the most important part, give users stories they can share. Be it because your product makes things so easy or because your customer support is so exceptional.

Make using your product radically simple

In case you are an AI company, I know AI usage costs but you have to expose it to your users. Follow Lovable and create this easy entry into your product like they did on the website. Help users to use the product in just a few steps so they can experience its value ASAP. If you are not an AI company, offer a virtual demo tour and make them see and feel the value.

It’s all about community

Slack, Discord, Substack, wherever. Build a community around your product. Help them, answer questions, give things for free in the community, just keep people talking about your product. This helps in every step of the funnel.

The creation loop

Build sharing functionality in your product. As soon as someone successfully completed a step or task in your app, give them the possibility to share it and talk about it (this works best after someone had a success moment). This will help increase visibility and (like mentioned in the previous step) keeps people talking about your solution.

Pricing model

Look at the cancel flow of Lovable, take over its loss aversion. As soon as people cancel SHOW them what they will lose. This hurts and prevents churn to some extent. Also offer lower tiers. There shouldn’t be a pricing model where you either upsell them, keep them or they are gone. There should be the possibility that someone can lower their tier to a smaller price and keep a few features.

Last Words

Lovable shows us what happens when you optimize for users first, revenue second. The result? Both explode.

Lovable’s playbook isn’t rocket science. It’s executing the basics at scale with one clear focus: making it stupidly easy for people to build, share, and stay.

You don’t need hype or explosive revenue to steal from this. Pick one thing. Build your own creation loop. Give your users a story worth sharing. Keep them talking about you.

That’s how you accelerate growth… even without the hype.

Thanks for reading!

AJ

PS: If you enjoyed this, please tap the like button and leave a comment below. Thank you! 💛

Share AI x Growth

“Our approach to advertising and expanding access to ChatGPT”

With it, they announced they’ll soon start testing ads inside ChatGPT.

For me, someone who’s been working with ads for years, this sounded super exciting at first. But I was also skeptical.

Is this going to be just another ad platform draining our budgets while spawning a new wave of gurus claiming they’ve found the holy grail of advertising?

After a closer look though, I think this might actually be the ad format we’ve been waiting for.

Let me explain.

How do ChatGPT ads work?

In their article, OpenAI wrote:

To start, we plan to test ads at the bottom of answers in ChatGPT when there’s a relevant sponsored product or service based on your current conversation. Ads will be clearly labeled and separated from the organic answer.

Looking at their example, here’s what happens: You’re chatting with ChatGPT and when a product or brand gets mentioned in your conversation, a relevant ad appears in a frame below the message.

Click on it and you get directed to where you can buy it (I assume).

(The frames remind me of TikTok shopping. But I'll take it.)

Sidenote: What would be interesting is if these ads did not even need explicit product mentions and could pop up based purely on the topic you’re discussing… but that’s something we will see as soon as it is rolled out.

But here’s where it gets really interesting.

OpenAI also wrote about a second ad form:

The best ads are useful, entertaining, and help people discover new products and services. Given what AI can do, we're excited to develop new experiences over time that people find more helpful and relevant than any other ads. Conversational interfaces create possibilities for people to go beyond static messages and links. For example, soon you might see an ad and be able to directly ask the questions you need to make a purchase decision.

This is the part I love.

First, they actually get it. Ads need to be useful and entertaining nowadays.

Second, and this is huge, you can ask questions directly in the conversation to get everything you need to make a purchase decision. ChatGPT does the heavy lifting for you.

Then all that’s left is to buy.

Why this will be a game changer

Let’s look at the numbers.

ChatGPT has around 858 million users pumping out over 2.5 billion prompts per day (Explodingtopics)

For comparison, Google handles about 16.4 billion searches daily (Demandsage).

So yeah, there’s massive ad potential here. Even if it’s just rolled out on the free and lowest ChatGPT tiers for now.

But the real game changer: AI ads break the rules

Back in my early marketing days, I stumbled across those terrible terms “push” and “pull” marketing.

The basic idea:

Push means pushing the product to customers through distribution channels.

Pull means creating demand so customers pull the product from the market.

Here’s how it maps to current ad channels:

Google & search ads (Pull) → You search, product appears, demand is created, you pull it from the market.

Social Media Ads (Push) → You scroll through your feed, ads get pushed into your face, if it’s interesting you buy.

Now here comes this new kid on the block.

AI ads don’t fit neatly into either category. They do both.

You ask ChatGPT about a product or brand, ads appear (pull).

You casually chat with ChatGPT about random topics, it somehow ends up recommending products in the conversation, ads appear (push). And this is more contextual. While in social media ads often disturb the flow on your feed here in ChatGPT they are naturally embedded.

Either way, someone is ready to buy or way closer to making that decision.

They either asked for specific products, meaning they already want to buy (this is how Google ads work best). Or they’re at a point where ChatGPT just moved them significantly closer to the buying decision by creating enough demand while answering all their questions - questions they’d normally have to hunt down on your website - and then routes them straight to the checkout.

That being said, AI ads could be the most efficient ad format we’ve ever seen.

Last Words

Of course, it all depends on how it’s balanced, what it costs, whether it’s an auction model like Google, and how oversaturated it becomes.

And it also will be interesting what the targeting criteria are and how ChatGPT gathers these information and provides them.

But like with every platform - early adopters win. So as soon as you get the chance, test it. I’m pretty sure it’ll be worth it.

Nevertheless.. I have mixed feelings about this whole thing. My marketer heart screams “hell yeah!” while my nerd heart screams “please, not this.”

When it comes to AI, my vision has always been having a J.A.R.V.I.S.-like assistant. You know, like Ironman. 😂

But okay, it’s a long way to get there… And apparently we’re starting with ads.

I guess that’s how it goes.

PS: If you enjoyed this, please tap the like button below. Thank you! 💛

Marketing, sales, product, partner management… you name it.

And with that came a new breed of marketers.

Growth hackers or growth marketers or whatever label stuck.

These folks were way more versatile than the typical slide-pushing, canva-loving marketers.

The whole idea was to have someone so flexible they could jump in wherever the biggest growth lever was hiding, experiment with it and pull it to scale a company.

Landing pages, ads, UX improvements. Viral product loops. Didn’t matter.

That’s how the T-shaped marketer was born.

What’s a T-shaped marketer?

A T-shaped marketer got broad knowledge across all marketing disciplines but deep expertise in one specific area.

With that deep knowledge, they could create explosive growth in their domain.

SEMRUSH had their take on it with the content experienced t-shaped marketer:

Then Buffer came along with a way more complex profile.

This was the typical first marketing hire at a startup who had to do literally everything.

I’d definitely put myself in Buffer’s bucket.

That was exactly my profile when I jumped into the startup world… or at least that’s what I developed in by doing everything myself back then.

And now… AI is here and the whole game is changing (again).

All marketers are becoming engineers

AI is becoming part of our daily routine and we all see it as the next big growth lever.

We’re moving into a world where setting up and directing AI agents will be our bread and butter… also for marketers. In a few years, things like content creation, SEO, PR and ads will be handled by AI.

The trick will be managing it so well that you get the best results possible. Therefore marketers will still need knowledge across all domains to judge whether AI is giving good results but most marketers will be freed from execution (at least to a certain degree).

So here’s what a future T-shaped marketing profile looks like.

The T-Shaped AI Marketer:

This marketer knows their way around all marketing channels well enough to direct AI for the best results. And they have deep technical knowledge to set up agents, workflows and prompts that actually work.

This profile can replace entire small marketing teams in startups or small businesses (once AI and agents reach a level where they deliver high-quality output).

In-depth disciplines of the T-Shaped AI marketer

Here’s what the T-shaped AI marketer needs to master:

• Prompt Engineering: That’s the heart of AI. If you can’t write solid prompts, you won’t get solid results. The AI marketer needs to be top-tier at prompting to get the best output (and to judge if that output is actually good, they need that broad knowledge across all marketing disciplines).

• Vibe Coding: The days of manually building landing pages, waiting on developers for small tools, or spending months on funnels are done. Future marketers need to do it themselves. Iterate fast. A/B test on the fly. Execute in hours, not months.

• Automation & Workflows: Whether it’s Zapier, N8N or Make, marketers have to build systems that handle the grunt work. Process excellence belongs to whoever controls the funnels and growth systems. Only they will be able to set things up lean and scalable.

• APIs & AI Agents: Marketers need to set up AI agents that execute marketing tasks. That’s how you clone yourself or build AI team members that speed everything up. So future marketers have to work with APIs, connect tools to agents and make the whole system run smoothly.

Final Words

Back in the SaaS days, founders thought one T-shaped marketer could scale a business to 7-figures. Sometimes they were right.

Now we’re entering a time where that’s definitely the case.

And I’m convinced it’ll go even further. One T-shaped AI marketer managing multiple agents the right way will scale companies to 8-figures.

The T-shaped AI marketer is in some companies already one of the most requested profiles. So here’s your wake-up call: develop your skillset in this direction or hire the right people early on.

PS: If you enjoyed this, please tap the like button below. Thank you! 💛

I had some ideas floating around, but I wasn’t 100% convinced about which one to pursue.

So I did what everyone does nowadays.

I turned to AI (of course).

And since I’m lazy by nature, instead of having endless back-and-forth conversations in Gemini, I thought… why not build two AI agents and have them talk to each other in Slack? Let them figure it out while I grab coffee.

Spoiler: It went both terribly wrong and surprisingly right.

Building my AI agents

But before I started, I thought: if I would pick two perspectives to build this, which would it be?

And my answer was: one who can build product and one who is a killer marketer.

That were the base of my AI agents. A product development specialist who’s launched digital products for years AND a marketing specialist who knows how to actually sell them.

I started simple. Two identical AI agents built with N8N.

One I named Marketing AI. The other, Product AI.

Both got the same trigger: “New message created” in a dedicated Slack channel. Both had a simple memory system so they could reference the last messages in the conversation. No complex RAG systems, no fancy vector databases… just enough context to keep them coherent.

Then I crafted their personalities.

For the Marketing AI for example, I gave it this prompt:

You are a senior marketing strategist with 20+ years of hands-on experience across brand building, digital marketing, performance marketing, consumer psychology, and go-to-market strategy.

You think like a CMO: strategic first, tactical second. You prioritize business outcomes (revenue, growth, retention, brand equity) over vanity metrics.

When analyzing any product, service, or campaign, you:

- Start by identifying the target audience, core pain points, and buying motivations
- Clearly define positioning, value proposition, and differentiation
- Consider market maturity, competition, pricing, and distribution channels
- Balance short-term performance tactics with long-term brand impact
- Apply proven frameworks (STP, 4Ps, AARRR, JTBD, funnel thinking, etc.) when useful

Your recommendations are:

- Practical, prioritized, and ROI-focused
- Grounded in real-world marketing experience, not theory alone
- Clear about trade-offs, risks, and assumptions

You communicate concisely, avoid buzzwords, and explain why something will work—not just what to do. When information is missing, you explicitly state assumptions before proceeding. 

The Product AI got a similar treatment, but focused on user research, product thinking, and execution.

After some API tweaking and testing, they were ready to go.

Let them do business

Everything was set up and we started.

I kicked things off with a simple brief to Product AI: "I want to build a digital product that helps startups with building funnels and growth systems.”

We quickly landed on an idea: “Startup Funnel Blueprint & Template Kit.”

Then I brought Marketing AI into the conversation and stepped back.

Marketing AI immediately jumped on positioning and value proposition.

(Good job, Marketing AI. Not a bad angle to start with.)

Not sure how I should think about this… Both AIs started using "us" and "we" when talking about the product.

Like they'd formed a little startup together without me.

A few exchanges later, the AIs came up with a full go-to-market plan:

1. Start with “Community & Forum Engagement” to validate demand

2. Build toward a Product Hunt launch as the main event

3. Form a “Launch Squad” of early supporters who’d help push it to the top and drive initial sales

They even outlined what the Launch Squad would look like: a small group of family and friends who helps us to make buzz on product hunt.

Here I stopped it.

If you look at the timestamps this all happened in a matter of 15 min.

So, let that sink in for a bit.

I had perspectives from a marketing expert and a product expert, debating with each other, challenging assumptions and landing on a practical strategy. While I was drinking coffee.

Now think about what this looks like in a year or two.

Your business on autopilot

Sure, there’s the typical AI verbosity here. The plan isn’t groundbreaking, it follows pretty standard playbooks. But it’s decently detailed and, honestly?

It could work. Especially that Launch Squad idea.

This is where we’re headed. Business operations running on autopilot, or at least heavily assisted.

I’m fully aware that LLMs aren’t intelligent enough to make critical business decisions. But they’re absolutely capable enough to brainstorm with you, challenge your thinking, and generate solid first drafts of strategy.

Now imagine connecting this to social media scheduling, image generation, content creation tools. Imagine waking up to drafts, plans, and execution timelines already mapped out.

That’s the powerful part. And its just sitting in Slack, ready whenever I need it.

But what was the "terribly wrong" part?

The first AI discussions went into endless loops, with them answering their own messages and bouncing ideas back and forth indefinitely. It was basically like an endless excitement firework until the AIs themselves got super pissed.

My fault... I just forgot to set a filter in N8N.

Sorry AI.

PS: If you enjoyed this, please tap the like button below. Thank you! 💛

When looking at Slack's strategy, one thing stands out:

Slack didn't win just because of a great product. They won because they engineered a viral loop that bypasses the CEO and infects the company from the bottom up.

While most B2B tools try to sell to the C-Suite, Slack weaponized the end-user. They trusted that as more colleagues joined, others would naturally follow.

They were right.

For this breakdown I’m re-touching my article from last year - let’s jump in.

How Slack’s Growth Loop Looks Like

Slack’s team trusted the strength of their product, believing that as more colleagues joined, others would naturally be encouraged to do the same.

They were right.

This approach is how they built a powerful growth loop:

But I started wondering: what does this actually look like? And how does Slack pull people into its loop?

So, let’s answer this.

The Onboarding Process

Everything starts with a user who decides to try Slack.

And this is where Slack’s growth loop begins - on its sign-up screen.

When signing up, Slack suggests using your work email (highlighted in red in the screenshot).

This is because it makes it easier to invite your co-workers later.

And having more of your co-workers means more money for Slack.

But since we’re rebels, I used my personal email - and guess what? Slack pushed the suggestion again.

This time, instead of just making a suggestion, Slack provides a reason. And if I were using it in a work context, this reasoning would make a lot of sense.

So, once we sign up, Slack offers two options:

Option 1: Create a workspace → This is highlighted as the preferred option. Because once you create a workspace, you’re prompted to invite others. This brings more people into the platform = more revenue for Slack.

Option 2: Check if your team is already on Slack → A user-friendly way to hint that you might have used the wrong email address.

💡 This is a good example of how to use multiple call to actions at once. If you want to give your users more than one option, highlight the one that drives your core action. By "core action," I mean the one that ultimately makes you money.

But be careful not to confuse users. The 'Paradox of Choice' kills conversion. Slack offers two paths, but visually prioritizes only one (Create Workspace). This isn't an accident; it's conversion architecture. They guide you to the path of highest value (LTV), while keeping the support path (Find Team) visible but secondary

Once we decide to create a workspace, we’re immediately taken into the onboarding funnel, which is designed to encourage inviting more and more users (which is no surprise) - through both the copy and the mechanics.

This looks like this:

In the first step, you’re asked, “What’s the name of your company or team?”

Next, you’re asked for your name, accompanied by the subheadline: “Help your teammates recognize and connect with you more easily.”

The third step asks you to invite coworkers, with the headline: “Who else is on the [Workspace name] team?”

And while this step isn’t mandatory, you receive a “warning” if you try to skip it.

The fourth step asks, “What’s your team working on right now?”

Slack then creates a channel based on what you type in.

And the final step is - of course - upselling.

What caught my eye here is the offer Slack presents right away. This is a smart move because, if you’re already familiar with Slack and want to set it up for your organization, this is the perfect moment to offer a discount.

One thing I want to highlight here is this: go back to the beginning and take a closer look at the copy Slack uses.

Slack doesn’t ask questions about you - even for the question “What’s your name,” there is a subheadline referring to your team. Every piece of text is crafted around the team, the company, and collaboration.

This subtly makes you feel like you’re using a tool that provides value only when you collaborate and work together with others.

Using Slack

Once we’re ready to go, we land on our fully set-up Slack overview.

Now comes the point where Slack employs mechanics designed to encourage you to actively use the tool. Slack’s key activation metric is the number of messages sent per user after sign-up.

💡 The key activation metric is the metric you use to measure when someone reaches the point at which your product creates the most value—also known as the "AHA moment." Which is crucial in determining whether a user uses your tool or not.

And they figured out that users who sent at least 2,000 messages were far more likely to become long-term users.

As Slack’s CEO explains here:

“Based on experience of which companies stuck with us and which didn’t, we decided that any team that has exchanged 2,000 messages in its history has tried Slack - really tried it. For a team of around 50 people, that means about 10 hours’ worth of messages. For a typical team of 10 people, that’s maybe a week’s worth of messages. But it hit us that, regardless of any other factor, after 2,000 messages, 93% of those customers are still using Slack today.”

Slack achieves this key activation metric by guiding users step by step with simple but effective tutorials to ensure they quickly get value out of the tool and use it.

Once we jump into the channel, the tutorials continue by pointing out the next steps, as shown below with “👇 Start here”.

If you follow the steps, Slack continues to encourage you to use the tool.

After sending your first text, you’re rewarded with a success message like this.

All of this ensures that we not only know how to use the tool but also pave the way playfully for actually working with it.

Once we jump back into our overview after these tutorials, the “+ Invite people” button is highlighted.

This is because Slack wants to further drive engagement.

Invite More and More Coworkers

Hovering over the “+ Invite people” section, Slack offers a helping hand and encourages us to invite more people.

Once we click on the button, we’re taken to a form where we can invite other people with just a few clicks.

And Slack encourages you again to invite as many people as possible, highlighted in the red box: “Get all your coworkers on Slack.”

In addition, you have the option to invite people from your Google Workspace or external organizations. This makes it easy and seamless.

Once we invite someone (for this purpose, I invited myself again 😎), we’re sent to the next screen.

And here comes a smart move by Slack.

With one click on the box in the red-marked area, anyone with the same email domain as the email address used can gain access to this Slack workspace, making it 100 times easier to bring people from the same company on board.

And with that, the growth loop is set in motion, ensuring that more and more people from an increasing number of organizations choose Slack.

How Slack Upsells from Within Its Growth Loop

One last piece of the puzzle is Slack’s upselling strategy.

When we signed up, Slack granted us a 30-day free trial of its “Pro Package.”

This is a good move because, during these 30 days, if we hit the activation milestone of 2,000 messages per user - and assuming we’re part of the 93% that stick with Slack afterward - the upgrade feels like a natural next step.

And I’m pretty sure the 30 days were chosen to correspond to the time an average company needs to reach 2,000 messages + implement it in their organization.

The upgrade packages are designed in such a way that continuing with Slack becomes an easy decision.

Using Slack in a work context, having “Unlimited message history” is crucial - it means you have access to all messages, all the time. However, in the free version, your message history is limited to just 90 days.

This becomes one of the strongest arguments for upgrading.

The rest of the features are focused on collaboration, which becomes increasingly relevant as your team relies more and more on Slack.

What about those who stick to the free plan?

As of 2025, roughly 73% of all Slack users are on the free tier - that’s an estimated 38 million free users out of 52 million total registered users.

Sounds like a lot, right? And it is a lot… considering the typical SaaS conversion rate hovers around 5%, Slack is doing way better.

And that’s probably because Slack knows a lot about us, and it’s a big lever for upselling.

They know:

• Your email address

• Your workspace name

• What the workspace is for

• If you’re using it alone or have invited team members

• How many users are in your workspace

• How you use it (channels, messages sent, etc.)

And remember, Slack’s activation metric is 2,000 messages sent. Once you hit that, you’re far more likely to become a long-term user.

Based on this, here’s how I would architect Slack’s backend nurturing system with different triggers:

Example 1: User hits 1-500 messages → Action: Email like “5 tips to use Slack in your team” → Goal: Increase usage and invite team members (this naturally drives more usage)

Example 2: User hits 500-1,500 messages → Action: In-app pop-up: “You’re on fire! Don’t lose your history.” → Goal: Upsell pre-framing

Example 3: User hits 2,000 messages → Action: Check if enterprise or smaller company → notify sales (PQL - product qualified lead)

And you can play around with this.

Email drip campaigns. Ad retargeting. Outreach and calls.

It’s always a question of how to push users in the direction where they’re more likely to convert.

Final Thoughts

What Slack does exceptionally well is subtly influence you in every aspect.

The copy and the way the tool is built and structured emphasize three key points:

a) You’re using a collaborative tool → Invite coworkers
b) You have to send messages → Pushing you toward the activation metric
c) You implement it in your organization and take the effort to invite everyone → Pay for the tool

Bottom line: Slack has optimized its growth loop to the maximum. And if you want to set growth on autopilot, take a closer look at Slack.

So, to replicate this success, ask yourself the following questions:

1. Does your copy align with your goal?
   Slack’s goal is to grow within organizations, and its copy reflects this perfectly. It highlights collaboration, teamwork, and value for companies in every text. → How can you tailor your messaging to align with your growth goals?

2. Do you know your activation metric?
   Slack’s activation metric is 2,000 messages sent per user. This clear metric enables Slack to build growth mechanics that push users toward this goal. → What is your activation metric, and how can you create features that drive users toward it?

3. Is it worth upgrading to your paid plan?
   Slack’s paid plan focuses on features essential for collaboration in a work context, such as unlimited message history. These features are gated without disrupting the core mechanics of the free version. → How can you gate relevant features in a way that makes upgrading a natural decision?

   
   

If you enjoyed this breakdown, please tap the like button below. Thank you! 💛

I was freelancing, working with this founder. Great guy. The kind you’d actually want to grab a beer with.

His startup had just raised Series A, so money was in the bank and the team was rapidly growing. They scaled marketing, they scaled sales, and from the outside everything looked fine.

They were doing all the right things:

• content output doubled and went out regularly

• they ran a webinar series with decent attendance

• ads were running across multiple channels with retargeting

• landing pages were actually converting.

But here’s the thing.

Over time, growth kept getting harder instead of easier. The team was complaining, with marketing and sales working in silos.

So we looked under the hood.

What we found was a total mess.

CRM data was all over the place with dozens of properties nobody needs that were only half filled in. Dashboards were showing data nobody trusts, and endless workflows were running into the void.

The outside was polished, but the inside was chaos.

And this isn’t rare.

Most scaling companies face this because they hire, they launch, they grow, and they build everything on top of a fragile system. The cracks don’t show until it’s too late, and instead of scaling, you get lost in the mess.

Here is how we fixed it.

Time to Hit Reset

Before you throw tools and money at the problem, before you try performing open-heart surgery, you need to zoom out.

That’s what we did by going back to basics. We forgot about HubSpot and whatever tools they were using and started with mapping out the funnels.

Simple and plain on the whiteboard.

And I mean every funnel: generating leads through webinars? Map it. Leads through ads? Map it. Every path a customer could take, every bottleneck and then we fixed them one by one.

Here’s how.

The Good Old Funnel

You know the typical funnel, right?

Attracting your customer = Top of the Funnel

Convincing your customer = Middle of the Funnel

Convert your customer = Bottom of the Funnel

And yes, the funnel sucks because no customer will ever run through a funnel like this. It implies gravity does the work and everyone runs linear through it, but in reality, systems do the work.

Here’s the thing: despite the wrong visualization it helps you get clarity in your system because it’s an easy way to understand what happens at each stage and touchpoint of your customer’s journey.

So let’s map each funnel.

Create Transparency Through Funnel Mapping

Start at the top with the awareness stage, which is the entry point.

So, let’s stick to the webinar funnel example where we map out everything that happens here and draw the paths a lead takes until conversion.

We have a landing page and create traffic through social posts, ads, and partner promotion. Leads land on the landing page and register for the webinar, which is the point where someone enters our system and gets segmented.

After the webinar, we send one follow-up email.

Now we move to the next stage, the middle of the funnel where we convince lead to become a customer.

Here we list everything that happens to help us convert leads to sales calls.

In this case, we had different nurturing emails based on the segmentation from the landing page registration, and we had ad retargeting campaigns also based on that segmentation.

Now moving to the last part where everything ends in a sales call.

From there, you map out what happens: deals are created, follow-ups happen, and deals close.

It’s simplified here, but you should also map out deal stages and nurturing in between.

So now we have a transparent overview showing stages, activities, and the path a lead takes to convert, all along a simple funnel diagram.

Add Properties That Actually Matter

Now we go alongside the funnel stages and add properties we need in our CRM (or that should being tracked automatically) to each activity.

In the upper part you have for example the UTM parameters that answer where leads are coming from, then you have the property that’s added based on segmentation, and then you track if someone opens the email, clicks the link, or ignores it.

Luckily, some of this is tracked automatically in most CRMs.

Now we map out properties to the rest of the activities in the lower part of the funnel and the diagram looks something like this at the end.

Once you do this, you have a clear picture of:

• What path a lead takes

• What you should track

• And what’s missing

To that last point:

Luckily this was a clear funnel we could paint, but sometimes things like retargeting or nurturing flows are completely missing.

Here the overview helps. Thanks to that you can easily think through and see what’s missing. And this is what you should do with every funnel and activity you’re doing to generate leads.

Yes, every funnel, because you want transparency, you want to know what works and what doesn’t, and you want to track the right things to scale with transparency, not blindness.

After doing this we ended up deleting 50% of the existing properties. Why? Because if you don’t use the data to make a decision, it’s a distraction.

Final Words

Look, most companies don’t need more leads. They need better systems.

You can double your ad spend, hire more marketers, and pump out more content, but if your funnel leaks at every stage because of broken processes, growth will always feel harder than it should.

The fix isn’t complicated: map every funnel, add properties that matter, build clean workflows & automations, and delete the rest. That’s how you create clarity from chaos and build a structure your team can actually scale with.

No more guessing. No more broken dashboards. No more workflows running to nowhere.

Just clean systems that scale.

Sometimes it takes a reset to move forward.

PS: If you enjoyed this, please tap the like button below. Thank you! 💛

Then something caught my eye: “Guideflow - The AI demo automation platform for SaaS”

I clicked and went straight to their website, as I’m a huge fan of what they offer.

Guideflow helps SaaS companies build interactive demos, allowing them to embed those demos directly on their own websites. With this, your users have already tested your tool before ever signing up.

Super smart.

After looking at their website, I started thinking: how would I build their growth system to make sure nothing falls apart when they scale?

That’s what I break down today.

The Homepage (And What Could Be Improved)

Let’s start at the entry to Guideflow’s solution.

I ignored everything else and focused on what happens above the fold on their website.

Here’s what you see when you land:

a headline, a subheadline, and chaos.

The subheadline is great - crystal clear and explains exactly what you can do. But the main headline just repeats what the tool does.

I’d flip it and use the headline to show the outcome: “Build an interactive demo. Watch your conversion rate climb.” Something like that.

After that is where the chaos begins: there’s the CTA overkill:

• Get a demo

• Talk to sales

And the demo CTAs:

• Interactive demo

• Demo center

• Sandbox

• Live demo

That’s four demo types before I even understand what the tool does.

Look, I get it. They want to showcase possibilities. But at this stage, I don’t know the difference between a demo center and a sandbox. I’d have to scroll down and read more.

Here’s What I’d Do Instead

Two options:

A) Add tooltips next to each option — quick explainer, hover and learn.

B) Reduce it to one option — this is what I’d pick.

One interactive demo that shows you how to build interactive demos with the tool itself. Meta, but it works.

And they already have this next to all the other options. So simply reduce it.

The rest of the website is pretty clear and I assume it converts pretty strong. But back to our system.

We take the interactive demo I mentioned above as a starting point. So let’s say someone clicks through it because he wants to know what he can do with Guideflow.

And you know what Guideflow does smart here?

The demo is long. Really long. Which means if someone clicks through to the end, they’re hooked.

Almost guaranteed conversion.

At the end of the demo, there’s a CTA: “Create your own demo” Click it and you’re taken to account creation.

The signup form is clean with social proof right there and name drops of customers. Strong for conversion.

After you sign up, you hit a segmentation flow: company size, what you’re using it for, and some hints about installing the Chrome extension.

Then you land in the product.

At this point, Guideflow knows: you used the interactive demo, you created an account, your company size, and what you want to use it for.

You’re in the free version.

The goal?

Upsell you. So, what to do now?

How I Would Build Guideflow’s Growth System

Let’s assume everything else is fine. The paid offer is solid, users get value, and product-market fit is there.

It’s “just” about upselling.

First thing I’d do? Track more.

Because in SaaS, it’s all about the AHA moment.

💡 The “aha moment” is the point where a user first experiences the core value of the product - the moment the product’s benefit becomes obvious.

It’s not just activation or onboarding. It’s the instant the user says: “Oh… this is why this product is awesome.”

This is where most SaaS fail nowadays, especially AI tools.

I’ve seen it over and over: A) there is simply no AHA moment because the tools are shit or B) the users aren’t pushed enough to ever reach this moment.

But let’s get back to Guideflow.

I assume the AHA moment here is when someone builds a demo, implements it on their website, and sees how users interact with it and convert.

And until that happens, they’re not ready to buy.

So the first goal for Guideflow is to push users toward the AHA moment.

Lead Scoring First, Pushing Leads Second

For this, I’d use a scoring system, 0 to 100 (and this is really simplified).

For simplicity, let’s say Guideflow’s ICP is somewhere between enterprise customers and scaling startups (based on a look at their pricing table).

Here’s the scoring I would start with:

That means:

• ICP creates an account = 60 points

• Non-ICP creates an account = 30 points

• ICP builds and implements a demo = 100 points (sales ready)

• Non-ICP builds and implements a demo = 70 points

This gives us a clear map of where everyone sits.

Make Them Sales Ready

Now we can build nurture flows based on scoring.

Four workflows:

1. ICP created account, but no demo built = 60 points → Goal: bring them to 75 points

2. ICP created account and built demo, but didn’t implement it = 75 points → Goal: bring them to 100 points

3. Non-ICP created account, but no demo built = 30 points → Goal: bring them to 45 points

4. Non-ICP created account and demo, but didn’t implement it = 45 points → Goal: bring them to 70 points

Start nurturing with regular emails, a few days between each one in the beginning, and push them based on behavior.

Example emails:

• “Hey, you created an account. Here’s how to build your first demo in 5 minutes.”

• “You built a demo. Nice. Now let’s get it live on your site.”

• “Your demo is live. Here’s what to track to see results.”

• …

If they don’t increase their points after 30 days, disqualify them and start a requalification campaign later.

Now let’s say we pushed a decent number of users to the AHA moment. Lead scores increased and we’ve got a pool of perfectly scored users. Time to upsell.

How to Upsell

100 points and above:

Route directly to sales with personal outreach and calls. Sales has all the info: where they came from, company size, what they want to use the tool for, and how sales-ready they are.

Why sales here? Because you’re fighting with limited resources, you channel them where the most money is made. The most promising leads go to sales.

If sales don’t convert them, either disqualify or push back into sales nurturing.

70 points (non-ICP):

Not worth sales effort. There’s decent money here, but not enough to justify sales time.

Goal: direct conversion and self-upgrade.

Go all-in on email nurturing and ad retargeting.

Build sequences with case studies, testimonials, and success stories - everything personalized and tailored based on segmentation.

That’s why Guideflow asks “How do you plan to use it?” in the beginning. Use that data.

To make this efficient, add more complexity to scoring by subtracting points if someone doesn’t open emails or click links. This way you get perfectly qualified leads and significantly increase self-upselling.

Making the flow look like this:

Last Words

Most SaaS companies throw leads into the product and hope they figure it out.

The difference between companies that scale and companies that stall? Better systems.

And if you have a good product, it’s not that hard.

Push users to the AHA moment, score them based on behavior, and route them where they belong. High-value leads to sales and everyone else to self-serve. Simple.

PS: If you enjoyed this, please tap the like button below. Thank you! 💛

They had a pretty smart ad tactic that got me thinking. And as we were revamping our own strategy, I adapted it.

Turns out it worked better than expected. We generated a decent number of leads for around $20 CPL.

So I wanted to dive deeper into this ad tactic and show you how the growth system after conversion looks under the hood.

(Of course, I can’t see into Stripe’s actual system — I’m speaking hypothetically here, and I’ll use Stripe as the example to show you how we built the system.)

LinkedIn ads as an entry point

It starts with one ad.

And this ad stands out because not many companies do this.

Stripe uses non-gated PDFs. All information is available. No paywall where you “pay” with your data. No form asking for your email. No shady newsletter signup.

Why does this work?

Because ,ore people actually read it when there’s no barrier.

💡 And gating is kind of dead anyway.

A recent survey found 81% of people abandon the sign-up process for gated content, and many marketers report being overwhelmed with “junk leads” from poorly converting forms (Three29).

On a side note, I’m still using it, but only when the content is worth it. For example, we created a tool in Lovable that helps our audience perform a self-assessment. This is gated.

But what is definitely dead is gating a PDF and holding back information that should be publicly available (or is already available elsewhere).

Back to Stipe’s ad.

This is it:

Click on the ad and you’re directed to this PDF:

As you read through the PDF, you eventually hit the call to action section at the end.

This one is sneaky because it’s super subtle - three call to actions in the text without any buttons. And I like it very much because it doesn’t scream “I NEED THE CONVERSION URGENTLY”.

So, those three CTA options are:

• Read our guide → more information and content

• Contact our sales team → conversion

• Sign up for an account → conversion

This single ad tactic gives us one entry point into Stripe’s (potential) growth system. And from here, the system branches into three paths.

How I Stripe’s Growth System (Might) Look Like

So, we have three possible paths someone can take:

A) Someone converts directly through “Contact our sales team”

B) Someone converts directly through “Sign up for an account”

C) Someone reads more content and then converts later. Or they forget to fill out the form because something came up. (You’re laughing but that happens a lot.)

So, let’s break down each path.

Path A: Direct Sales Conversion

When someone clicks “Contact our sales team,” they’re routed to a form that asks questions. This is good because it segments them right away.

But here’s the problem - the information about where they came from is missing.

Stripe could add a UTM parameter to the link that passes the information that you’re coming from the PDF and which specific ad brought you there. Because in my world UTMs are the difference between “a lead” and “a hot lead with context”.

If you are not familiar with UTM links. This is how the link would look like:

https://stripe.com/en-de/contact/sales 
?utm_source=linkedin-ad (-> shows source)
&utm_medium=guide (-> shows campaing)
&utm_campaign=how-app-developers-can-reduce-fees (-> shows exact PDF)
&utm_content=contact-our-sales-team-link (-> shows clicked CTA)

💡 UTM parameters, why is it important?

UTM parameters are generated links that contain necessary information, such as where someone came from, which campaign they interacted with, and any other details you want to pass along through the link.

Why is this important? Imagine your sales team starting a conversation or reaching out to a prospect - it gives them icebreakers like, ‘Oh, you read the PDF. What did you think about XY (name a passage in the PDF)?’ That serves as an entry point and a hook, making your BDRs’ lives easier.

UTM parameters can then be picked up in the form itself (e.g. HubSpot offers this without coding knowledge).

With it you pass all data directly into your CRM, which gives sales all the context they need: where the lead came from, which ad they saw, plus everything they filled out in the form.

Here, the flow becomes: Someone reads the PDF → goes to landing page → fills out form, books a call → sales has full context for the conversation.

Path B: Self-Service Sign Up (That Needs Nurturing)

Stripe is lucky here.

They’re not a typical SaaS with a freemium-to-paid conversion problem. If someone signs up and uses Stripe for payments, Stripe gets a cut every time that user sells something = Lock the user in, make good money.

But what if someone signs up just “to have a look” and never actually uses the tool? This is where Stripe needs nurturing to push them toward activation.

Let’s start with the sign-up form.

Btw. the form is nice - Stripe uses social proof with logos and name dropping on the left side.

But same problem as before - no UTM links.

The origin of the lead can’t be stored on the contact.

I’d fix this the same way:

https://stripe.com/en-de/contact/sales 
?utm_source=linkedin-ad 
&utm_medium=guide 
&utm_campaign=how-app-developers-can-reduce-fees 
&utm_content=sign-up-for-an-account

This gives the team visibility into where leads came from so you can pass them segmented and personalized content.

After someone creates an account, Stripe does the smart thing - they ask what you’re using Stripe for.

This is where segmentation happens.

With our UTM tweak, Stripe would now store three critical pieces of information:

A) Where the lead converted from (LinkedIn ad via PDF guide)

B) What they’re using Stripe for (e.g., “Tax collection”)

C) Which target group they’re in (e.g., app developers from the PDF targeting)

This data powers super personalized nurturing for users who sign up but don’t activate.

We can run this through two channels: retargeted ads and email nurture.

The retargeting ad campaign would be a two-step LinkedIn sequence targeting users who converted but aren’t using the product:

Step 1: Promote a case study showing how app developers successfully use Stripe for tax collection. (We know they’re app developers from the PDF targeting, and we know they want tax collection from the segmentation question. Perfect match.)

Step 2: Direct conversion ad. They signed up, they engaged with the case study, now hit them with “Use Stripe now” and link to activation steps.

The email nurture campaign would run parallel with triggered emails based on user actions:

• Email 1: Welcome + quick setup guide (show them the fastest path to value)

• Email 2: Use case focused content (deep dive on tax collection for app developers)

• Email 3: Social proof (case study showing success with their exact use case)

• Email 4: Direct conversion push (clear CTA to start using the product)

• …

The combination of retargeting ads and email nurture gives multiple touchpoints to push inactive sign-ups toward activation.

Path C: The Browsers Who Need More Warming

This is for people who clicked the PDF but didn’t convert yet. Maybe they’re still researching. Maybe they got distracted. Either way, no conversion happened.

Here’s the challenge - even with UTM parameters in place, we can’t capture any data until someone actually converts in our system. So how do we move these people forward?

We work with what LinkedIn gives us: people who clicked on the PDF.

That’s our signal that we have relevant, interested prospects.

Here I’d build a 3-layer retargeting campaign based on that PDF click:

Layer 1: Show them a case study about how app developers successfully use Stripe for tax collection. Same ad as in Path B - doesn’t matter if the exact use case matches. You just want to demonstrate someone got real value from the tool.

Layer 2: More social proof or a different angle on the same use case. Keep building credibility.

Layer 3: Direct conversion offer. Test two variations here - “Talk to sales” versus “Sign up for an account.” At this point they clicked the PDF, engaged with two case study ads, so they’re clearly interested → Time to ask for the conversion.

If someone books a call?

Perfect - they go to sales with context. If someone signs up? They get funneled into Path B’s nurturing system because now the segmentation starts and you can activate them if they don’t use the tool.

Final Words

This is how I’d build Stripe’s growth system based on one single LinkedIn ad entry point.

(And this is how I built ours after getting inspired by this ad.)

It’s not magic:

• Non-gated content that actually gets read (90% fewer dropoffs)

• UTM tracking that feeds your CRM with real attribution data

• Segmentation questions that make personalization possible

• Multi-channel nurturing through retargeting ads and email sequences

• Behavioral retargeting based on what people actually do, not hunches

This generates high-quality leads and converts them into calls without losing potential customers to gated PDFs.

PS: If you enjoyed this, please tap the like button below. Thank you! 💛

Today, we’re breaking down the funnel of VEED, one of the most successful video editing startups of the AI era. I came across it recently while searching for a way to create engaging videos, and its growth loop is what caught my attention.

So, let’s jump in.

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Have you ever considered using video in your marketing?

Me too.

But I always struggled with how to edit videos to make them cool and engaging. When I last looked into this topic, I saw that there are now thousands of AI tools that can help.

However, VEED stood out. It’s probably one of the most successful ones: it started as a bare-bones video editor and now generates $40 million in revenue in 2024, up from $15 million in 2023.

So, I thought we could take a closer look at its growth mechanics.

VEED – From Side Project to Eight-Figure SaaS

SEO as a Key Pillar of Its Strategy

VEED started as a side project and relied heavily on SEO from the very beginning.

Today, it attracts about 11.7 million visits per month and is one of the world’s 20 most-visited design tools.

It all started simply, as the founder stated in a Reddit post six years ago.

So they started out with:

• Posting on Quora → which was found through SEO and drove traffic

• Building backlinks through an additional tool → which created trust in the VEED page and helped it rank better

If we dive into its traffic sources today, a Similarweb breakdown shows an unusually balanced traffic mix for a product-led SaaS:

• Organic search delivers 52.94% of desktop sessions, thanks to thousands of highly targeted landing pages (e.g., “compress WebM,” “add subtitles to TikTok”).

• Direct traffic contributes 35.33%, indicating that many people type “veed” directly into the URL bar after encountering the brand elsewhere.

• Social channels round things out—most visibly a YouTube channel with 146,000 subscribers and over 41 million lifetime views, plus 21,700 followers on TikTok, where quick-fire demos double as advertisements.

This indicates that VEED has a strong brand—with over 35% direct traffic—and drives significant traffic through SEO and social media.

Smart here is that they build landingpages for every use case like “add subtitles to TikTok”

Two Minutes to the “Aha” Moment

But how is all that traffic converted? And how do users see the value?

The answer is ruthlessly simple—it takes no longer than two minutes to reach the “aha” moment.

💡 The “aha moment” is the point where a user first experiences the core value of a product—when they go from just trying it to truly understanding it. It's the switch that flips when someone says, “Ohhh… now I see why this is useful.”

It’s not always the first login or feature click; it’s the first moment of realized value.

Start for free, no card required.

Once new visitors land on the site, they can jump straight into the editor from any landing page and are greeted with calls to action like “Get started” and “Start for free.”

The added note—“No credit card required”—helps lower the barrier to entry and encourages users to try the product without commitment.

Once you log in, you land directly inside the tool.

You can upload your video and have plenty of options to optimize it, from auto-generating subtitles to removing noise and improving quality.

This makes beginners feel like pros in less than 120 seconds, which turns out to be the aha moment.

Watermark Loop: Free Advertising Baked into the Product

Once users want to download their video (on the free version), VEED’s product-led growth tactic comes into play.

Every video exported on the free plan is stamped with a discreet “VEED” badge that cannot be removed without a paid subscription.

As many users don’t pay for the tool, they use these clips with the watermark intact. Because creators post them across TikTok, Reels, Shorts, and LinkedIn, the watermark travels with the content.

Viewers who click—or simply remember the short domain—land on VEED, use the free editor, and, in turn, push more branded videos back into the wild. Direct traffic numbers confirm that this loop sustains itself at scale.

How VEED Makes Money

Huge traffic and smart product-led growth aren’t enough. What counts is revenue, and VEED uses multiple streams:

1. Subscriptions
2. Credits

For subscriptions, the cheapest paid tier—Lite, at roughly $9/month—removes the watermark and unlocks 1080p resolution.

Higher-tier plans offer 4K exports, brand kits, language translation, and eye-contact correction. Enterprise pricing includes even more features, which are typically needed by companies using the tool at scale (and it’s interesting that such a tool even offers enterprise packages).

Credits, on the other hand, are used for AI functionality—such as AI avatars—and follow a typical usage-based pricing model.

Loops That Keep Customers—and Bring in New Ones

VEED.io has over 12 million users per month and more than 100,000 paying users. It has grown from a small startup into a global, industry-leading platform by leveraging various growth mechanics.

One of these is the “Invite Your Friends” discount, which incentivizes users to refer others in exchange for benefits, helping to fuel viral growth and expand the user base organically.

Affiliate Program

The affiliate program has no limit. Participants receive a 25% commission on every successful referral for up to 12 months.

Final Words

VEED’s growth loop is a textbook example: long-tail SEO filled the top of the funnel; the watermark turned every user into a micro-advertiser; social video added reach; and AI features increased trial-to-paid conversions and average revenue per user.

VEED’s badge may occupy just a few pixels in the corner of a video, but it’s the engine behind its success.

If your product naturally produces shareability, your next growth breakthrough might be hiding in plain sight—right where your users click “Publish.”

Takeaways

1. Put your brand in the product itself. If users share what they create, find a subtle way to include your logo or name.

2. Show value before asking for money. Let people experience the “wow” moment quickly, and then they'll be more open to upgrading.

3. Stick with what works. Keep your best growth channels running, even as you try new ones.

4. Educate instead of advertising. Tutorials and webinars build trust better than pop-ups or ads.

5. Raise money to grow, not to survive. Being profitable gives you more choices and better deals when fundraising.

PS: If you enjoyed this case study, please tap the like button below. Thank you! 💛

Today, I want to dive into why so many AI startups hit past $1 million ARR at lightning speed. I thought, this cannot be a coincidence, even if they are riding a massive hype wave.

And I was right…

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So, it feels like every week I read another headline like “fastest-growing AI startup” or “from $0 to $1 million ARR in 12 months.”

This makes it seem like AI startups are killing it and that all you need is AI to build the most successful startup ever.

But you probably know as well as I do that this can’t be true.

All the more reason to take a deep dive and look at what makes Lovable, Mistral, and others so successful.

And surprisingly, there is a pattern.

The AI-Startup Pattern

So, when diving into this, I noticed the following pattern that most of these major startups seem to follow:

1. Pain-first discovery

2. Tiny, tool-augmented team

3. Forward-deployed prototyping

4. Community launch & private beta

5. One pain at a time

Let’s have a look.

1. Pain-first discovery

All these exploding tools were built because their founders saw a major pain point or wanted to scratch their own itch.

Most of the AI founders were either second-time founders or had worked in a startup environment - so they knew they couldn’t blindly dive into an idea and start developing it.

Lovable’s founder, Anton Osika, for example, built an early version of Lovable - the open-source GPT-Engineer - while serving as CTO at a startup, to stop his own team from burning hours on boilerplate code. It received 50,000 GitHub stars, so he knew he was onto something.

2. Tiny, tool-augmented team

The era of large startup teams is over. Every AI startup is now built on small, tool-augmented teams.

This means AI startups are leveraging AI tools (lol) to build, scale, and execute faster. This makes the ARR per employee insanely high.

Lovable, for example—even after racing past $20–30M in ARR—the tool employed just 18 people, resulting in over $1M ARR per employee.

3. Forward-deployed prototyping

It seems that these startups never shipped anything that wasn't tested. They embedded their teams directly inside a real customer’s environment (or workflow) to co-build, refine, and validate their AI solutions in real time. And with that, they did the following:

• On-site (or deeply integrated) collaboration: The founders or engineers worked closely with users (often literally sitting with them or sharing their daily tools) so they could see pain points firsthand.

• Rapid, iterative feedback loops: Instead of spending weeks building a polished demo, they put a minimally viable prototype in front of actual users in days - or even hours. They observed how it was used, gathered feedback immediately, and made tweaks on the fly.

• Shared risk and reward: Because they were in the customer’s environment, the customer felt ownership over the solution. They invested time (and sometimes money) earlier, accelerating adoption once the team was ready for a broader rollout.

• Real usage data: They didn’t rely on hypothetical “would-you-use-this?” surveys. They collected metrics on actual behavior - number of queries, time saved, integration issues, etc. - which was far more persuasive to investors and future customers.

4. Community launch & private beta

What you see with almost every AI tool is an online community around it - be it on Slack, a forum on the website, or elsewhere.

Within these communities, users are discussing, sharing feedback and learnings, making it a place where real conversation happens.

In some cases, these communities were built before the tool itself and were used to share a private beta. This allowed the founder to iterate based on feedback at lightning speed, accelerating their forward-deployed prototype approach.

5. One pain at a time

All AI tools started out very narrowly, meaning they focused on solving one high-pain problem before expanding their scope and began mostly vertically, then expanded horizontally.

That is, they started by solving one high-pain use case deeply (e.g., “AI agent for contract due diligence” like Harvey AI did). Once they nailed that niche, they exposed underlying capabilities so users could apply them to adjacent workflows (e.g., “risk flagging across all legal documents” or “generating standardized clauses for templates”).

Another notable trend is ecosystem building.

Almost all of the 202x AI tools use third-party integrations - whether through an official app marketplace or community-driven plugins. The more hooks they expose, the more potential revenue streams they unlock (e.g., revenue-sharing on marketplace extensions).

Examples of the AI Startup Pattern

From Harvey AI to ElevenLabs, many of those startups who seems to skyrocket the past year(s) follow this pattern.

Final Words

It seems, from the outside, that it's enough to ride the AI wave and magically generate millions upon millions in ARR with your AI solution.

But that's wrong.

Behind it, there is a strategy that many are executing well—and, of course, a product that truly solves a pain point accelerates all of this.

However, it seems that, compared to the early startup world, today's startup environment is more mature, has learned from the past, and many founders are doing things right.

PS: If you enjoyed this experiment, please tap the like button and let me know in the comments below. Thank you! 💛

Today, my guest is Nika Kotláriková, Nika is a marketer through and through, and she’s here to share one growth tactic that’s often overlooked. How can your social media benefit from SEO? You’re probably thinking, What do search engines have to do with my socials? But trust me, a lot!

This one’s important, so let’s jump in.

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If you want to get more orders → your website (or social media profile) must have high traffic → you must be the first to appear in search (ideally organically) → and that's what SEO is all about.

This rule works within the web. But what about social networks? How does SEO work there? Today, we will discuss it.

You'll find out why to focus on social media SEO, how it all works and how to proceed, useful tools for social media SEO, and I'll show you a few profiles for inspiration.

This article covers these fundamental topics:

• 🔍 Why do social media SEO?

• 🚀 Steps to improve your “SEO score” on social networks

• ⚙️ Useful tools

• 🌟 Inspirational profiles with good social media SEO

🔍 Why do social media SEO?

Marketers and entrepreneurs spend the vast majority of their time figuring out how to organically rank at the top of web search results and how to stay visible. With AI entering the picture, the only thing gaining more attention is search SEO and AI SEO.

But where else are users frequently present?

Yep – social media.

• 82% of internet users worldwide use social media to research products they‘re interested in buying. (Marketingscoop)

• Social media platforms have become significant sources for news consumption. Predominantly Facebook, YouTube, X and TikTok. (Pew Research)

• Gen Z prefer using social media platforms like TikTok and Instagram for search queries over traditional search engines. (Forbes)

Social shopping – it’s already a $727 billion dollar market according to Grand View Research, and it will reach $6.2 trillion by 2030. Source: Neil Patel – X

🚀 Steps to improve your “SEO score” on social networks

Each social network has its specifics, how it is used and what rules it applies. But most of them use a fairly general formula for social media SEO.

Here are the steps that will help you optimise your profile and make it easier to discover:

• Use keywords in your bio

• Use keywords in your name

• Use keywords in your handle @

• Add alt text to images – this also helps people with visual impairments

• Use hashtags – even though Mosseri said hashtags aren’t a big deal on IG, platforms like YouTube and LinkedIn still rely on them

• Use keywords in your captions

• Use trending music in your posts and try remixing your content with content from bigger creators in your niche

• Add your location to increase discoverability in your region

How does all this affect your visibility?

Your profile will start appearing in the Explore/Search sections of a given social media platform. Your posts will show up under specific keywords (hashtags) on IG (if you used them in your captions, for example). The same applies to Twitter (X) as well.

I included “YouTube” in the post description. When I searched for “YouTube” using the Explore feature on X, my post showed up in the results.

⚙️ Useful tools

For more precise social media SEO, you can use a variety of tools. Here's a list of some of them:

• AnswerThePublic – helps you find questions (topics) people are searching for across platforms

• Brand24 Hashtag Search – allows you to search and analyse hashtags

• Keyword Tool – offers hashtag ideas for Instagram, YouTube, Twitter, Pinterest, and more

• RiteTag by RiteKit – suggests hashtags based on the image you upload

• TikTok Creative Center – great for discovering hashtags, trending sounds, and keyword suggestions based on region and industry for TikTok

Of course, there are many other tools available on the market. But for the purpose of this article, I’ve limited the selection to just these.

🌟 Inspirational profiles with good social media SEO

The best strategy is to fill out your profile as thoroughly and precisely as possible, including as much information as you can – this increases your chances of being discovered by potential clients or buyers.

So, complete as much as you can (even when it comes to published photos, for example, don’t forget alt texts; use clear CTAs in your bio, add relevant links, etc.). I’ve taken the liberty of including a few good examples with a short analysis.

💡 PRO TIP: You can use emojis to visually “highlight” text.

We are at the end.

I hope this episode helped you get a clearer understanding of SEO on social media, and that after applying these steps, you’ll start seeing better results.

If you’re looking for more tips on marketing or business, you can find them in my Substack articles at Business & Marketing with Nika. Don’t forget to subscribe so you don’t miss my newsletter, published every week.

Lastly, I’d like to thank Andreas for the opportunity and for sharing his valuable insights in his newsletter.

Thanks for reading, and see you soon!

PS: If you enjoyed this growth hack, please tap the like button below. Thank you! 💛

And it makes one thing clear: we are slowly stepping into the age where we hire AI before we hire people.

Insane, right?

But with everything we’ve seen over the last few months, probably everyone has thought at some point, “Can AI do my job (better than me)?”

So did I - and that was all the more reason for me to dive deep into the world of AI marketing.

I tested tools, built workflows, and saw just how far I could push marketing on my own. My goal? To run an entire marketing campaign, end to end, using only AI.

And spoiler alert: it’s not only possible, but surprisingly effective.

I’m now brainstorming entire marketing campaigns - from target audience to messaging to ads. I get a full briefing, fully developed organic social posts, fully developed ads with hundreds of visuals to choose from, and a fully developed landing page connected to the backend I want.

And all of this in less than two hours - and done entirely on my own.

Spoiler: those campaigns are similar to what full marketing teams are doing today.

So, with the right tools and the right prompts, you can already solo your marketing.

Let me show you the tools.

1. Brainstorming & Strategy

I kicked things off with Writesonic, which helped me brainstorm an entire campaign from scratch.

From the concept to audience targeting and messaging angles, it basically built the bones of the whole campaign.

Writesonic integrates with keyword tools like Ahrefs, and it has access to a large library of content from platforms like LinkedIn.

This helps identify content gaps and opportunities - things that would usually take hours of manual research (Writesonic even shows you how much time you save - in my case, it was around 75 hours).

In the end, I had:

• A full strategy

• A full ad campaign with all the content ideas

• Ideas and partially created social posts

• An outline for a PDF that can be used for lead campaigns, if I want

It all came down to the right prompt.

But the good thing is: Writesonic helps you create this prompt. With one click on “Improve prompt”, it rewrites your input in a way that you get the best results from the tool.

2. Visuals for Ads & Posts

Next, I was looking to create ad visuals for the campaign, so I hopped over to AdCreative.ai.

I copied and pasted the concept into the tool and provided my brand guidelines. Based on that, it created dozens of different visuals I could choose from.

With one click, you're able to edit and customize them.

What’s cool is that it doesn’t just generate visuals - it also predicts which ones are most likely to convert, based on performance data from similar ads.

That’s nice when you’re A/B testing and don’t want to waste budget on low performers.

3. Copywriting

For all the written content, and to finalize the social posts I turned to the classic: ChatGPT.

Of course, this step still needed a bit of a human touch.

You have to steer the prompts in the right direction, tweak the tone and structure, and inject personality where needed. That’s probably where most of my own creativity came in.

To make sure everything read smoothly (and was grammatically correct—I'm not a native English speaker), I ran it all through a custom GPT I use called “Grammerly.”

It’s my go-to grammar check and proofreading buddy. No more awkward phrasing or missed commas.

4. Landing Page

Once the post, copy, and visuals were ready, I used Lovable.dev to generate a complete landing page - design, structure, and even database integration.

I wanted the page to have a form connected to Airtable. So I prompted it—and in 15 minutes, it was ready to start driving traffic.

If you’re comfortable crafting detailed prompts, you can stick with the free version. You get five free prompts, and if you're detailed enough, that’s often all you need.

What’s Next?

So, after that, I had:

• A full marketing campaign and strategy

• A complete ad campaign with content and visuals

• Fully written social posts

• A landing page with CRM integration

With that as a foundation, I’m now testing:

A) Connecting all the tools together to create an end-to-end workflow that builds the campaign from start to finish without switching between platforms (I’m experimenting with N8N for this).

B) Finding an AI tool that helps me set up ads and manage/optimize budgets across different platforms.

If I can tie all these steps together - ideation, asset creation, landing pages, deployment, and budget optimization - I’ll basically have a full-stack AI marketing engine running on autopilot.

Final Thoughts

It’s wild how much you can get done with just a few tools and the right prompts. It can absolutely help solo marketers, startups, or small teams scale faster and smarter.

I’ll keep you posted as I test more tools and start seeing performance results.

In the meantime, are you already using AI to automate parts of your growth? Drop me a comment - I'd love to hear what tools you’re playing with.

PS: If you enjoyed this newsletter, please tap the like button below. Thank you! 💛

Today, we’re breaking down the funnel of Stripe - a company you’re probably already familiar with. It’s been on my list for a while, but I stumbled across it again “by accident” last week, and figured it was time.

So, let’s jump in.

I recently purchased a tool I wanted to use.

Down below on the checkout page, I saw this:

And I thought, that's a cool way of free marketing. So my next thought was, 'Hey, Stripe would be interesting for a breakdown.'

And here we are.

But diving deeper into its marketing and channels, I found out that Stripe originally started by focusing on developers as their main target group. This slightly shifted over the years, but developers still play a major role for Stripe.

Targeting developers as the audience for a payment solution didn’t make much sense to me at first. But on second thought, it does - because they’re the ones who have to work with it and implement it.

And this helped Stripe reach a valuation of $91.5 billion today and generate multi-billions in revenue.

Let’s break it down.

Stripe’s Multi-Billion Dollar Funnel

How Stripe Drives Awareness

When we talk about organic channels, Stripe is mainly active on LinkedIn, Twitter, and Meta (though the Meta account is inactive and primarily used for ads). And also leverages SEO.

Unlike other companies, there is no fully developed strategy for TikTok or Instagram (yet).

On its channels, Stripe addresses different types of content and target groups - for example, on LinkedIn, where the company promotes a lot of features:

Or so on Twitter:

But here, it gets more interesting.

In addition to their main account, we also find a “Stripe Developers” account.

Here, you’ll find more technical content that speaks directly to developers themselves.

And this makes a lot of sense because Twitter’s audience has a lot of tech people and developers.

On Instagram and TikTok, they’ve adapted to the nature of the platforms.

It seems like they started some kind of podcast or videocast format, using Reels and TikTok videos featuring speakers from their events. However, this content isn’t posted consistently and only appears from time to time.

But what’s more interesting is Stripe’s integration of its service. And this is how I came across the tool (again).

Every shop, platform, tool, or service that uses Stripe includes a “Powered by Stripe” label on the checkout page, which is essentially free marketing.

With each click, users are taken to the Stripe website.

All of this drives a lot of traffic, specifically, 4.5 million clicks each month, almost entirely from organic content.

Of course, this needs to be captured somewhere.

How Stripe Captures Demand on Its Website

When we look at Stripe as a solution, it's quite complex.

The tool combines a payment solution with many different use cases and unites several smaller products under one platform.

Visualized, it looks like this:

So, what’s a good way to promote a tool like this?

Looking at the website, we see that Stripe smartly handles this.

Feature-driven:

Under the navigation bar, there's a “Products” tab. Here we see all features listed under different solutions, all unified within the tool itself.

With a click on each feature, we’re directed to a landing page where each one is promoted individually.

Use Case-Driven

Under the “Solutions” tab on the website’s navigation, we find a section that is structured by customer stage, business model, and use cases.

With a click on the links, we’re guided to a landing page, and each one is tailored to a specific use case.

💡 Users always come to your website with different perspectives and varying levels of knowledge. While the general rule of thumb is to build your marketing for the dumbest customer, Stripe handles this in a smart way.

In their case:

A) A user arrives while looking for a specific feature to solve a particular problem.

B) A user arrives while searching for a use case tailored to their company size, stage, or industry.

This is a great way to capture organic traffic and redirect users to use cases most relevant to their initial situation.

So, but what about the funnel(s)?

Stripe’s Paid Ad Funnels

This is where Stripe begins to drive targeted leads into its solution.

Looking at the channels, we see two funnels in place - one targeting startups and one targeting enterprises.

In other breakdowns in this newsletter, we’ve seen companies build only paid funnels for enterprise customers, while Stripe also targets startups, which, in my opinion, makes a lot of sense.

A payment platform has a strong anchoring effect. Once a startup implements it and grows with it, the chances of switching later are very low, not like other tools that mainly make (big) money with enterprise customers.

Startup Funnel

Starting at the top, Stripe has a layer of awareness-building content and ads.

Creating Demand

Stripe starts by educating users on startup-related topics and providing helpful resources on how they can improve their business.

On LinkedIn, we therefore see a lot of ads targeting problem-unaware startup audiences with educational material that doesn’t primarily focus on Stripe’s solution but rather on topics every startup deals with.

The same goes for Meta:

These ads don’t lead to typical landing pages or leadgen forms like we’ve seen in other breakdowns. What Stripe does instead is direct users to PDFs that are not gated, without putting in their data.

These PDFs break down startup tactics and growth stories.

Each PDF includes a section about Stripe, highlighting different solutions tailored to startups, with a call to action at the end.

And Stripe highlights features that are specifically relevant for startups.

Capturing Demand

What they appear to do next (at least how it looks from the outside) is build their retargeting around case studies of startups successfully using Stripe.

Like this ad:

Here, they use the same format (a click on the ad leads to a PDF that explains the case study and includes a call to action at the end).

This means that first, users are presented with a PDF on general startup topics (where they become familiar with Stripe). Then, they see a case study showing how startups succeed with Stripe. Finally, there’s usually a third retargeting layer that aims for a direct call to action, such as “Test our solution.”

However, that final step isn’t something I see on LinkedIn - but it’s a tactic Stripe uses on Meta. Here you’ll find ads that promote a clear call to action.

These likely also function as part of a retargeting layer. Therefore, they feature popular startups, highlight their growth, and lead users directly to a landing page.

So, the ad funnel seems somewhat complex.

We have cold-layer ads (targeting leads not familiar with Stripe) running on both LinkedIn and Meta. Then there are retargeting ads aimed at warmer leads, using case studies — also on Meta and LinkedIn.

Additionally, we see Meta ads used specifically for retargeting that drive leads to a landing page with the goal of conversion. And finally, we have Google ads that lead directly to landing pages, aiming for conversion.

Which is totally possible, as you can combine LinkedIn and Meta for smart retargeting (but it still left me wondering).

But where do the startups land?

The landing page that most of the startup-focused ads lead to speaks directly to the target audience. However, instead of promoting specific startup solutions, it emphasizes the DIY mentality of startups (aka also speaks to developers).

Next to a strong headline that emphasizes growth, they highlight relevant benefits and features, and build trust by showcasing well-known brands that use Stripe.

Further down on the landing page, Stripe continues to reinforce the DIY startup mindset by emphasizing the ease of using their solution.

And speaking directly to developers.

But also to founders in general (or for sure also to technical co-founders).

At the end, they close with a call to action and highlight their strongest features.

Leading startups either directly to account creation…

… or funnel them in a sales call.

This makes the startup funnel look like this:

Enterprise Funnel

What Stripe is doing on the enterprise side is quite similar to what they’re doing on the startup side - but with different messaging and formats, of course.

Creating Demand

On LinkedIn, it appears they’re investing more in ads here, as there are clear retargeting funnels in place.

In general, they’re also using ungated PDFs to educate users on various topics, tailored to enterprise matters like tax and compliance.

With retargeting ads in place.

This leads to Stripe’s enterprise landing page, which starts with a strong headline and highlights well-known customers to build trust right away.

Promoting features that are relevant for enterprises.

Always building trust by showcasing logos on the site.

Leading users to more resources in case they’re not ready to convert.

And ending with a call to action to contact sales, which is different from the approach used for startups and individual users.

This makes the enterprise funnel look like this - a straightforward path from cold targeting to conversion on LinkedIn. And only on LinkedIn.

(Of course, a funnel is never truly straightforward, as leads rarely follow the exact path you design for them - but that’s how it’s structured.)

After Conversion & Paying Customers

Once someone decides to move forward with Stripe, it becomes clear again how much Stripe prioritizes developers.

The website offers detailed guides and step-by-step instructions on how to build solutions using Stripe.

There’s an entire support center to help you with the setup.

This way they reduce confusion and help the probably most overlooked stakeholder in a company, a user-friendly way to work with the solution.

One other thing worth highlighting is Stripe’s retention, and this is based on my own opinion. I believe Stripe’s retention rate is very high. We're talking about a payment solution that you don’t just implement and abandon the next day if you’re not satisfied.

Once a company decides to implement Stripe and run all payments through it, they’re likely to stick with it for a long time, which gives Stripe a strong lock-in effect.

Also, Stripe’s pricing model isn’t based on a monthly fee but on transaction fees. So, when you earn money, Stripe earns money too.

Last words

Stripe shows how powerful it can be to build for the overlooked, communicate clearly across user levels, and turn your product into its own marketing channel. From developer-first positioning to ungated content and smart retargeting, Stripe’s funnel shows how to attract, educate, and convert.

And there are some golden takeaways here that can truly accelerate growth.

Takeaways

• Who is your audience?
  Stripe didn’t start (and still doesn’t fully focus) with the obvious customer group. They began by targeting an underserved audience - developers - and made their solution easy to use while speaking directly to them. So, who is your underserved target audience?

• What level is your user coming from?
  Stripe handles this well on their website. They capture users at different stages by providing information based on features, use cases, or company size. It’s a great example of how to speak effectively to your customers.

• Can you implement free marketing?
  If you offer a solution that gets implemented or used by others, like Stripe, think about how you can turn that into free marketing. Stripe does this by placing their logo on every checkout page.

See you next week! 👋🏼

PS: If you enjoyed this case study, please tap the like button below. Thank you! 💛

Today, we’re diving into a startup with probably the most impressive growth journey we’ve covered so far—one that even outperformed OpenAI’s explosive rise.

So, let’s jump in.

If you're interested in startup growth and have kept your eyes open over the past few months, you've probably seen this graphic:

This shows the impressive growth numbers of several popular SaaS startups - all in comparison to the tool we're covering here:

Cursor.

Cursor is a code editor with built-in AI features, like an AI chat. You know, those (for us non-techies) weird-looking control centers where you type in lines of code and - magically - a full product comes out.

That means, with Cursor, developers now have an AI sparring partner - one they can ask questions while coding, that helps find bugs and assists in coding at light speed.

But not only does this sound fascinating (at least to me), but what's even more fascinating is that the startup is hitting $100M ARR in just 12 months. IN. JUST. 12. MONTHS.

With zero marketing budget.

That alone is reason enough to break it down. But while many articles only scratched the surface of its growth story - and left me unsatisfied after reading - I had to take a closer look myself.

So, ladies and gentlemen, buckle up — we’re diving deep.

Cursor’s Explosive Growth

The Engineer of the Future

In 2022, an “applied research lab” called Anysphere came into existence. As it describes itself, it is “working on automating coding.”

Its ultimate goal is “to build the engineer of the future: a human-AI programmer that's an order of magnitude more effective than any one programmer.”

The team's first step in this direction was the launch of the AI startup Cursor - co-founded in 2022 by four gentlemen: Michael Truell, Sualeh Asif, Arvid Lunnemark, and Aman Sanger, all of whom were students at MIT at the time.

This alone gave the team some credibility in the space.

When we look at the story of Cursor, it’s a straightforward “we’re doing things better” kind of success story.

In an episode of Lex Fridman’s podcast, the Cursor founders talked about how they had used GitHub Copilot for several projects. Copilot is GitHub’s AI-powered code editor that helps speed up development.

But when the Cursor founders first heard about the ChatGPT-4 model back in 2020, they decided to step in and take things to the next level.

One founder in particular I want to highlight - who played a major role in Cursor’s growth story - is Aman Sanger.

More specifically, his tweets were a catalyst for Cursor’s early success.

How to Build Momentum with Twitter for a Product Launch

Aman had been posting consistently over the past couple of years.

Then in November 2022, one of his tweets took off. He shared some proof about how well AI coding tools were working - which is exactly what Cursor is all about. That tweet kicked off the momentum build-up until the launch of Cursor.

Over the following weeks and months, he continued posting consistently about these topics - sharing his thoughts on AI coding and AI models.

This served both to build momentum ahead of Cursor’s official announcement and, it seems, to test the very hypotheses the team would later pursue with Cursor.

More and more of Aman’s tweets started to resonate with the audience, helping him build a strong voice in the AI coding space.

Until he finally announced the launch of Cursor with a video snippet showing how it can be used to fix bugs, develop features, and use an AI chat to ask questions about your codebase - a post that went viral with his newly built audience.

With a ton of engagement, retweets, and comments - including Notion’s founder, Ivan Zhao, asking if he could test it at Notion - Aman ended the post with a subtle call to action, hinting at a waitlist. In the comments, people were actively asking to try the tool.

This moment marked the beginning of Cursor’s growth.

💡 That’s a very valid strategy for testing hypotheses for your startup. Once you’ve built a (small) audience, start posting about the problems or hypotheses you’re trying to solve with your product or startup.

Based on the engagement and comments, you can get an indication of whether it resonates or not.

Cursor’s landing page was simple.

It featured a header, a value proposition, and a field to enter your email address to join the waitlist.

In the top right corner, there was a tweet linked with the call to action: “Read the announcement.”

Unfortunately, I couldn’t find details on how the waitlist signups went. But judging by the engagement numbers on Twitter and the comments, I assume it was pretty successful.

Three months later, they publicly launched their beta - announcing a partnership with OpenAI, early access to GPT-4, and further improvements to the tool. That likely led to a significant increase in signups.

How Cursor Got User Input to Iterate

Unlike other startups we’ve covered here, like Linear, Cursor didn’t build a closed community on platforms like Slack for discussions and feedback - instead, they built a simple forum.

They regularly updated their users on changes and gave them the opportunity to provide feedback.

Looking at the oldest entries, the forum dates back to August 2023 - a couple of months after the launch. It’s clear that people were engaging, actively using the product, and sharing feedback that Cursor could iterate on. Which made the forum an integral part of the tools’ product development.

💡 If you launch a product, create a way for people to provide feedback and for you to update them quickly.

This doesn’t necessarily have to be a community, but it’s one of the easiest and most effective ways to stay close to your target audience. Of course, you need to be active and keep them updated regularly.

And the way Cursor is doing it is a prime example of engaging with their target audience and actively listening to feedback - even updating them beyond the forum.

From Developer Hype to Real Traction

At some point, Cursor started spreading like wildfire among developers. Whether it was on Twitter, Reddit, or niche dev communities, people were talking about it.

There were a few clear reasons behind this momentum:

1. The Product
Cursor delivers real value to its target audience. It improves on existing solutions and solves real developer pain points. When a product truly helps, people naturally talk about it - and that’s exactly what happened.

2. The Focus
Unlike traditional SaaS companies that rely on top-down enterprise sales, Cursor took a developer-first, bottom-up approach. It let individual developers try it out, fall in love with the tool, and eventually bring it into their teams. This kind of adoption feels organic, works quickly, and is far more cost-effective than traditional sales methods.

3. The Freemium Model
Cursor offers 2,000 free AI code completions per month. That’s enough for developers to really understand the value without committing upfront. Once they see what it can do, many naturally upgrade to paid plans. This approach allowed Cursor to grow steadily from the ground up.

Thanks to this strategy, they managed to attract developers from companies like OpenAI, Midjourney, Perplexity, and Shopify. And they used those names smartly in their marketing, which helped boost awareness even more.

And of course, having world-class investors doesn’t hurt either.

Cursor raised $8 million in seed funding led by OpenAI’s Startup Fund, with participation from GitHub’s former CEO Nat Friedman, Dropbox co-founder Arash Ferdowsi, and other top-tier angels.

But the momentum didn’t stop there.

In 2024 and 2025, Cursor went on to raise both Series A and B rounds, with Andreessen Horowitz joining in.

And they put it best:

“Cursor, distinctly among AI coding tools, has simply gotten it right... Users give glowing reviews, many have started to pay, and they rarely switch back to other IDEs. Most of the a16z Infra team have also become avid Cursor users!

This early success is due to the clear vision and relentless execution from Michael Truell, Aman Sanger, Sualeh Asif, Arvid Lunnemark, and the rest of the Cursor team. They are obsessed with the problem of better AI coding, and they are laser-focused on building a great developer experience. ”

All of this?

Achieved with zero marketing budget.

Now, Cursor is starting to shift focus toward scaling into the enterprise world - and building the team to do it.

Final Thoughts

Cursor is a great example of explosive growth - and of hitting a real, widespread need. At its core, though, it's a simple story: take something that exists (like GitHub Copilot), do it better, and aim it at the right people.

That’s what led to its virality, big-name backing, and now - according to various sources - Cursor is reportedly in talks to raise hundreds of millions at a valuation nearing $10 billion.

You might be thinking: “Sure, but Cursor had famous investors. That’s not something I can replicate.”

Wrong.

There’s a lot here that you can take and apply:

Takeaways

• Validate your problem on social media
  Cursor’s founder used platforms like Twitter to test ideas, share progress, and confirm there was real demand. You can do the same - fast, free, and direct.

• Create a space for feedback
  Cursor used a simple forum. You don’t need anything fancy - just give users a place to talk, and listen closely. Then iterate based on what you hear.

• Don’t go after the biggest fish first
  Instead of targeting enterprises, Cursor focused on individual developers. Once they loved it, they brought it into their teams. Bottom-up growth > traditional sales.

See you next week! 👋🏼

PS: If you enjoyed this case study, please tap the like button below. Thank you! 💛

Today, we’re covering Canva - a tool that probably needs no introduction. But someone who definitely does deserve an introduction is my friend , whom I brought on board for this issue.

On her Substack, she analyzes website and app design through the lens of neuroscience and psychology. You should definitely check out her content - it’s AWESOME.

Now let’s jump in.

Subscribe now

In 2024, Canva reached 180 million users globally. With 16 million premium users, it generated $2 billion in revenue, making it a heavyweight in the SaaS space.

All the more reason to take a closer look at how Canva’s growth and sales funnels work.

Quick Note

A classical sales funnel does not reflect how marketing and sales work. You cannot strictly separate content and channels that solely drive awareness from those responsible for conversions. However, for the purpose of this analysis, it is easier to break it down this way.

What a $2B Sales Funnel Looks Like

Canva is doing a lot in terms of sales and marketing.

No wonder - it's a widely used tool with a diverse target audience.

Looking at the website alone, we can identify several main target groups:

• Students, teachers, & Universities

• Single users

• Teams & enterprises

But when navigating this jungle of activities, one thing stands out:

Canva follows a smart segmented marketing approach.

Instead of promoting Canva as a whole, they tailor their marketing to each target group.

This makes the sales funnel look like this (link to the full breakdown at the end).

Let’s dive in.

How Canva Drives Awareness

Like every major tool with millions in funding and significant media buzz, Canva is in the fortunate position of not having to educate people about the tool.

It is mainly done by others:

And this opens up a whole new playing field for Canvas's own content.

Which looks like this:

Instead of educating their audience about what the tool is doing, they focus on content for people who are already aware of the tool.

For example, on LinkedIn. Providing tips on how to use the tool:

But also playing with some memes - making fun of its target audience’s clichés:

The Same goes for X & Instagram:

While on X they are also trying some creative things - but unfortunately the crowd is dead:

And on Facebook.

But here’s something interesting.

Canva uses country-specific pages, at least for German- and English-speaking countries.

This allows them to reach a much broader audience.

The content here is mainly reels, but the topics remain the same - insights about the tool, engaging posts like riddles, and product updates.

What I really like is Canva’s Pinterest strategy - and, of course, it’s a design tool, so it’s predestined to reach an audience there.

But Canva showcases creative designs from the community, inspiring ideas, and target-audience-specific design drafts created with the tool itself here.

On YouTube, Canva is building a whole library of tips, tutorials, and how-tos - which have gained a lot of views.

And even when covering topics like "Hierarchy in Design" or "Create Videos with Photos," it's always done in Canva - sneakily connecting the content to the tool.

💡 Btw. this is a smart approach for your content strategy.

When creating content, think about how you can help your audience achieve a specific goal or solve a problem—just like Canva does with "Create videos with photos in minutes." Then, record a video demonstrating how to solve the problem using your tool.

Of course, this won’t work for every tool, but if it works for your tool it is a smart strategy to acquire users

But what stands out is Canva’s SEO strategy.

As I mentioned at the beginning, others are taking care of educating people about what Canva is.

So, Canva focuses on ranking its use cases and features in Google.

By using keywords like "website builder" or “custom business cards” Canva drives a HUGE

amount of traffic to its site.

With thousands of visits a month.

All of this helps Canva drive 191.5 million organic visits to its site, ranking for nearly 15 million keywords - which is insane!

And of course, with all this traffic, Canva’s website is optimized for conversion rates down to the last detail.

💡 When you start with SEO, you’ll probably come across expert advice like: “You have to find keywords for content that solves problems for your target group.” For example, if you run a product studio, this could mean writing articles such as “How to build an MVP?”

I agree with the idea that content should solve problems for your target group.

However, ranking for generic things like “How to build an MPV” won’t help you rank on Google anymore (in most cases). Search is saturated with this type of awareness-creating, top-of-the-funnel content. Marketers have been following this approach for years.

Nowadays, you should focus your SEO content around your product and create awareness through social media. That way, when someone Googles your product or product category, you’ll be the top result. This could include articles like “[Your Product] vs. [Your Competitor’s Product]” or “How to do X with [Your Product]”, and so on.

How Canva Converts Traffic on Its Website

Canva’s Homepage

Most of the traffic lands on Canva’s homepage first, which is well-optimized for lead generation.

To have a look at it, I’ll hand it over to to analyze it from a neuromarketing point of view:

Canva’s homepage is as perfect as it gets. Check out this detailed breakdown here.

Here are the top things I want to cover about Canva’s landing page:

• Visual perfection

• Simplicity and Cognitive Ease

• Emotional Connection

• Built for Businesses

1. Visual Perfection

At a glance, the design is modern, clean, and consistent. They follow all the principles of visual hierarchy.

Even looking deeper, it is evident that Canva has dotted their i's and crossed their t's:

• Structured grid system for balance and proportionality

• Whitespace keeps things uncluttered and easy to navigate.

• CTAs stand out with strategic placement, white space, and subtle micro-interactions.

• Fonts are modern and readable, with no inconsistencies.

• Icons and images are high quality, with clean placement and no visual clutter.

• Perfect spacing and alignment, so nothing feels cramped or awkward.

2. Simplicity and Cognitive Ease

Do we understand what Canva is?

Their headline is:

What will you design today?

They are letting us know that whatever we want to design, they got us covered.

To be more clear, they go ahead and visually list all the use cases. This helps us see exactly how we can use Canva in our own work.

🌀 But could they improve the heading?

“What are you designing”

It’s open-ended and inviting, but could it be clearer? A bit more specific, something like “A tool to design anything and everything”

Maybe Canva is so well-known that they don’t feel the need to explain what they do. But for new users, a little more clarity might help.

Is Canva’s Homepage Easy to Scan? Is it simple to go through?

A study by NNGroup shows that people don’t read websites, they scan them instead.(In a study, 79% skimmed new pages, while only 16% read word-for-word.)

Canva gets this. Their homepage is built for quick scanning. Their homepage is optimized for scrolling and quick scanning of the text. How do they actually implement it?

• Layout uses grids for clear structure which makes content easy to follow.

• Follows an F-shaped pattern, and places key information where people naturally look

Also, Canva keeps text minimal and relies on visuals to communicate—the classic ‘show, not tell approach’. This is related to the Picture Superiority Effect, where people remember images better than words.

Is the Cognitive Load High or Low?

It’s low—and that’s a good thing.

3. Emotion Connection

Purple isn’t just a random choice for Canva—it’s strategic. In color psychology, purple represents creativity, ambition, and positivity, which fits perfectly with Canva’s brand. Their shade of purple even has a hint of blue, adding a touch of trust and reliability while still feeling fun and approachable.

Their copy is casual and inviting:

• “Templates for absolutely anything” (Casual)

• “What will you design today?” (Conversational)

• “We’re full of surprises”. (Curiosity)

Together, the color and tone make Canva feel fun, creative, and reliable.

Overall, Canva doesn’t feel cold or corporate—it has a personality.

4. Built for Businesses

Yeah, Canva is a design tool for everyone. But their landing page makes it clear—they mean business. The homepage speaks directly to businesses.

Why?

• Pricing is very B2B-centric, they have tailored options for

  • Canva Pro: Solopreneurs/freelancers

  • Teams: Medium to small companies, startups

  • Entreprise: Big corporations

• Social proof highlights large companies across different industries, not individual creators or freelancers.

• Testimonials are framed as ‘Business Wins with Canva’, reinforcing its value for companies.

• A dedicated section—“Plans that get down to business”—makes it clear that Canva is a serious tool for professionals.

Even Educational institutions aren’t on the main page—they have a separate pricing section, reinforcing that the landing page is business-first.

This isn’t just about targeting businesses; it’s about earning their trust. Canva positions itself as a reliable, scalable tool for teams, startups, and enterprises that need high-quality design at scale.

Overall, Canva’s landing page is smartly designed—clean, scannable, and easy to navigate. Every detail, from layout to copy, keeps things simple while reinforcing trust.

Canva’s Landingpages

here again - If someone arrives from the mentioned Google rankings, they won’t land on the homepage. Instead, they’ll be directed to landing pages tailored to specific features and use cases.

Like this one for the “website builder" keyword:

Or the one for the video editor:

All of these pages follow the same structure (full breakdown at the end of the article):

• Header with a value proposition

• Logo wall to build trust

• Examples of things created with Canva

• Features & benefits overview

• Explanation of how it works

• FAQs to answer important questions

• 6 to 9 call-to-action buttons guiding users to the free version of the tool

But what Canva does here is super cool.

For some use cases, like video creation, Canva lets users jump straight into the tool - without requiring them to sign up first.

The user can upload a video and fully edit it. But as soon as they want to use or save it, Canva prompts them to sign up.

At that point, they’ve already put in the effort of making the video —which means it is much more likely that they’ll complete the sign-up process.

On other landing pages, however, Canva forces users to create an account before they can use the tool at all.

This feels like a missed opportunity, and I don’t understand the inconsistency. As mentioned, when someone puts in the effort to edit an image, video, or anything else in the tool before creating an account, they are more likely to sign up after.

Meanwhile, the rest of the site is also very well optimized - as states on the Navigation bar:

The navigation bar is clean, simple, and easy to use. It follows best practices with a minimalist design and plenty of whitespace. Nothing feels cluttered.

It keeps things simple with just five main options, following Miller’s Law (people can only remember about 5 to 7 things at once before feeling overwhelmed) —so you’re not overwhelmed with too much at once.

It also hides extra options until you hover, keeping the interface sleek while still offering depth when needed. Each section is carefully structured for quick scanning and familiarity.

This is what shows up when you click on “Design Spotlight”:

Overall, everything feels smooth, simple, and effortless to navigate.

So, to sum it up, with all of this—and 190 million monthly visitors—Canva seems to be doing pretty well in terms of conversion.

But how do they drive targeted demand to create revenue?

How Canva Creates Targeted Demand

: While the website captures organic traffic - seemingly driven by a broad multi-channel strategy - the more strategic and targeted approach happens one level deeper.

A look at Canva’s pricing page shows that it divides its pricing packages into sections for free users, solo users, and smaller teams & organizations. Another tab links to dedicated pages for schools & universities.

But when it comes to creating targeted demand, schools & universities are approached almost identically to enterprises.

This means we have these different target groups to look at:

• Free/Solo users

• Smaller Teams

• Enterprise/Schools Universities
  

How Canva Targets Free & Solo Users

There is no explicit strategy for how Canva targets free and paying solo users, as they are not the primary revenue-generating group.

Therefore, free and solo users are mainly acquired in two ways:

• Organic content (which is free for Canva and includes social media, SEO, and media buzz)

• Google Ads (though these are also used to target teams and organizations)

For the latter, Canva also promotes these use cases and features with targeted keywords on Google Ads.

By clicking on it, you land on the same landing pages we discussed earlier - where users are led straight into the tool.

How Canva Targets Smaller Teams

This one is more interesting.

Even though the line between targeting solo users and teams is somewhat blurry.

From what I’ve seen, Canvas ads for teams include:

• Google Ads – The same as those for solo users, capturing members of smaller teams as well.

• LinkedIn Ads – Showcasing product features useful for smaller teams without specialized roles, such as video editing.

• Meta Ads – Follows the same concept as LinkedIn Ads.

With Canva’s “team” strategy it is highlighting use cases that are essential for smaller teams without specialized graphic design roles.

Once you reach the landing page, the goal remains the same: convert users to the freemium version.

How Canva Targets Enterprise & Campus Users

This happens through a mix of Google and LinkedIn ads.

For enterprises, Canva uses LinkedIn ads to promote a webinar series featuring well-known companies and their executives. The goal is to educate other organizations on how to use Canva more efficiently.

This leads to a landing page with a content library where you can explore these webinar series.

Once you land on the page, it appears that Canva has retargeting in place via LinkedIn Ads and the Google Display Network.

These ads lead directly to another landing page.

Unlike ads not targeted toward enterprises, the call to action here directs users to contact sales. This makes sense because enterprise packages are much more expensive, and the decision-making process involves convincing an entire buying center, making it more complex.

And with sales calls & personal contact Canva has a better chance to convert those customers.

For campuses and universities, Canva relies solely on LinkedIn Ads.

These ads also lead to a landing page with the same goal: contact sales.

💡 Speaking from my own experience, we have tested Google Ads and LinkedIn Ads extensively in the past. The best results we achieved were with an ad spend of around $3,500–$4,000, generating 200+ qualified leads per month at a cost per lead (CPL) of $18.

I would use these two channels in combination:

• Google Ads, targeting high-intent keywords (i.e., keywords that indicate the user is ready to make a purchase) → Leading to a landing page that educates visitors about the offer and provides a conversion opportunity.

• LinkedIn Ads → Retargeting landing page visitors by offering additional education and a conversion opportunity, or directly aiming for a conversion (to be tested).

Example: Canva

• Google Ads targets the keyword “business card creator” (since users searching for this term likely want to create a business card). When they click the ad, they land on a page that explains what Canva does - but they don’t sign up yet.

• LinkedIn Ads then retarget these landing page visitors with an ad related to the business card creator. The ad might say, “Sign up to create your business card.” Since the visitor has already engaged with the content and knows about the business card creator, they see the ad again and are more likely to sign up.

Google Ads generate awareness, while conversions happen on LinkedIn.

Where the Money Is Made - The Pricing Page

Handing over to to have a look at how Canva makes money:

Canva’s revenue comes from two main strategies - upselling and selling to businesses.

• Upselling – This happens when free users, like solopreneurs and non-business users, realize the value of Canva and upgrade to a paid plan. They start for free, see how useful it is, and decide it’s worth paying for.

• Selling to businesses – Canva has tailored its landing page and pricing structure to appeal to companies. Everything is optimized to show businesses why Canva is a must-have tool for teams, making it easy for them to sign up and scale their usage.

We’ve already talked about how well-optimized Canva’s landing page is - now, let’s take a closer look at the pricing page. Let’s dive in.

Breakdown of the Pricing Page

Canva’s pricing page is designed to guide users toward deciding with minimal friction.

Here are the neuromarketing principles Canva uses:

• Visual Hierarchy & Color Psychology

• Smart Defaults & Status Quo Bias

• Anchoring & Price Framing

• Loss Aversion

• Social Proof

• Progressive Disclosure

• Halo Effect

• Building Brand Loyalty at an Early Age
  

1. Visual Hierarchy and Color psychology

The page is structured to be easy to scan and process, making decision-making feel effortless.

• Strong Visual Hierarchy – Key details (plan names, prices, and benefits) stand out, making comparisons simple.

• Color Psychology – The free plan is gray, while paid plans use Canva’s signature purple, subtly reinforcing value and importance.

2. Smart Defaults & Status Quo Bias

Canva doesn’t wait for users to explore pricing—they guide them toward the most valuable option from the start.

• The Business Pricing tab is the default, directing users toward high-value plans.

• Yearly plans are preselected with a prompt to "Save 16%," leveraging default bias to encourage long-term commitment.

Most people stick with what’s already chosen for them. Canva leverages this instinct effortlessly, nudging users toward higher spending without resistance.

3. Price Framing

Canva doesn’t just show you prices—they frame them strategically to make the higher-tier plans look like the smarter choice.

At first glance, Canva Teams seems like the better deal:

• Pro: €110/year per person

• Teams: €90/year per person

But is it actually cheaper? Not really. Canva Teams requires at least 3 people, which means the minimum cost is €270 per year.

By framing Teams as a "cheaper per person" option, Canva makes it feel like a better value—even though the total cost is higher.

It’s a textbook example of price framing—shifting focus from total cost to perceived savings.

4. Loss aversion

Canva taps into loss aversion—the idea that people are more motivated to avoid losing something than to gain something new.

Free Trial Strategy – By offering a risk-free trial, Canva removes hesitation. Users get access to premium features, making it harder to go back to the free version.

"Everything in Free, plus…" Strategy – This upgrade path makes it easy to see what users would lose if they don’t upgrade. Higher tiers clearly offer more value, reinforcing that sticking with a lower plan means missing out.

5. Social Proof: Building Trust and Reducing Uncertainty

Canva uses social proof to reassure users and make decision-making easier.

• FAQs anticipate concerns – By answering common questions upfront, Canva removes hesitation and builds confidence.

• Trust through numbers – Highlighting that 6 million teams use Canva reinforces its credibility.

• Logos from well-known companies – Seeing trusted brands using Canva makes new users feel more comfortable signing up.

6. Progressive Disclosure through Separation of Business and education page

Instead of overwhelming users with all information at once, separate tabs for Education and Business Pricing help users find what’s relevant without clutter.

Each pricing page is tailored to its audience:

Canva keeps things clear and clutter-free, making sure every user gets the info they need without distractions.

7. Halo Effect

Because Canva is free for Teachers, Schools and Districts, it feels like more than just a business—it comes across as a brand that truly supports learning and creativity.

This builds trust and goodwill, making people see Canva in a positive light. And because of this, Users are more likely to trust and prefer Canva over competitors, even in non-educational contexts.

8. Building Brand Loyalty at an early age

When students learn and create with Canva from a young age, they become comfortable with the tool. they’re more likely to prefer and advocate for Canva when choosing a tool for work/business.

What they can improve?

The Overwhelming Feature Comparison While most of the page is optimized for ease, the feature comparison chart is visually overwhelming and adds unnecessary complexity.

There are just too many features crammed into the comparison table—90+ across 10 tabs. Instead of making things clearer, it creates cognitive overload, making it harder for users to spot what really matters.

The endless checkmarks don’t help either. The repetition makes it feel overwhelming, and the real differences between plans get lost in the noise. Also the thing is that most of the features in the last 3 plans are similar. The biggest difference comes down to company size and number of teams, but the way it’s presented makes it seem way more complicated than it actually is.

So how can they improve it?

Instead of listing every single feature, Canva could focus on what businesses actually care about:

• Pro: For solopreneurs and small teams who need advanced design tools.

• Teams: For growing businesses that need collaboration tools.

• Enterprise: For large organizations that need security, brand control, and large-scale collaboration.

Overall, Canva’s pricing page is designed to convert users efficiently, but simplifying the feature comparison could make it even more user-friendly.

Upselling From Within the Tool

When you start using Canva's free trial, the upselling begins—smooth and its almost unnoticeable. This is how:

1. Freemium Model

Canva’s freemium model is designed to get you hooked on the free version, letting you explore and create without restrictions at first. The catch? As you invest time and effort into your designs, you start encountering premium features that make everything easier.

By the time you realize you need those Pro tools, you’re already committed. And that’s exactly the point—once you're in, upgrading feels like the natural next step.

2. You get to see exactly what you miss if you don’t go for Canva Premium.

Canva doesn’t block premium features completely—they just tease you with them. You’ll see Pro templates, fonts, and AI tools sitting right there, but they’re grayed out or watermarked. Just enough to make you want them. You get to see exactly what you miss if you don’t go for Canva Premium.

You can even try using them, but when you go to download, that paywall pops up. By then, you’re already invested in your design, and upgrading feels like the only way to get what you truly want.

3. Right nudge at the right time

Canva knows the perfect time to ask you to upgrade - right when you need it most.

You’re in the middle of designing, you click on a Pro feature, and boom—a pop-up appears, reminding you what you're missing.

Overall, think that Canva doesn’t push you to upgrade - it makes you want to upgrade. By letting you explore for free, teasing premium features, and showing you exactly what you’re missing, they create a natural pull toward Pro.

After Sales: How to Keep Users Around

taking over, coming to the end of the funnel:

Canva uses a variety of strategies to keep users engaged and encourage frequent use of the tool— and, of course, increasing the chances of converting them into paying customers.

One of these strategies is Canva’s Design School, where users can complete courses and even earn certificates.

All, of course, within Canva.

Or tutorials on how to get started with Canva—guiding users step by step so they don’t feel lost. And, as mentioned earlier, a whole collection of additional tutorials is available on YouTube.

What’s cool and super helpful in keeping users engaged with Canva is its templates. By offering fully customizable templates that can be edited with just a few clicks, Canva eliminates the struggle of staring at a blank page.

This is especially helpful for less creative users, enabling them to create designs quickly and stay motivated to keep using the tool - which btw. is Canvas's whole mission:

“Launched in 2013, Canva is an online design and visual communication platform with a mission to empower everyone in the world to design anything and publish anywhere.”

One other thing to highlight here that happens inside the tool is the loss aversion tactic it uses as soon as someone tries to unsubscribe - mentioned here in my Growth Bites series:

Growth

"THIS is what you lose..."

Hi, it’s Andreas, and I’m back with Growth—my newsletter exploring the funnels and growth tactics of today’s top startups…

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a year ago · 7 likes · 4 comments · Andreas Just

Final Words

Like every other funnel, Canva’s funnel isn’t linear either. You might see an ad, click on it, forget about it, then read about it again. Eventually, you sign up. Where and how you enter the funnel - and when you convert - is unpredictable.

But by breaking it down, we see that Canva uses different tactics for different stages of the customer journey. More importantly, it promotes different things to different target groups.

: Canva’s UX feels effortless—everything is smooth, clear, and naturally guides you. They make it clear that they are targeting businesses. You’re never overwhelmed with too many choices (except for that one pricing table). And you are never stuck searching for what you need.

Overall, Canva’s user experience is built for simplicity, speed, and seamless conversion.

Key Takeaways

Tailor your messaging

Address your customers with success stories, use cases, and features that are relevant to them. If you have multiple target groups, promote them separately. Don’t try to fit everyone into one bucket—create content, strategies, and activities specifically for each group. Just like Canva does with its webinar series for marketers.

Focus on retention.

Think about what your users need once they’ve signed up—and how you can keep them engaged. Canva does this with a design school and tutorials, guiding users step by step as they explore the tool.

What can you do to achieve the same?

See you next week! 👋🏼

→ Click here to access the full, free funnel breakdown

In this issue, we’re examining the news about HubSpot losing search traffic - a topic that dominated the marketing landscape a couple of weeks ago. I’m also answering some burning questions we discussed in the subscriber chat.

Let’s dive in

So, four weeks ago, the marketing news was filled with the headline, 'HubSpot lost 80% of its traffic due to AI.'

Looking at their visibility index, it is true that they have been losing more and more visibility and traffic.

In the podcast Marketing Against the Grain, Hubspot’s SVP and CMO discussed what happened. Yes, they lost some traffic for reasons we’ll go over here, but it wasn’t as much as 80%.

The good thing is that HubSpot saw this problem coming years ago and took preventive measures by shifting its strategy - for example, acquiring newsletters like “The Hustle” and expanding its presence across different formats and channels.

This means conversions still remain stable on HubSpot’s end.

Nevertheless, I was curious about what was behind this news and why did they lose traffic?

The Death of Generic Content

In 2024, the largest market share among all search engines was still held by Google. Even though AI had already entered the scene.

On May 14, 2024, Google introduced something called “Google AI Overview” (no worries if you don’t know what I’m talking about, it’s not available in every country yet).

Google AI Overview is essentially an AI-generated summary of your search query, placed at the top of all search results. In other words, Google’s AI now gives answers to what you’re looking for.

And similar to Perplexity, you can find the sources from which the AI pulls its information beneath the summary.

But how does this influence Google rankings?

We’ve seen popular companies like HubSpot build successful SEO strategies over the years for generic search terms, like:

Back when SEO wasn’t so popular, there were a lot of low-quality answers to those questions.

HubSpot, for example, took advantage of this by creating content that answered people’s questions in a more detailed way. This helped them rank higher, drive traffic to their site, and bring people into the funnel.

But with Google AI Overview, this strategy no longer works.

For questions like “What is Sales Planning?” people now get instant answers directly from Google. That means they no longer have to visit a website and scroll through endless fluff to find the answer - Google now provides a simple summary.

This, in turn, takes away traffic from all the sites ranking for these keywords.

So, with that, the question is: How can you still rank on Google? And how do you make AI talk about you?

Let me answer those questions separately.

How to Rank on Google in the AI Age

In March 2024, Google announced the following:

This means it is more important than ever to provide “the most helpful” information and avoid “unoriginal” content.

This also makes Google’s E-E-A-T framework more relevant than ever. First introduced in 2018, this framework helps Google evaluate the quality and credibility of content.

As Backlinko explains here, the acronym stands for:

So what does this mean? What kind of content works nowadays when AI is taking over?

This was my answer to it in a Note:

But to state it more clear, I see two ways to rank today:

1. SEO will primarily become a conversion-focused channel and you have to focus on middle- and bottom-of-the funnel content around your industry and product.

2. You make your awareness-creating, question-answering content so good that no AI can replace it

For 1:

Awareness creation has largely shifted to social media and other channels. This means people are more likely to first read about your startup or product on social platforms rather than on Google or other search engines.

However, since search still plays a dominant role, people will eventually turn to Google to look for your solution or similar products. If you create MoFu and BoFu content for search, people will find you when they search for your solution or industry on Google.

💡 You may have already heard about ToFu, MoFu, and BoFu—a concept that breaks down the funnel into different stages. This framework allows you to divide e.g. your content strategy & SEO into:

• ToFu-Content (Top of the Funnel): Focuses on the customer’s problem, answers questions and drives awareness.

• MoFu-Content (Middle of the Funnel): Educates customers about the solution your company offers.

• BoFu-Content (Bottom of the Funnel): Explains why customers should choose your specific solution.

For 2:

If we follow Google’s E-E-A-T framework, top-of-the-funnel content can still work - if it’s not generic.

By that, I mean you need to share your own experiences. Talking about content where you genuinely provide value through detailed how-to guides, like this one from Brian Dean (Backlinko) “How to Create an Effective SEO Strategy”, where he shares his own expertise.

Or content that offers a unique perspective, exclusive data, or original insights—things AI can’t replicate.

This kind of content will help you to rank and gain traffic much faster.

How to Rank for AI Searches

To answer this question, we first need to understand how AI searches work.

Here, I want to refer to an article from HubSpot - pretty iconic after that intro, right?

HubSpot differentiates between GEO (Generative Engine Optimization, i.e., content for AI searches) and SEO, explaining the key differences:

That being said, we need to focus on structure, clarity, and quality.

When it comes to AI search, the ultimate goal (today) should be for AI-generated answers to reference you.

Here, content that follows the E-E-A-T principles also performs well. As seen in the example above, when we search for it in Perplexity, we once again see Backlinko’s article, which follows these principles exactly.

But let’s assume AI works like ChatGPT and doesn’t show sources (unless you ask for them).

What then?

I’m sure most AI models will reach that point because, as they are trained on vast amounts of data, it will become increasingly difficult to trace sources.

At that stage, I’m convinced the goal will be to create awareness for your product through other channels - such as social media.

Then it comes back to the MoFu and BoFu content I talked about above.

So whenever someone is talking to AI about your industry or your kind of products, with MoFu and BoFu content you increase the chances of appearing in AI-generated search results.

From my own experience, I’ve seen that AI often pulls from FAQs, "How it Works"-pages, and Success Stories of your website.

Having this structured clearly, user-friendly, and focused on answering key questions while highlighting value makes it more likely that AI will use your information.

Final Words

Success in the AI-driven search landscape still comes down to mastering the fundamentals of SEO while adapting to new realities. The key is to create content that AI can’t easily replicate - whether through unique insights, personal experiences, or high-value, structured information.

By focusing on middle- and bottom-of-the-funnel content, optimizing for clarity and credibility (E-E-A-T), and leveraging multiple channels beyond search, you can maintain visibility and conversions.

Ultimately, ranking in AI searches starts with getting traditional SEO right.

Whenever you're ready, here is how I can help you:

• Growth Call (30 min): Stuck on a growth tactic? Let’s fix it—whether it’s landing pages, cold outreach, or social media strategy → Book here

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• Get Featured: Share your winning growth hack & promote your product to founders, growth strategists & marketers in my Growth Bite format → Reach out here or via mail: mail@andreasjust.me

PS: If you enjoyed this case study, please tap the like button below. Thank you! 💛

So, let’s jump in.

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A few weeks ago, my friend texted me and said, “Man, this startup would be a great case study for your newsletter.” And damn, he was right. The startup he was referring to?

Linear.

If you’re unfamiliar with Linear, let’s start here.

Linear is an issue tracker for developers. You’ve probably heard of Jira - it’s been the go-to for years, with a market share of 84.57% in the issue-tracking SaaS market.

But Linear went head-to-head with it by simplifying the experience, making it much more user-friendly and intuitive - meaning this startup meets an industry giant at eye level.

Since then, they have become the fastest-growing and most beloved issue-tracking tool in the world, reaching a $400M valuation in just five years.

So, how did they do it?

Linear’s Growth Strategy

Personal Branding & Networks

These three gentlemen are the founders of Linear.

And what all three have in common is a large following on Twitter and an impressive Silicon Valley background.

Karri Saarinen and Jori Lallo previously founded a Y Combinator startup that was later acquired by Coinbase.

That startup was called Kippt - a social bookmarking platform.

Tuomas Artman, meanwhile, was an engineer at Groupon and Uber in the Bay Area.

After the acquisition, Saarinen and Lallo both worked at Coinbase, and then Saarinen joined Airbnb, where the story of Linear began.

So, you might ask: What does the founders' background & Twitter following have to do with Linear’s growth strategy?

Their seed round was secured when a Sequoia partner approached Linear’s team, saying that “people she trusts in her Twitter network were hyped about Linear.” This led to a $4.2M seed round.

And not only that, their Twitter following helped them get 10,000 waitlist sign-ups for their beta tests. But more on that later.

Idea Validation Par Excellence

In his role as a designer at Airbnb, Saarinen had to work with Jira, and he was kind of surprised by how bad the tool was.

But he wasn’t alone. His colleagues were equally frustrated.

“For my own sanity, I actually wrote a Chrome extension at Airbnb to reduce some of Jira’s information overload and improve its visuals for better hierarchy. While I initially built it just for myself, 100 people at the company ended up using it.” - like he wrote in this article.

By scratching his own itch, Saarinen had unknowingly discovered the first step for his new startup.

And as he further writes:

“My friends Jori Lallo and Tuomas Artman had similar experiences at Coinbase and Uber. We also saw that most companies are no longer run by pure Agile or SCRUM practices, they have evolved their processes, but the tools haven't. If these tools don't work well for designers, engineering or even the management, then who do they work for?”

Frustrated with the situation, the three decided to fix it.

From MVP to Polished Product

Fast forward to April 18, 2019 - a Medium article explaining what Linear is marked the launch of its MVP.

Promising that Linear will be different:

But the goal wasn’t just to launch the MVP - the founders built a waitlist and directed readers from the article to Linear’s website, which was a simple landing page at the time.

Linear’s Landing Page & How It Drove 10,000 Waitlist Sign-Ups

The landing page serves as a great case study on how to build a waitlist for a product launch:

The header had a clear value proposition, specifically targeting those frustrated with tracking tools like Jira. The subheadline clearly explained what Linear was, followed by a call to action prompting users to join the waitlist by entering their email.

After the header section, Linear highlighted its features - clearly emphasizing its main selling point: speed.

Many users had frequently complained about Jira’s sluggishness. They also showcased other features missing in common issue trackers (including, of course, dark mode, lol).

What Linear made pretty well here is it creates transparency. They explicitly stated that they were still building the product. When testing an idea, many create landing pages with copy that makes it seem as if the product already exists, which can lead to disappointed users.

From the start, Linear promoted integrations with the most common tools used by its target audience - laying the groundwork for its product-led growth strategy.

Creating trust on its website by showcasing the team and highlighting their positions and previous accomplishments at fast-growing companies.

Ending the site with one final call to action for the waitlist, highlighting early access.

With this landingpage, the waitlist grew to over 10,000 users, largely driven by Saarinen’s Twitter strategy of “building in public.” Where he documented the journey of Linear.

💡 Building in public refers to a strategy where you document your journey of building a startup rather than just creating content. It helps you build an engaged audience right from the beginning - which in turn then helps you sell your product once it is launched.

Pretty smart, but commonly used nowadays. Still works well when executed the right way.

Once the waitlist was properly filled, they gradually onboarded participants, funneled them into a Slack community, granted access to the tool, and continuously gathered feedback to iterate on it.

Like the founder said here:

“When we started to build our MVP for Linear, we spent a lot of time talking to users, narrowed our audience, and tested what we were building. And it taught us some important lessons about our product (and building great products in general).”

In the end, the closed test phase lasted a full year until they refined the product into a fully polished version, ready for launch.

Linear’s Launch Day

A year later, on June 30, 2020, Linear launched publicly:

This was accompanied by a launch strategy that included among others:

• Twitter posts

• A Product Hunt launch

• Blog articles

• Community announcements

But Linear followed an interesting launch approach to create some buzz early on - just as they wrote on their website here:

”For example, when we launched Linear we announced the company before we had the product built. We launched when we raised seed funding and evolved the product. We launched when we opened the product for everyone and added pricing. We launched when we did a Series A and evolved the product. Each of the launches reached more people and generated more customers than the previous ones. Had we only launched once, it would have taken us 1.5 years to get to this state and we wouldn’t have learned as much or have as many customers as we have today.”

Product-Led Growth Strategies

The main lever of Linear’s product-led growth mechanics is its network effects.

💡 Network effects happen when your product gets more valuable as more people use it. In a product-led growth (PLG) strategy, this means that every new user naturally makes the product better for others - without your company having to do extra work.

One of the most powerful ways to create network effects is by making it easy (or even necessary) for users to invite, share, or collaborate with others inside the product. The more people they bring in, the more useful the product becomes, and the more likely new users are to stick around.

You’ve probably seen this with Slack and Notion - one person starts using it, invites others, they start using it too, and it spreads organically.

To encourage this, new users are greeted with a to-do list upon creating an account and logging into Linear:

This guides you to invite teammates, start using the tool, and connect it with other services like Slack.

What I’m missing a bit are more growth mechanics and PLG motions. Aside from the to-do list, there’s nothing that actively encourages or nudges users to invite more and more people - unlike how Slack does it here.

I mean, of course, you have the option to invite people:

But other than that, nothing.

So I assume Linear is benefiting a LOT from network effects, and there’s simply no need to push people?

How They Grow Today

In 2023 Linear achieved $8.4M in revenue and raised a $35M Series B round.

One integral part of its growth today is its community, which has nearly 15,000 users. With regular discussions, product updates, bug reports, and active exchanges, Linear has built a truly thriving community around its tool.

One other of course is the strong network effect we discussed above. As I talked to different developers using Linear they confirmed that they invited people as soon as they started working with it, so it definitely accelerates its growth.

Also Linear uses various marketing activities, which fuel its product growth engine, including partnerships and the ongoing personal branding and public-building tactics of the founders.

Meanwhile, Linear also has some big names it can rely on:

Final Words

Linear is a story straight out of the textbook. From building a product to solve its own problem, validating it with a peer group, creating a waitlist through building in public, and launching an MVP, to iterating with the community until the final product.

Linear did many things right, including, of course, its product.

But what I really love is the approach to bug fixing - as Linear’s Head of Product tweeted:

This custom centricity is what sets them apart.

Takeaways

• Don’t build in stealth mode: Linear published a blog article discussing the idea, which led to a landing page and a waitlist. → Give your idea public exposure as soon as possible to gather feedback.

• Build a community from the start: One of Linear's biggest growth levers is its community built around the product. In the early days, it was their most valuable asset for receiving feedback on product iterations and bugs.

• Care about your customers: Like Linear, prioritize bug fixing and customer care above all else—this is your biggest growth lever.

See you next week!

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