They’ve been building for months. Sometimes a year. The product is beautiful. The features are polished. The architecture is clean.

And nobody wants it.

Not because the product is bad. Because they never stopped to ask if anyone needed it in the first place.

Steve Blank saw this coming. In 2005, he published The Four Steps to the Epiphany. It’s dense. It’s not a fun read. But it might be the most important book for anyone trying to build something from zero.

The core thesis is simple: Startups are not small versions of big companies. Big companies execute known business models. Startups search for them.

That distinction changes everything.

The Product Development Death Spiral

Here’s how most startups die.

Founder has an idea. Founder builds the idea. Founder launches the idea. Crickets. Founder adds more features. Still crickets. Founder runs out of money.

Blank calls this the “Product Development Death Spiral.” You keep feeding the machine without ever validating that the machine should exist.

The fix isn’t better marketing. It isn’t a better landing page. It’s doing the work most founders skip entirely.

Talking to customers. Before you build.

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The Four Steps

Blank’s framework has four stages. They’re sequential. You can’t skip ahead. (Most founders try. It never works.)

1. Customer Discovery

This is where 90% of the value lives. The goal isn’t to pitch your product. It’s to understand the problem.

You’re testing a hypothesis: “I believe [these people] have [this problem] and would pay for [this solution].”

The trick is to ask open-ended questions.

Not “Would you use a tool that does X?” (Everyone says yes to that.)

Instead: “Tell me about the last time you dealt with [problem]. What did you do? How did it go?”

You’re listening for pain. Real pain. The kind people are already spending time and money trying to solve.

If you can describe your customer’s problem better than they can, they’ll assume you have the solution. Even if you haven’t built it yet.

2. Customer Validation

Now you build something. But not the full thing. The minimum viable version.

Put it in front of the people you talked to in step one. See if they’ll actually pay for it. Not “express interest.” Pay. With real money.

This is where most founders discover their assumptions were wrong. That’s fine. That’s the point. You’d rather learn this with a prototype than with a fully staffed company and 18 months of runway burned.

If nobody pays, go back to step one. This isn’t failure. It’s the process working.

3. Customer Creation

You’ve validated demand. People are paying. Now you figure out how to reach more of them.

This is where marketing and sales strategies actually matter. Not before. Running Facebook ads before you’ve validated demand is like optimizing the engine on a car with no wheels.

4. Company Building

The boring stuff. Processes. Hiring. Structure. You only do this after the first three steps prove the business model works.

Most startups try to do this from day one. They hire a VP of Sales before they have 10 customers. They build a customer success team before they know what success looks like for their customers.

Why This Still Matters in 2026

You’d think after 20 years, founders would have internalized this. They haven’t.

AI has made it even worse, honestly. It’s never been easier to build a product. You can go from idea to working prototype in a weekend. So founders do. They build first, ask questions never.

The tools got faster. The fundamentals didn’t change.

If you’re pre-product-market-fit, your job isn’t to build. It’s to learn.

I can’t say this enough (apparently). And learning is NOT easy. It’s hard. Don’t kid yourself thinking it’s easy and there are shortcuts. There aren’t. There are lucky people, and there are people who do the simple, consistent, hard things.

Both exist. But only one is something you can control.

Every hour you spend coding before you’ve talked to 30 potential customers is an hour you might be wasting.

(I know that’s uncomfortable. It was uncomfortable for me too.)

The One Question That Matters

Before you write another line of code, answer this: Can you describe your customer’s problem so clearly that they nod and say “yes, exactly”?

If not, close the laptop. Go have 10 conversations. Real ones. Not surveys. Not forms. Conversations where you shut up and listen.

The product can wait. The customer can’t.

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Steve Blank’s The Four Steps to the Epiphany is available on Amazon (https://www.amazon.com/Four-Steps-Epiphany-Steve-Blank/dp/0989200507). If you’re building something from zero, it’s required reading. And if you’ll do something with it (not just add it to the shelf), I’d say it’s worth every hour you spend on it.

Reply. I read every response.

You find 47 blog posts, 12 YouTube videos, and a Reddit thread with 200 comments. Three hours later, you’re more confused than when you started. You’ve consumed a mountain of free information and learned almost nothing useful.

Sound familiar?

Stewart Brand said it best at the first Hackers’ Conference in 1984:

“On the one hand information wants to be expensive, because it's so valuable. The right information in the right place just changes your life. On the other hand, information wants to be free, because the cost of getting it out is getting lower and lower all the time. So you have these two fighting against each other.”

Forty-two years later, we only remember the second half of that quote. And it’s costing us more than we realize.

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The Great Cost Shift

In the old world, the deal was straightforward. You wanted knowledge? You paid for it. Buy the book. Subscribe to the journal. Hire the consultant. The transaction was clean. Money for insight.

In the new world, the cost didn’t disappear. It shapeshifted.

Algorithms learned something publishers never figured out: your attention is worth more than your wallet. Every scroll, every click, every rage-share. That’s the new currency.

And unlike money, you don’t feel yourself spending it.

The gatekeepers of knowledge didn’t vanish. They evolved. They went from charging at the door to mining the room.

The Three Hidden Paywalls

The truly valuable information - the kind that actually changes how you build, sell, and think - hides behind three paywalls.

1. The Paywall of Time

There’s a founder I knew who spent six months trying to learn sales from free content. Podcasts, Twitter threads, blog posts, the works. She consumed hundreds of hours of advice.

Then she hired a sales coach for $5,000. In two sessions, the coach identified three specific mistakes in her demo that were killing her close rate. She doubled her revenue in 60 days.

The free content wasn’t wrong. It just couldn’t replace twenty years of pattern recognition distilled into two hours of focused feedback.

Expertise takes years to develop. You can access the information for free, but you can’t shortcut the time it takes to know which information actually matters for your specific situation.

2. The Paywall of Trust

Anyone can publish anything.

A 22-year-old with a Canva account and a ChatGPT subscription can produce content that looks indistinguishable from someone who’s built three companies.

This is a trust crisis.

The challenge is knowing who actually knows what they’re talking about.

When everyone sounds credible, trust becomes the scarcest resource.

The old gatekeepers - publishers, universities, professional credentials - were imperfect filters, but they were something.

We tore them down without building anything to replace them.

Now the filtering burden falls entirely on you.

3. The Paywall of Critical Thinking

Here’s a number that should scare you: the average person consumes 34 gigabytes of information per day. That’s roughly 100,000 words. The length of a novel. Every. Single. Day.

But consumption isn’t comprehension. Reading isn’t reasoning.

The ability to filter signal from noise, to synthesize contradictory viewpoints, to know when a framework applies to your situation and when it doesn’t. That’s a skill. And it’s one the free-information economy actively works against. Algorithms reward engagement, not understanding. They serve you more of what you click, not more of what you need.

The Algorithm Tax

There’s an invisible tax on every piece of “free” content you consume (including this one).

Call it the Algorithm Tax.

It’s the 20 minutes you spent reading a LinkedIn post that taught you nothing but felt productive. It’s the podcast episode that rehashed the same advice you’ve heard six times but had a great title. It’s the Twitter thread that was optimized for virality, not accuracy.

The Algorithm Tax is paid in fragments of attention so small you never notice any single payment. But compound it over weeks and months and years, and the bill is staggering.

Every hour spent consuming mediocre free content is an hour not spent building, selling, or thinking deeply about your specific problems.

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What This Means If You’re Building Something

If you’re a founder, this isn’t just philosophy. It could be a strategy, if you’ll do something with it:

Curation is a product. In a world drowning in content, the person who can reliably separate signal from noise creates enormous value. If you can become a trusted filter for your niche, you’ve found a moat.

Experience beats information. Stop trying to learn everything before you start. The founder who ships a mediocre v1 and talks to 10 customers learns more in a week than the founder who reads 50 blog posts. Information is a complement to experience, not a substitute. (And get a good mentor already, for goodness sake, even if you have to pay for it).

Build in public if you must, but build something. The “learn in public” trend is valuable, but only if you’re actually building, and only if the people you’re building it for are watching. Sharing your lessons has diminishing returns if you’re not generating new lessons to share.

Pay for what matters. The ROI on the right mentor, course, or consultant dwarfs the cost. The expensive thing is cheap when it saves you six months of wandering.

The Bottom Line

Stewart Brand was right - both halves of the quote.

Information wants to be free. It’s in the nature of digital goods to be copied, shared, and distributed at zero marginal cost.

Information also wants to be expensive. Because context costs. Because expertise costs. Because knowing which information to trust, when to apply it, and how to adapt it to your situation - that will always cost something.

The founders who figure this out, who invest wisely in expensive information while being ruthless about filtering the free stuff, have an enormous advantage.

The rest are still Googling at 2 AM.

What’s your experience? Has “free” information made you smarter, or just busier? Reply. I read every response.

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Rahul Vohra had a problem in summer 2017.

His team at Superhuman had grown from 7 to 14 people. They’d been coding for two years straight. Investors were asking when they’d launch. The team was getting restless.

But he had no way to know if they were ready.

You know this feeling. You’re adding features. Testing pricing. Tweaking messaging. Trying five things at once because you’re not sure which one will move the needle.

Rahul built a system to know. A way to measure product-market fit before spending a dollar on growth.

The result? He went from 22% product-market fit to 58% in nine months. Not by guessing faster. By knowing what to build.

This decision—and the framework he built around it—is exactly what Customer Development is supposed to do. And it’s why I spent yesterday writing up the Customer Development framework for you.

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The Survey That Changed Everything

Rahul found a metric from growth expert Sean Ellis: ask users “How would you feel if you could no longer use the product?”

Track the percentage who answer “very disappointed.”

The threshold for product-market fit? 40%.

Rahul surveyed his early users. The ones who’d used Superhuman at least twice in the last two weeks.

Result: 22% said “very disappointed.”

That’s barely half the threshold.

Rahul asked: what if we could increase this number systematically?

Discovery: Who Actually Loves This?

Rahul looked at that 22% who loved Superhuman. He assigned personas to each person. Founders. Managers. Executives. Business development.

He ignored everyone else.

Then he asked: what do these people have in common?

They dealt with 100-200 emails daily. They sent 15-40 replies. They prided themselves on being responsive. They aimed for inbox zero but rarely got there.

He named her Nicole.

Rahul made Nicole the only person that mattered.

Not “potential customers.” Not “the market.” One specific person with one specific set of problems.

The product-market fit score jumped to 33% just from this focus.

One person. One problem. That’s the constraint that forces clarity.

When you’re trying to serve everyone, you’re building features for people who don’t care. When you pick one person, every decision gets easier. Build this or that? Ask: does Nicole need it?

Validation: Why Does Nicole Love This?

Next question: what does Nicole actually value?

Rahul surveyed the “very disappointed” group again. This time asking: “What is the main benefit you receive from Superhuman?”

The answers clustered hard around three things:

• Speed

• Keyboard shortcuts

• Focus (one email at a time)

Everything else? Noise.

Then he looked at the “somewhat disappointed” group. The ones who wanted to love Superhuman but couldn’t quite get there.

He found a pattern: the ones who valued speed but were only somewhat disappointed had one thing in common.

They needed a mobile app.

Not “would be nice to have.” Needed.

Calendaring. Integrations. Better search. Read receipts. All showed up in the data.

The Roadmap That Writes Itself

Rahul split it 50/50.

Half the roadmap: make speed even faster. Add more shortcuts. Build more automation. Polish every detail Nicole already loved.

Half the roadmap: mobile app. Calendaring. The features blocking people from becoming Nicole.

Three quarters later?

Product-market fit score: 58%.

From 22% to 58% in nine months. Not by launching. Not by “iterating with the market.” By systematically talking to customers and building what the data told them to build.

What This Actually Means for You

Customer Development isn’t about launching fast. It’s about answering two questions before you scale:

1. Who will be very disappointed without your product?

2. What makes them feel that way?

Everything else is guessing.

You don’t need 2 years to figure this out. Just the discipline to ignore everyone except the people who would be very disappointed.

Rahul built an engine instead. Survey users. Segment by disappointment level. Focus on what the very disappointed love. Fix what blocks the somewhat disappointed from getting there. Measure the score. Repeat.

The score became Superhuman’s only OKR.

That’s Customer Development working.

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When Do You Use This?

You’re in one of three situations:

Situation 1: You’re pre-launch with some beta users
You think you’re close but you’re not sure. You have a gut feeling something’s missing. You keep adding features hoping one will click.

Do this instead: Run the survey. Find your 40%. Build only for them until you hit 40% “very disappointed.” Then scale.

Situation 2: You’ve launched but growth is expensive
Your CAC is too high. Conversion rates are weak. You’re getting users but they’re not sticking. You can’t figure out why.

Do this instead: Survey your happiest users. The ones who’ve stuck around. Find out what they value. Stop building for everyone else.

Situation 3: You’re stuck between ideas
You have three feature requests. Your team is split. Everyone has an opinion. Nobody has data.

The problem isn’t deciding between A, B, or C. The problem is you’re asking the wrong question. You’re trying to pick features when you should be asking: which one moves us closer to 40%?

Do this instead: Talk to the customers who would be very disappointed. Ask what benefit they get. Build what reinforces that benefit, not what sounds cool.

Customer Development gives you the framework to stop guessing. It won’t tell you what to build. But it will tell you who to build for and what they actually value.

That lets you move faster. Not because you’re cutting corners. Because you’re building the right things.

Rahul moved faster by knowing. He had a number that told him if he was getting closer or further from fit. He had a system that told him what to build next.

That’s the difference between wandering and walking toward something specific.

The hard part isn’t the framework. It’s the discipline to use it every week. To ignore the feature requests from people who aren’t Nicole. To say no to ideas that sound good but don’t move the score.

That discipline is what separates founders who find fit from founders who burn runway chasing everything.

The system works. Superhuman proved it. But you need the framework to apply it.

→ Read the Customer Development Framework

I recently took over the entrepreneurial division of a non-profit. The goal is to help founders in East and West Africa create sustainable, profitable, physical product impact-focused businesses. In other words, Social Enterprises.

As part of my work with them, I was happy to be able to visit Kenya and Uganda recently, distribute the non-profit’s “The Shoe That Grows” to kids in the most poverty-stricken county in Kenya - one of the largest schools in Kenya, in fact.

Sandwiching this experience of distributing shoes to kids, I was excited to meet many entrepreneurial social enterprise founders.

But, one question kept coming up over and over again.

How do I expand my revenue when it’s seasonal?

Many entrepreneurs all over the world run into this same issue. It might be the Christmas season for e-commerce, or summer for SaaS, or the rainy seasons for construction products and agriculture.

Seasonal buying is everywhere. It’s not just you.

So, what’s the best way to deal with this, and increase revenue during these lower volume seasons?

The easy starting point is to consider what complimentary products or services the same person buys in the low season.

That’s a good start. But we can do better.

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Enter, the best 2 principles of revenue expansion + a bonus

I like to eat dessert first, so I’ll start with the bonus.

Bonus: Extra capacity

Whenever I’m looking for new revenue, I look at the extra capacity a business has. In Toyota’s Production System, this would be considered waste.

In Uganda, however, someone said “Waste is not waste until it’s wasted.”

I like that.

So, reconsider the extra capacity in your process as potential opportunity for someone else, and thus revenue for you.

Ideally, you don’t have this extra capacity or overage. But if you do, you can sell it.

Amazon is the most famous example of this, productizing extra computing an storage services, which they already used, as Amazon Web Services (AWS). AWS exists as 18% of Amazon’s total revenue in July, 2025 (estimated to make up 75% of their total operating income)!

“We have a meaningfully larger business in the AWS segment than others,” Amazon CEO Andy Jassy told analysts on a conference call.

In the companies I was talking with, they have extra capacity in the way of buildings and land, people-power, and machines that sit idle. They might also have bought raw materials in bulk which can be sold or used to build other products.

The lesson here is that in every business (except probably those who follow the Toyota way), there is extra capacity in their processes.

Look at this extra capacity, a cost to you, as raw materials for someone else. There’s opportunity in it. Maybe not as much as if you could use it, but it’s definitely worth something to someone. Find out who.

1. Leverage similar processes

Another entrepreneur who mentioned their cyclical revenue with an organic produce wash wanted my thoughts on entering a seed market.

So, I asked him… where in this new business idea are you using the same workflows, assets, resources, or processes, as you have in your current business?

Answer: nowhere.

Result: red flag!

Why? Because the only thing that’s similar is a few customers (not even all of them). Otherwise, you’re starting a brand new business.

Starting one business is hare enough. Starting more will be a distraction.

Instead, I asked him to look at and document every asset, resource, and process in the current business. After you’ve found extra capacity that can be monetized, look for what you can do with what you already have. How can you leverage your machinery, people, and more? Especially in the down-turn times.

2. Solve the problem you just created

Now, I know I started with the bonus, but this one is my favorite method for generating new revenue on top of a current business.

If I asked you, “What problem does your customer have before they meet you?” I’m sure you could answer this, right?

Great. Now, “What is their new world like after using your product?” Fill in the blank.

And now, the kicker…. “What problem do they have now that you’ve solved this prior problem?”

And voila. There you have it. The new problem to solve.

It’s the same customer, and a built in problem, who already trusts you.

As it’s famously said, “It’s easier to sell more to your current customers than get a new customer.” So, do it. You know them intimately. You know their current status, and their new desired status, because you just created the new problem they now have by solving their old problem.

Easy peasy, right?

Good. Now what are you waiting around here for? Go do it!

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If you’re a founder who wants to get unstuck, reduce churn, get through that revenue plateau, generate more leads, and more… Get in touch today!

→ I want to get unstuck, let's talk

P.S. If you want to learn more about The Shoe That Grows or their entrepreneur Fellowship, consider learning more and/or donating at BecauseInternational.org.

I recently wrote about how your ideal customer is one who values your product the most”. And then quickly, in one of my private communities, I had this question pop up:

But how you would talk to your ideal customer if they are not the ones who try the product?

In my case -- I totally agree. CTOs / Director of Engineering are probably the ones who make decisions. But it is developers who try the product first.

In the article you talk about messaging. I get it. But how practically you can reach out to decision makers?

Let’s dissect this question here and get to the root of this question here, right now.

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This is the "the user is not the buyer" problem.

Sure, it's a tough one, and I don't think there's a one-size-fits-all solution.

Here’s the key… it depends on one thing:

→ Who actually has the power?
(and hint, it’s not always the person with the credit card)

Let me explain…

Scenario 1 - Smaller org charts

Your product is used and bought by smaller companies, they have CTOs/directors, but it's pretty flat, and they are in build mode. These are likely early stage or smaller companies still trying to figure out their market fit or value proposition.

The user (developer) might have the power. Here’s why…

The CTO's incentive is to reduce time to market/iterate. The faster they are to market and iterate, the faster they learn, the faster they find PMF, the more likely everyone keeps their jobs (and maybe they get a big payout win 3-10 years from now, or at least that's the promise from the CEO).

The user/dev has the power because of the time constraint.

They're likely to come to the organization with knowledge - it's why they were hired. So, their suggestion on what to bring to the table in terms of dev tooling will be massively important.

They might even setup a free account to use before anyone notices, "just to get things done".

Eventually they have to level up to a paid tier and voila, the company has just been trojan-horsed.

Scenario 2 - Larger org charts

The CTO/directors/leadership are the ones who have the power because there’s different constraints other than time. In this case, let’s just say security is the primary constraint.

No user/dev is going to be allowed to install software themselves. This comes from top-down.

Thus, the sales cycle is going to be long since you have to sell the value differently and there’s likely a vetting and due diligence type of process they have to go through to choose your product over another.

The users/devs don't have much of a choice because the primary value/risk isn't UI/UX/DX or whatever the user/dev cares about. It's security + outcome/output.

Now here’s the thing… The person with the credit card is who we typically would call the "decision maker" (and in the original question, it was called the “ideal customer” even).

But the reality is, they aren't always the one with the power. It depends on the constraints they're under.

It's also not “who tries the product first”, as the original question states.

It's “who has the leverage”?

Who has the power, the constraints, and/or the incentive to push it through the most?

Subsequently, this is who values it the most.

IMPORTANT POINT: I’m getting picky about defining “value” here. It needs to be actionable - something within the bounds of reality. Someone who says it’s worth N to them, but doesn’t have the means to actually trade N for it, doesn’t really matter at the end of the day.

Let’s get back to it…

If your user/dev values it more than the holder of the budget, then you only have one thing to do….

The CTO will never write the check for the value the user/dev deems it’s worth.

That said, as a dev, I've paid for tools out of my own pocket that mean enough to me to do so if it's valuable enough. And in that case, the incentive and value isn't because the company will win... it's because I'm going to look great when I make the company win.

Different incentives.
Different payoffs.

But, with that in mind, let's get more specific...

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Let’s get more specific…

I posed this question back to the OP: “What's the typical path for adoption (that works best for you!)?”

Perhaps for you, it goes something like this:

1. User/dev registers

2. User/dev runs free trial on a local environment

3. User/dev gets a the value right before the do a pull request, so they can see the before and after scenarios (highlighting any issues)

4. User/dev sees value (Note: here’s how to master the “aha moment”). They see it will save them time with QA’ing their own changes, perhaps it could even be automated?

5. User/dev tries to convince leadership it's necessary to get it paid for

6. Leadership tests/sees process, checks budget, decides yes/no

7. Leadership gives approval for purchase

8. User/dev/leadership purchases

9. User/dev continues to use it and propagates among other user/devs in the co.

In this case (change based on the assumption of the scenarios above, small vs big orgs, user flow, etc), here's some questions to figure out:

What's the real incentive behind why the dev suggests the tool? Does the dev want it because it helps them be awesome / reduces the pain of doing their job, or because it'll help the company goals?

What's the real incentive behind why the leadership buys it? Because they'll see it'll take less time for the dev to do their job, they'll be better at it, thus getting to the goals of the company?

If those things are true, I would do these 2 things….

1. Give the user/dev the tools they need to convince their leadership that it's a slam dunk (for their incentives). Translate the value from the user/dev’s terms into the leadership’s terms.

Note: It's best if this isn't explicitly declared to them like "here's how you convince your leadership this is a good idea" but more like "here's a report showing how much time you were going to spend doing it in the old way vs how much time you actually spent doing it this way". Also, make these actual, real numbers as much as possible or the dev won't use the report because they’ll know the numbers are inaccurate.

2. I'd also do some customer interviews here with the devs to figure out how those conversations usually go with leadership. What do they need to make that conversation go faster/easier? What stops them from buying?

Find the friction, smooth it out.

The meta point here is that you're not going to talk to the credit card holder; the user/dev is going to do that for you.

Give them the best possible chance at convincing the leadership. Make them look awesome for even bothering the leadership with a choice like this. Make it obviously awesome for them to decide “yes”. These users/devs are your sales people. Treat them as such in the sense that if they win (product does what the user hopes and dreams it will, getting them to the promised land), you win ($), and then they win again (look good, systemically removing friction in their job/process, etc). Not to mention, the leadership wins and the company wins.

Now go, and proselytize those devs. ;)

If you’re a founder who wants to get unstuck, reduce churn, get through that revenue plateau, generate more leads, and more… Get in touch today

→ I want to get unstuck, let's talk

🧢 Hat tip to Yuriy Gerasimov from Diffy (visual regression for Wordpress and Drupal) for the being the muse this week! Thanks for letting me write about our chat, Yuriy!

A friend texted me yesterday, frustrated after a weekend at a pickleball convention where he was selling his new board game.

"We had mismatched expectations of how folks would value things: '$30 for a game is pricey' while holding a $20 hot dog...."

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I've seen this exact scenario play out before. You've built something great, but the people you're talking to keep saying it's "too expensive" or "not worth it."

The issue wasn’t the fact that the game cost $30.

They were talking to the wrong person.

The Pickleball Revelation

Here's what I told my friend:

"Whenever I see that price objection, I hone in on the likelihood that they weren't your ideal customer. The pickleball players might not value the game as much as those who are pickleball adjacent - the moms, dads, grandparents, husbands, wives of pickleball players."

Think about it.

The players would rather play actual pickleball than a board game version of it.

But the family members who love someone who’s obsessed with pickleball?

They're desperate for ways to connect. (It is a cult, right?)

"$30 to connect with someone I love is nothing," I explained. "The value isn't there for the pickleball players, it's much higher for those who love pickleball players."

I bought two copies of the game for myself.

One for my family (who don't play as much as I do) and one to give to friends who do play.

In both cases, the purchase was for connection, not for the game itself - a higher level value.

Why This Matters for You

This same principle applies to every product or service I've analyzed. The person experiencing the problem isn't always the person who values the solution most.

Here are three real examples from companies I've worked with:

Case 1: The Time-Tracking Tool

• Who they targeted: Freelancers and consultants

• Who actually bought: Agency owners managing multiple freelancers

• Why: Individual freelancers saw time tracking as overhead. Agency owners saw it as essential for profitability and client transparency.

Case 2: The Code Review Platform

• Who they targeted: Senior developers

• Who actually bought: Engineering managers and CTOs

• Why: Senior devs were confident in their code. Managers needed to ensure quality across their entire team.

The Framework: Finding Your True Buyer

When you're getting price objections or lukewarm responses, work through this three-step process:

Step 1: Map the Problem Chain

Ask yourself:

• Who experiences this problem directly?

• Who feels the consequences of this problem?

• Who has budget authority to solve this problem?

• Who gets promoted/fired based on this problem being solved?

These could be four different people.

Step 2: Identify the Value Multiplier

The person who values your solution most isn't necessarily the end user. Look for:

The Connector: Someone who wants to bond with or help the end user (like the pickleball families)

The Amplifier: Someone who benefits when the end user succeeds (like the agency owner whose freelancers track time)

The Protector: Someone who prevents negative outcomes (like the CTO preventing bad code from shipping)

The Optimizer: Someone who improves efficiency across multiple people (like a customer success director who needs data to prevent churn and improve satisfaction scores)

Step 3: Reframe Your Value Proposition

Once you identify the true buyer, reframe your messaging:

Instead of: "Save 2 hours per week on time tracking" Try: "Increase project profitability by 23% with accurate time data"

Instead of: "Catch bugs before they ship" Try: "Reduce post-launch incidents by 67% and protect your reputation"

Instead of: "Respond to customers faster" Try: "Prevent 34% of potential churn with proactive support insights"

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The Validation Process

Before you pivot your entire marketing strategy, validate this with real data:

1. Survey your existing customers: Ask who initiated the purchase and why

2. Interview lost prospects: Find out who the real decision-maker was

3. Test new messaging: Create landing pages for different buyer personas

4. Track conversion rates: See which persona converts better

Here are some common mismatches, as examples:

Security Tools: Users are developers, buyers are CISOs.
Productivity Apps: Users are employees, buyers are team leads.
Analytics Platforms: Users are analysts, buyers are department heads.
Development Tools: Users are junior devs, buyers are senior directors.
Marketing Automation: Users are marketing coordinators, buyers are marketing directors.

That all said, don't spend months on this. Here's a quick way to validate your true buyer:

1. Interview 10-20 existing customers (or customers of alternatives or workarounds) about their buying process, jobs-to-be-done style, as a documentary of the facts, not their feelings.

2. Create new personas based on your interviews, with hypotheses around who’s buying and for what purpose. Create messaging around these personas.

3. Launch targeted ads or other campaigns using the messaging to each persona and measure engagement

4. Analyze results and commit to the highest-converting persona

Voila! You now know more about your actual IDEAL customer profile than you did before.

What you may not have realized before doing this activity is you actually already had a persona and messaging, you just didn’t conceive of other alternatives as to why people might value your product or service that weren’t what you started with in your head when you built the thing.

Red Flags You're Targeting the Wrong Person

Watch for these warning signs:

• Consistent price objections from your target audience

• Long sales cycles with multiple stakeholders

• High engagement but low conversion rates

• Customers who buy but don't use the product (this could also be a promise-problem; you’re not fulfilling on the promise you made in your copywriting)

The Bottom Line

My friend's board game wasn't too expensive. He was just selling it to people who didn't value what it actually provided.

The pickleball players wanted to play pickleball.

The families wanted to connect with their pickleball-obsessed loved ones.

Same product.
Different value.
Different buyer.

Your SaaS works the same way.

Stop trying to convince people who don't value your solution.

Start finding the people who desperately need what you've built.

The right customer will never say your product is too expensive. They'll say it's exactly what they've been looking for.

Now stop trying to convert the wrong people and go find your actual buyers.

SIDE NOTE: If you want to connect with your pickleball-obsessed family or friends over a nice board game, HotShot Pickleball is the best! Enjoy!

If you’re a founder who wants to get unstuck, reduce churn, get through that revenue plateau, generate more leads, and more… Get in touch today

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I was just listening to Darknet Diaries and something the host said sparked an idea. This is just one of those times I thought I’d share with everyone else. It’s a tad techie, so if this isn’t for you, we’ll see you in the next article.

But, if you run your own domain, like I do with nateritter.com, that’s related to my identity, you might consider doing this yourself….

Here’s the idea.

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For those of us who are extra security conscious, and can setup and use a catch-all/wildcard email address, you could setup what I’m going to call from now on a “UUID email addresses” per site.

Here's how I see it working from the user perspective:

1. User sets up catch-all email address (i.e., `*@nateritter.com` might forward to `foo@nateritter.com`)

2. Go to a site you want to register at

3. Generate a random string (anything like Raycast or tools like that can do this out of the box) `[random-string]@nateritter.com` to use as the email address when registering. Obviously use a random password generator for the password too. Register with that.

4. Any confirmation emails go to your catch-all (in this example, `foo@nateritter.com`), so you can confirm your email address or whatever you need to do next with it.

5. Whenever you go to sign in, your password manager will fill in the details for you, so no need to remember either the password nor the email address.

This would be similar to `nate+amazon@gmail.com`, where “amazon” can be replaced with anything you want and you still get the email in Gmail, but the wildcard local-part/username (“amazon” in this case) would be a random string.

This would be way more secure because it would be so much harder for hackers to simply guess what the email address is with a “forgot password” or “sign in” functionality, which basically tells them that the email exists on the target website.

That’s it.

I'll be here all week.

Let me know when someone builds this into an automation.

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(FWIW, I suggested this to 1Password too, so let’s hope)

In the last few days, I turned a few tools into what’s as close as I can get to a second brain.

But that’s not even the impressive part.

The truly impressive part is that millions of other people are doing the same, in minutes, and unlocking connections between the stuff we’ve been putting in the digital space for ages!

This. This is why AI is not just a fad. This is how AI can become useful to us, personally.

Besides having robots do all the housework and cook dinner for us, I’ve been excited by the thought that all the things I think about could become useful, long after I’ve gotten dementia or died.

“That’s all great, Nate, but what about today?”

Today, I can finally say the dream of assistance in connecting my personal thoughts with the outside world - trends, changes, new ideas - to create and build new realities and ideas… well, that’s a thing now.

NOTE: It’s still a bit clunky.

But, if you’ve read up on Model Context Protocol (MCP), here’s how to apply it to your own personal knowledge management system (PKM), like Obsidian.

(And if you haven’t read up on it, don’t worry, I’ll walk you through it here.)

Here’s the point: We’re finally at a stage where we can connect dots that might never been connected before in our own journal entries, evergreen notes, thoughts, and discussions.

Let’s get to it. Only 2 steps.

1. Setup the tools

2. How to use it

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Setup the tools

1. You’ll already need to have Obsidian downloaded and a local vault of Markdown files.

2. You’ll need to know where your vault is - the path to it. Here’s an easy way todo that… get the “Show Current File Path” community plugin. Install and enable it.

   

   Open up a file and then the command palette. Type in “copy path” and select “Show Current File Path: Copy path”. Paste that somewhere that you can use later like a text file. It’ll look something like this:
   
   /Users/nateritter/Library/Mobile Documents/iCloud~md~obsidian/Documents/Nate Ritter/

   Just make sure to add the slash at the end, and remove any sub-directories that might have crept in there based on the file you chose to do this with.
   
   NOTE: I know it’s not recommended you use iCloud for your vault location, like I do, so just beware of that. Why it’s a bad idea is outside the scope of this write up, but I know. Don’t flame me in the comments.

3. You’ll need node and npx installed. There are a myriad of ways to do this, and I don’t want to be a participant in messing up your system, so be careful here and ask a trusted friend if these sound too technical for you. My surface-level recommendation is to test your system first to see if you have node, and if not, install it via homebrew.

   1. Open a terminal window and type
      node --version && npm --version

   2. Hopefully you see something like this as the response:
      v23.9.0

      11.2.0

   3. This means I’ve installed v23.9.0 of node and version 11.2.0 of npm. If you get a response other than a couple of version numbers, you likely need to install one or both of these. My opinion is that it’s easiest to install these on a mac using homebrew like this, again, in your terminal:
      /bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)"

   4. When homebrew is installed, install node and npm like this:
      brew install node

   5. In some cases you’ll want npx as well, so, test that first with:
      npx --version
which should respond with a version too. If it doesn’t just install it globally with this command:
      npm i -g npx

   6. Done with half the geekery.

4. Now, you’ll also need to download Claude Desktop. There’s the link for you right there. Download it. Install it. Open it.

5. Next, we’re going to find the config file for the MCP servers that can be added to Claude. Per Anthropic’s instructions here, open the Settings, then click on Developer, then click on “Edit Config”

   

6. Here comes the 2nd half of the geekery. With the config file open in your favorite text editor, add a bit of code to the config file (this comes straight from the maker of the MCP themselves). Here’s the format:
   { "mcpServers": { "obsidian": { "command": "npx", "args": ["-y", "obsidian-mcp", "/path/to/your/vault", "/path/to/your/vault2"] } } }
   
   So, here’s what I added inside the mcpServers object:

   

   NOTE: I have other MCP servers listed, so if you don’t, you can remove the comma at the end of my example, as shown by the example above this screenshot.

7. Quit Claude Desktop and re-open it. You should now see a number next to a little tool icon (I have a lot, you won’t see this many):

   

   Clicking it will show you all the MCP tools you have available, including the “obsidian” tool and what it can do.

Great… that was annoying easy to setup, right?

So, how about we move on to actually using it, shall we?

How to use it

This part is easy.

If you want to only ask questions about your own Obsidian vault, simply type this in the prompt like so:

use_mcp_tool obsidian

Or, if you would rather be less of a nerd, just ask it nicely like this:

Use the mcp tool obsidian.

Follow this with whatever prompt you want, like so:

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If you’re a founder who wants to get the most from AI to reduce churn, understand your ideal customer, generate more leads, and more… I’m here for you. Get in touch.

→ I want to get unstuck, let's talk

Imagine having complete clarity about exactly who your customers are, what they need, and how to reach them effectively.

This is the desired state of proper market segmentation – a foundation so critical that skipping it is like building a house without blueprints.

Most entrepreneurs rush to develop products without this clarity, which is why so many startups eventually fail.

Market segmentation might sound like boring business jargon, but it's actually a fascinating process of exploration and discovery that can determine whether your business thrives or merely survives.

The Disciplined Entrepreneurship framework, developed at MIT, presents market segmentation as Step 1 in a 24-step process.

Let's break down why this step is so vital and how you can execute it effectively.

1. Why market segmentation matters

2. What makes a true Market Segment?

3. How to do market segmentation in 3 steps

4. Primary market research (don’t outsource this!)

5. How long to spend on the market segmentation process

6. What you’ll get by doing it

7. Next steps

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Why Market Segmentation Matters

The first commandment of entrepreneurship is remarkably simple: the single necessary and sufficient condition for a business is a paying customer. Not a great idea. Not a brilliant product. Not even a strong team.

Without someone willing to pay for what you offer, you don't have a business.

This truth is why market segmentation is so essential. You need to identify exactly who those potential paying customers are, what problems they face, and how urgently they need solutions.

Many entrepreneurs fall into one of two common traps:

1. Selling to everyone: Thinking your startup with limited resources can create products that fit the needs of anyone you encounter. This scatters your focus and resources.

2. Abstract customer scenarios: Creating spreadsheet projections based on secondary research without actually talking to potential customers. This is what veterans call "having fun with spreadsheets" rather than validating real market demand.

Instead, disciplined entrepreneurs narrow their focus to well-defined, winnable market segments that can serve as a foundation for growth.

What Makes a True Market Segment?

A target customer or market segment isn't just any group of similar people. To be considered a proper market segment, the group must share three fundamental characteristics:

1. They buy the same product.

2. They buy it in the same way (same use case, value proposition, channel).

3. There is word of mouth between them – they influence each other.

The third point is often overlooked but extremely important. If potential customers don't communicate with each other, your marketing efforts will be far less efficient.

How to Conduct Market Segmentation in 3 Steps

Step 1A: Brainstorm Widely

Even if you think you already know your target market, start by brainstorming a wide array of potential customers who might benefit from your idea or technology. This isn't about viability yet – it's about creating as long a list as possible.

One team, who developed a solution for connecting young professional women and combating loneliness, initially considered markets ranging from youth to elderly across various demographics before narrowing their focus.

Similarly, another team, which created technology to feel three-dimensional objects rendered by computers, brainstormed applications ranging from boxing channels to flight simulators to computers for the blind.

No idea is too crazy at this stage. As one founder put it, "stealthy is unhealthy" – socialize your idea widely to get feedback rather than keeping it secret.

Step 1B: Narrow Thoughtfully

Once you have many potential markets, you'll need to narrow them down to 4-10 candidates for deeper analysis. Begin with this critical question: "Is this market segment one I could get really excited about and dedicate the next six years of my life to serving?"

If you're not passionate about serving a particular market, cross it off regardless of how lucrative it might seem. You simply won't last.

After applying this personal filter, use analytical filters to evaluate:

1. Business considerations: Market size, competition, value proposition, etc.

2. External resources needed: Teammates, partners, capital requirements

3. Execution risks: How many things need to go right for you to succeed?

Geoffrey Moore, author of "Inside the Tornado," suggests eight specific criteria for narrowing market opportunities, including whether the target customer:

• Is well-funded

• Is readily accessible to your sales force

• Has a compelling reason to buy

• Can be served with a "whole product" (possibly with partners)

Step 1C: Build a Market Segmentation Matrix

Create a framework to analyze your top market segments in a structured way. Your matrix should include rows for:

• End user description

• Task they're trying to accomplish

• Benefit they receive

• Urgency of their need

• Example end users

• Lead customers

• Willingness to change

• Market characteristics

• Size of market

• Competition/alternatives

• Other components needed for a complete solution

• Important partners

Now fill this matrix through primary market research (PMR) – directly interacting with potential customers. Secondary research (reading reports others have written) is insufficient, especially for innovation-driven startups creating products that don't yet exist.

The Power of Primary Market Research

When talking with potential customers, maintain an empathetic listening mode. Don't try to sell anything or steer the conversation toward your solution. Be in "inquiry mode," not "advocacy mode."

Remember:

• You don't have "the answer" for your potential customers

• Your potential customers don't have "the answer" for you

• Focus on understanding their pain points, not designing solutions yet

One team interviewed dozens of women to validate their assumptions about loneliness and friendship-building challenges.

This primary research helped them understand that women in different life stages (new graduates, relocating professionals, new mothers) had distinct needs and behaviors.

Another team spent three months on market segmentation because they had strong intellectual property protection. This allowed them to thoroughly research eight different industries, from entertainment to medical visualization to industrial design.

The key: Don’t outsource this. Nobody should know your customer like you do.

How Long Should You Spend on Market Segmentation?

Give this process at least a few weeks of full attention. The time invested depends on:

1. The speed at which your target market is moving

2. Whether you have a strong competitive advantage (which buys you more time)

3. The personal needs of your team

Don't let this become a never-ending process or fall into "analysis paralysis." Make your best assumptions and then test them. You'll revisit this step as you gain more information through the remaining steps.

What You Should Gain from Market Segmentation

When done properly, market segmentation delivers three major achievements:

1. A solid analysis: The matrix provides fundamental information to move forward in an evidence-based manner.

2. A mindset change: You'll shift from focusing on your product to seeing the world through your customers' eyes – building from the customer back, not from the product out.

3. A coherent and cohesive team: This process tests whether your team can work together, debate issues, and ultimately unite around a vision. If you can't collaborate effectively during this relatively easy step, you should consider adjusting your team.

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Real-World Applications

Market segmentation works for both "technology push" (a solution looking for problems) and "market pull" (a problem looking for solutions) ventures (See 3 Pathways to Entrepreneurship That Actually Work for these definitions)

One team saw that teachers spent hours on the energy-draining task of grading papers.

They segmented the teacher market by subject (math, science, language arts), level (elementary, middle, high school), school type, geography, teacher experience, and technology receptivity.

This detailed segmentation helped them understand that "teachers" weren't a monolithic group but represented many different types of potential customers with varying needs and buying behaviors.

Inside this type of segmentation is your fabled, mythical, and often misunderstood and underserved ideal customer profile (ICP).

Your Path Forward

Problems showing up later in a startup's journey often come from entrepreneurs not doing rigorous market segmentation upfront.

Invest your time and effort here, and it will pay dividends.

The goal isn't perfection, but to develop a deep understanding of potential markets so you can make an informed decision about where to direct your limited resources for maximum impact.

As always, if you’re a founder who needs help figuring out your ideal customer profile and walking through this process in more detail, I’m here for you… Get in touch.

→ I want to get unstuck, let's talk

We all have ideas. Sometimes we just don’t know if they’re good or bad ideas.

Sometimes we don’t even care if anyone else thinks they’re good or bad - validation soapbox be damned.

But, sometimes, when it’s this easy to build, you just can’t say no.

Sure, I could have spent my time elsewhere. But, I’m not just an entrepreneur. I also like building things and playing with new digital toys, just because I can.

This is one of those stories. The story of spicytake.xyz.

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The problem with content

I like to write. But, when my brain is stuck, it’s hard sometimes to come up with new, fresh ideas.

When creating content gets difficult, I start looking around at inspirational sources.

It could be business books, philosophy, or even how nature works or a strange academic paper that was published 70 years ago.

Whatever the case, I like collecting that info.

Unfortunately, collecting resources doesn’t solve the blank screen problem we all stare at sometime.

What if….

But, what if we could take some inspiring YouTube video transcript, or that academic paper, or that blog post that really got you thinking… and instead of just summarizing it, created a super short social media post (no, I won’t call it an “x post” or whatever)?

I mean, like really really short.

What if we could take the insights from those posts and generate some spicy take 🌶️?

That just might get the juices flowing.

In fact, it did. And does. Often.

And if it could do it for me, it could do it for others.

Enter: Lovable

Now, there was a day, not too long ago, where I built a startup in a weekend using actual code I wrote myself.

But, there’s this new AI thing going around. Perhaps you’ve heard of it.

I have used AI tools to help me code for quite some time. But, this time I wanted to crank this sucker out as fast as possible. I didn’t want to spend too much time on it. I mean, I preach time prioritization all the time. I can’t go back on it now.

So, I fired up Lovable.dev and gave it a whirl.

Within a couple hours, I had the base functionality written and working.

By the end of the next day, I had history, login, and even an API built.

Sure, I could have done this using code myself. But, I was doing this between time with my kids, snowboarding, and client work.

The switching costs alone would have made this almost impossible.

Then, the roadblock

The only thing I didn’t have working was the Billing section. For some reason, Loveable really couldn’t figure out the Stripe setup.

Shortcut to about 8 hours of trying 3 different AI coding tools to get it to work, and I just realized it wasn’t necessary.

I took my own advice, and shipped it at midnight, without billing.

Why?

Because who knows if anyone is going to care.

If they do, then maybe I’ll add it back in. But until then, I’ve done zero validation work to see if people want it.

I’ll probably put close to zero marketing effort into it too.

So, why add billing when I might be the only person who uses it? Psssh.

*slaps big red button*

Send it!

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What’s next?

Well, if you want to give it a try, go for it. It’s open to use for free anonymously.

Registering for an account is only required if you want:

• to see your history and have access to old URLs and posts generated

• to get an API key to generate them programmatically

Now, here’s where you might ask…

Nate, why would anyone want to do this programmatically?

Well, if you’re like me, and you generate content all the time, it might be nice to automate the generation of some tweets, Bluesky posts, and/or LinkedIn carousels based off the insights you write about.

That’s all. It’s late. I’m done.

Go. Be fruitful and multiply (your content).

Now, if you’re a founder who needs help figuring out why your churn is so high, why your leads aren’t buying, or why your ads aren’t working, I’m here for you…

→ I want to get unstuck, let's talk

My hope is that we can hear from and help each other along the difficult journey of becoming sustainable (in all the healthy ways) and successful entrepreneurs.

And it’s hard to do this alone.

So, let’s do it together.

This is a conversation space exclusively for subscribers—kind of like a group chat or live hangout. I’ll post questions, updates, and stories from you that come my way too, and I can’t wait to see you jump into the discussions too!

Join chat

How to get started

1. Get the Substack app by clicking this link or the button below. New chat threads won’t be sent sent via email, so turn on push notifications so you don’t miss conversation as it happens. You can also access chat on the web.

Get app

2. Open the app and tap the Chat icon. It looks like two bubbles in the bottom bar, and you’ll see a row for my chat inside.

3. That’s it! Jump into my thread to say hi, and if you have any issues, check out Substack’s FAQ.

Imagine waking up every morning with a clear sense of purpose, working on something you genuinely care about, with a team that shares your vision. This isn't just entrepreneurial fantasy—it's the foundation of sustainable business success. The most successful founders don't just chase profits; they're obsessed with creating impact.

I've studied the entrepreneurial journey extensively, and what separates those who merely start companies from those who build lasting ventures comes down to something deeper than a clever idea or technology. It comes down to finding your raison d'être—your reason for existence.

Let's explore the three proven pathways to entrepreneurship and how to determine which one might be right for you.

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The Three Starting Points for Any New Venture

Every entrepreneurial journey begins from one of three distinct starting points:

1. The Idea-Driven Entrepreneur

You've identified a problem or opportunity that excites you. Perhaps you've thought of a new approach that could change the world—or at least a small part of it—in a meaningful way.

What it sounds like: "I want to start a company in Africa that will create a sustainable business model to improve life for the people there and empower them with jobs."

The danger here is thinking the idea alone is enough. It's not. Ideas evolve dramatically as they meet market realities.

2. The Technology-Driven Entrepreneur

You have access to a technological breakthrough and want to capitalize on it, or you want to help deploy it faster to benefit society.

What it sounds like: "I have a robot that allows the user to feel objects rendered by a computer."

This starting point radiates with potential, but the challenge is finding the right application and market for your technology.

3. The Passion-Driven Entrepreneur

You're confident in your skills and are driven to make an impact. You may want to be your own boss but haven't landed on a specific idea or technology yet.

What it sounds like: "I have a master's in mechanical engineering and I can quickly prototype almost any technological gadget. Now I want to put my skills to use in the most impactful way possible, and be my own boss."

While passion is crucial, it's only the beginning. You'll need to channel that passion into a specific problem worth solving.

The Entrepreneurship Reality Check: Are You Really Ready?

Before diving in, ask yourself these critical questions:

1. Do I understand that founding a company will be incredibly hard and still want to do it?

2. Am I prepared for a lengthy process filled with failures I'll need to learn from without taking personally?

3. Do I recognize I cannot do this alone?

4. Do I understand that success isn't guaranteed and requires constant iteration?

5. Am I committed to building an "anti-fragile" organization that grows stronger when faced with challenges?

6. Will I take ownership of decisions while still listening to advice?

7. Am I willing to leave my comfort zone daily?

8. Am I doing this for more than just the money?

If you answered "no" to any of these questions, it doesn't mean entrepreneurship isn't for you—it just means now might not be the right time. And that's perfectly okay.

Many entrepreneurs fall into the "curious/exploratory" category. They're interested in learning about entrepreneurship but aren't ready to quit their jobs and dive into the chaos and uncertainty of a startup. Some find their place in corporate entrepreneurship or as "entrepreneurship amplifiers," helping build resources that support startups.

Finding Your Core Question

Before you can narrow your focus to an idea or technology, you need to answer a fundamental question:

What can I do well that I would love to do for an extended period of time?

This means finding something that will motivate you through both the good days and the bad—and there will be plenty of both.

Beyond the Idea: Building Your Founding Team

Entrepreneurship is not a solo sport. Research from MIT shows that businesses with multiple founders consistently outperform those started by individuals.

Finding co-founders is like finding a life partner—it requires effort, discernment, and there's no algorithm to simplify the process. Here are five ways to increase your odds:

1. Get involved in the entrepreneurial community, but recognize that casual networking events aren't enough. Look for opportunities to see potential partners in action, like hackathons or pitch competitions.

2. Consider co-founder matchmaking platforms as a starting point, but remember you need to work together under pressure to truly test compatibility.

3. Join business incubators and accelerators where you can observe people in action and learn about their reputations.

4. Use social media strategically to connect with like-minded entrepreneurs, but understand this only provides leads.

5. Leverage your personal networks, especially alumni connections, for honest perspectives on potential partners.

Remember, the decision about who your co-founders will be is one of the most consequential choices you'll make. Don't rush it, and keep your standards high. Even with the most rigorous selection process, not all founding relationships work out long-term—but that shouldn't stop you from trying to build the strongest possible team.

The Hard Truth About Profit vs. Purpose

Please don't start a company just because you have an idea or technology. That's like deciding to run a marathon because you thought it would be nice to go for a run on a sunny day. You won't last.

What you need is obsession, not just passion. Entrepreneurship requires a driving commitment that will sustain you through inevitable challenges.

If your answer to "Why are you starting this company?" is simply "to make money," you're missing the point. That's profiteering, not entrepreneurship. You won't build a great company, and your team won't stay the course through the inevitable ups and downs.

Making a profit is certainly necessary for sustainability, but it should support your primary mission rather than be the mission itself.

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Moving Forward: The Search for Specificity

Once you have your idea or technology and enough of a founding team to begin, you're ready to enter what entrepreneurs call "The Search for the Holy Grail of Specificity."

Entrepreneurship isn't abstract—it's intensely practical and detailed. Winners get the specifics right, diving deep into market segments, identifying precise customer needs, and developing targeted solutions.

Remember, you don't need a perfect idea or team to start—just enough to begin the journey with confidence and excitement. The process itself will refine both your concept and your team over time.

What truly matters is whether you have the informed passion—or better yet, the obsession—required to make your venture successful. Because in the end, it's not just about launching a business; it's about creating something meaningful that makes the world better.

The path won't be easy, but for those with the right mindset and commitment, it offers the chance to build something truly extraordinary.

Now, if you’re a founder who needs help figuring out your ideal customer profile and walking through this process in more detail, I’m here for you… Get in touch.

→ I want to get unstuck, let's talk

Most founders build SaaS funnels backward.

They study what $100M companies do today, copy their strategies, and wonder why conversion rates stay flat.

What those companies do now isn't what got them there.

The real key to any marketing is not doing what others do. It’s knowing your customer.

So, let's break down how to build a funnel that actually converts by starting with the foundation: understanding your customer deeply.

The Foundation: Customer Understanding

You need to know who you're serving, the emotional words they use when describing the problem, how they want their problem solved, and how they talk about all of it.

Start with the customers you have.

Don't have any? Start with your target market - find the Facebook group, sub-Reddit, Twitter community, or other places they frequent.

Customer Research Done Right

Read “The Mom Test” by Rob Fitzgerald to understand how to frame your questions without your ego, and why that's so important. Then use Katelyn Bourgoin's Clarity Calls Cheatsheet to get practical examples of questions to ask.

You need to understand (1) their current state (prior to buying your product), (2) their desired state (after they use it) (3) the emotions involved in triggering buying decisions (4) the catalysts that drive purchase decisions.

This knowledge will tell you:

• What to say (emotional conversion words)

• Where to say it (distribution channels and watering holes they frequent)

• Who to say it to (and who to listen to)

• How to say it (current → desired state)

• When to say it (the catalyst for buying)

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Building Your Funnel

Once you understand your customer deeply, your funnel naturally falls into place.

Here's how to structure it:

1. Top of Funnel: Content That Converts

Your content should focus on where your customers already are.

Based on successful SaaS companies, your early customer acquisition will likely come from:

• Direct outreach (40% of early customers)

• Content marketing (35%)

• Beta and launch lists like Product Hunt & their competitors (25%)

As you grow to 500+ customers, this starts to shift to something more like:

• Organic search & partnerships (45%)

• Referral program (30%)

• Paid acquisition (25%)

2. Middle of Funnel: Nurturing Strategy

Go to where your prospects live/congregate, or better yet, partner with those who already have your customers as their audience.

Speak to them using their own words.

Your messaging should consistently demonstrate your understanding of their current state, a clear path to their desired state, and evidence you can help them get there.

3. Bottom of Funnel: Conversion Optimization

Focus on three core metrics:
1) Time to first value (get this as low as possible)
2) Core feature adoption rate
3) Customer success metrics specific to your product

That’s it.

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So, what do I do now?

Take these steps today:

1. Start a relationship with your target market (either your best customers today or even someone else’s customers in your space)

2. Ask them open-ended questions about their buying behavior and what they do and where they do it online.

3. Document their exact words and look for patterns.

4. Use their language in your marketing all throughout their buying journey.

Remember: Tactics without empathy won't save you. Knowing your customer will tell you exactly what to do next.

Now stop reading and talk to a customer. Or, if you’re a founder who needs help figuring out your ideal customer profile and walking through this process in more detail, I’m here for you… Get in touch.

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Ever notice how most scaling advice feels like it was written for venture-backed startups with millions in funding?

That's because it was.

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The reality for bootstrapped Micro-SaaS founders is different.

You can't burn cash acquiring customers. You can't hire a team of developers. And you definitely can't wait 18 months to figure out product-market fit.

But here's what most founders miss: scaling a Micro-SaaS isn't about doing everything the big players do, just smaller. It's about doing fewer things, but executing them perfectly.

After working with dozens of bootstrapped founders and analyzing data from successful Micro-SaaS companies, I've noticed clear patterns in what actually drives sustainable growth from 0 to 1000 customers.

Let's break it down.

Why Most Fail to Scale

The reasons for failure to scale are surprisingly consistent:

1. Premature scaling (spending before validation)

2. Poor unit economics (CAC > LTV)

3. Weak product-market fit

4. Ineffective pricing strategy

But here's what's interesting: the minority that succeed follow a remarkably similar playbook.

A lot has already been said about validation and product-market fit.

So, let’s assume you have validation already (i.e., build where there is already competitors), here's how to scale systematically (and here’s a more detailed article on How to Win at Micro-SaaS):

Customer Acquisition Strategy

Your first 100 customers will come from different channels than your next 900.

Here's a progression that works:

0-100 Customers:

• Direct outreach (40% of early customers)

• Content marketing (35%)

• Product Hunt / beta and launch lists (25%)

100-500 Customers:

• Word of mouth (40%)

• SEO-driven content (35%)

• Strategic partnerships (25%)

500-1000 Customers:

• Organic search & partnerships (45%)

• Referral program (30%)

• Paid acquisition (25%)

Pricing Optimization

Based on data from successful Micro-SaaS companies, here’s some thoughts to work with:

• Start with 3 tiers

• Price middle tier at target customer's willingness to pay

• Set top tier at 2.5x middle tier

• Bottom tier at 0.4x middle tier

Common Pitfalls and Solutions

1. Premature Channel Expansion Solution: Start by trying everything, but as quickly as possible, figure out what works best and focus on that one channel as long as possible.

2. Poor Unit Economics Solution: Track CAC payback period and adjust acquisition strategy accordingly.

3. Weak Onboarding Solution: Implement success milestones, track time-to-value, work to lower it to as fast as possible.

4. Pricing Too Low Solution: Test price sensitivity with new customers while grandfathering existing ones.

Remember: Scaling isn't about doing everything at once. It's about doing the right things in the right order.

Start with validating product-market fit. Move to systematic acquisition. Build retention systems. Then optimize for scale.

Your first priority isn't growth - it's building something worth scaling.

What's Next?

Take these steps:

1. Audit your current metrics

2. Identify your biggest gap

3. Focus exclusively on that gap for the next 30 days

4. Share your results and learnings

Remember, sustainable growth comes from systematic execution, not random tactics.

Now stop reading and start implementing.

QUICK NOTE: If you're generating consistent revenue but haven't scaled your marketing spend, you might be leaving money on the table too.

Want help figuring out your scaling potential?

I'll help you identify which marketing initiatives you should scale, help your marketing lead understand the models, and give them a system to scale up too.

If you're a $1-5M/year founder who needs help getting to the next level, get in touch today.

→ I want to get unstuck, let's talk

Ever wondered why some products captivate users instantly, while others leave them puzzled?

The secret often lies in the Time-to-Aha—the duration it takes for a user to experience a product's core value. Some call this “Time to Value”, or TTV for those of you at parties who want to bore someone.

It might be boring at parties, but … wait for it … research indicates that SaaS companies optimizing this metric can significantly boost conversion rates.

Let’s get to what it is, why it matters, and how to reduce it so you can increase your trial-to-conversion rate…

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What is Time-to-Aha?

Time-to-Aha measures the interval from a user's initial interaction to the moment they first realize the product's core value—the Aha! moment.

This is when users understand why they need your product and how it benefits them.

Examples from Successful SaaS Companies:

• Calendly: Users can create and share their first calendar link within minutes, showcasing the platform's scheduling efficiency. Time to aha is supposedly < 3 minutes.

• Loom: Enables users to record and share their first video swiftly, highlighting seamless communication. Target is < 2 minutes.

• Notion: Allows users to create and share a page promptly, demonstrating its collaborative capabilities. Ideally this happens in less than 4 minutes.

These companies have streamlined their onboarding processes to ensure users quickly experience the product's value, often within minutes.

Why Time-to-Aha Matters

A shorter Time-to-Aha correlates with higher conversion rates and improved user retention.

According to OpenView's 2022 Product Benchmarks Report, product-led growth (PLG) companies that focus on delivering value quickly are more likely to achieve rapid and efficient growth.

That’s you, right?

You want to achieve rapid and efficient growth. I’m sure of it. It’s why you’re still here, reading this.

Keep going to get the dirty details in bullet point format.

How to Measure Time-to-Aha

1. Define Your Aha Moment:

• Identify the first meaningful outcome users achieve.

• Determine when they first experience your core value proposition.

• Pinpoint actions that correlate with long-term retention.

2. Track Key Metrics:

• Time from signup to the first core action that gives the user their meaningful outcome.

• Track the percentage of users reaching the Aha moment.

• Track the drop-off points in the activation journey.

• Track the user paths leading to the fastest activation.

3. Segment Your Data:

• By user type or plan.

• By acquisition channel.

• By onboarding path taken.

• By feature first used.

Tools to Assist:

• PostHog: For event tracking and user paths.

• Mixpanel: For funnel analysis.

• Amplitude: For cohort analysis.

Strategies to Reduce Time-to-Aha

Yea, I’m still doing bullet points so you can get, ahem, the point, quickly.

Try any or all of these to reduce your time-to-aha.

1. Streamline Registration:

• Eliminate unnecessary form fields.

• Offer social sign-in options.

• Pre-fill obvious values.

• Defer non-critical setup steps (according to the user getting the value)

2. Optimize Onboarding:

• Create guided paths for users.

• Use intelligent defaults to reduce decision fatigue.

• Show progress indicators to keep users motivated.

• Celebrate small wins (and the Aha! moment) to encourage continued use.

3. Reduce Technical Friction:

• Provide one-click integrations.

• Offer sample data for users to experiment with.

• Auto-configure common settings.

• Include concise video tutorials (send these as emails or put in the onboarding spots where people might usually get hung up)

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Advanced Optimization Techniques

To further refine your Time-to-Aha, consider implementing advanced optimization techniques.

Start with progressive disclosure by introducing only the essential features initially, then gradually revealing more advanced options as users grow comfortable. Doing things like this with step-by-step guidance helps users make progress without feeling overwhelmed.

Another option is to leverage smart defaults to simplify choices and speed up decision-making.

Pre-select common options, offer templates tailored to typical use cases, and suggest recommended settings based on user behavior to create a seamless onboarding experience.

Finally, incorporate success triggers to motivate and engage users.

We all like that dopamine hit we get when someone confetti plays the first time. Surprise and delight them.

Automate congratulatory messages when milestones are achieved, award badges to recognize progress, and set progress milestones to encourage continuous use.

And if you really want to go the extra mile to build trust and inspire confidence, integrate social proof elements such as testimonials or user success stories throughout the journey.

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Warning Signs to Watch For:

• > 50% of users never reaching the Aha moment.

• Support tickets about basic setup issues. Every one of these is a to-do item to fix something that’s unclear.

• Frequent trial extension requests. I mean, maybe you have an audience who just likes to ask for free stuff and deals all the time, but it also might mean they’re just not quite getting it and you have some work still to do.

• High bounce rates on critical setup pages.

Final Thoughts

Reducing Time-to-Aha is a game-changer for improving conversions and customer retention.

Start by understanding your user's journey, removing friction points, and iterating based on data.

Remember: Every minute shaved off Time-to-Aha is another user more likely to convert.

Now, go create those Aha! moments for your users.

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Next Steps…

If you're generating consistent revenue but haven't scaled your marketing spend, you might be leaving money on the table too.

Want help figuring out your scaling potential?

I'll help you identify which marketing initiatives you should scale, help your marketing lead understand the models, and give them a system to scale up too.

If you're a $1-5M/year founder who needs help getting to the next level, get in touch today.

→ I want to get unstuck, let's talk

Want to know the most expensive mistake bootstrapped SaaS founders make with marketing?

They try doing everything at once.

Industry data shows early-stage SaaS companies typically spread their limited resources across too many channels, getting mediocre results everywhere instead of exceptional results somewhere.

But, the pattern is clear.

Successful companies break through early revenue plateaus by mastering one channel at a time.

They turn content into a conversion engine, not just a blog.

They make their product do the selling.

They transform customer stories into acquisition machines.

So, let's break down exactly how to execute each strategy, with frameworks and processes you can implement even with a small budget.

1. Content as Your Growth Engine

2. Product-Led Growth That Actually Works

3. Customer Success Stories That Convert

4. Referral Programs That Drive Growth

5. SaaS-Specific Paid Advertising

NOTE: This article is only about marketing strategies, not sales. If your acquisition strategy is primarily sales-led, just skip this article and talk to my friend Scott Cowley, or read his article about Building a Sales Pipeline that Converts. Otherwise, the only part of this that covers sales is in the Paid acquisition strategy. Delivering a lead to a sales team can be helpful there, but it’s also not necessary, so edit as you see fit.

Ok. Let’s go. No more fluff, no theory - just what works when you're bootstrapped. 🚀

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Choosing Your Primary Growth Channel

EDIT: This article ended up being insanely long.

So, I made a cheat sheet for you. Instead of forcing you to read all of it, I suggest you do this quick little evaluation on your product and choose the strategies that are best for you.

THEN go and read the appropriate strategies.

I mean, do what you want, but I’m all for TLDRs and stuff.

Here ya go….

Let's be practical about this decision. Rather than trying everything at once, here's a framework to help you choose your starting point.

Answer these questions in order:

What's your current MRR?

$0-1k: Start with Content or PLG
$1k-5k: Any strategy except Paid
$5k-20k: Any strategy

What’s your available budget?

$0-500/mo: Content or PLG
$500-2k/mo: Content, PLG, Success Stories, or Referral
$2k+/mo: Any strategy including Paid

What’s your product’s time-to value?

< 1 hour: Product-Led Growth (because you don't need paid)
Same day: Success Stories or PLG (because you don't need paid)
Multiple days: Content or Paid (watch your payback period!)
Weeks+: Success Stories or Paid (watch your payback period!)

What’s your target customer’s research process?

Technical evaluation: Content
Quick solution needed: PLG or Paid
Peer recommendations: Success Stories or Referral
Complex purchase: Success Stories or Content

What’s your team’s core strength?

Technical expertise: Content
Product experience: PLG
Sales/Marketing: Paid
Strong network: Referral

Priority Matrix

Score each channel based on your answers:

• Matches 4-5 criteria: Primary channel

• Matches 2-3 criteria: Secondary channel

• Matches 0-1 criteria: Avoid for now

Example Scoring:

Scenario: $3k MRR, $1k budget, same-day value, technical evaluation, technical expertise

Content: 5/5 (Primary)
PLG: 4/5 (Secondary)
Success stories: 2/5 (Not yet)
Referral: 2/5 (Not yet)
Paid: 1/5 (Avoid)

Remember: This framework is a starting point, not a rule book. Your specific context may require adjustments, but it provides a structured way to make this important decision.

Ok, let’s focus on the Primary? Scroll to your Primary strategy, implement it, and win!

Here’s that table of contents again, to help you get there faster:

Strategies:

1. Content as Your Growth Engine

2. Product-Led Growth That Actually Works

3. Customer Success Stories That Convert

4. Referral Programs That Drive Growth

5. SaaS-Specific Paid Advertising

Get in there!

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Strategy 1: Content as Your Growth Engine

According to Open Benchmarks from Baremetrics data from bootstrapped SaaS companies, here's what a successful content funnel looks like:

Content Funnel Metrics Standards:

Blog visit → Email signup: 2-5%
Email → Trial signup: 15-20%
Trial → Paid conversion: 8-9%

Here’s the details (where the devil is) for this path…

Stage, Definitions, and Target Metrics:

Blog Visit

Ideally to count a “blog visit” it would mean the visitor spent at least 2 minutes on the page and scrolled at least 50% of the way down the content. You alternatively count it a visit if they clicked or engaged with code samples or demos if they are on the page. In the end, we want them to have read and/or engaged with the content. That’s a visit.

Blog Visit → Email Signup: 2-5%

At this stage we want the user to do something in trade for their email address. They could download something like a technical resource or lead magnet, or just subscribe to your newsletter or a 7-day email course. Whatever the case, we’re looking for 2-5% conversion rate from a blog visit (as defined above) to an email signup, so you should have a call-to-action (CTA) on every blog post.

Email → Trial Signup: 15-20%

The 15-20% conversion rate might seem high at first, but the reason we want this is because anything less means we’re not attracting the right people higher up the funnel (your blog traffic or your promise with the email signup is wrong). So, if you’re not getting this rate, fix your traffic sources or how you’re conveying the value of what you’re delivering when you get their email address.

A trial signup isn’t a trial signup unless they: (1) create an account, (2) verify their email and (3) completes some basic next action like setup their profile or do the first activity in the onboarding sequence. Anything less, and I wouldn’t count it as a trial signup because they aren’t actually using the product at all. If you have to email them to prod them into activation, do it. Then count that as a trial signup.

Also, this is a good place to start keeping an eye on the sources of traffic that brought these trial visitors in. It’ll be more important in the next stage, but without having paid conversion data, if you just launched, use the trial signups to get a hypothesis going.

Trial →Paid Conversion: 8-9%

Again, this might seem relatively high at first glance. But, again, if you’re not getting this rate, something is wrong with your traffic or your offer. Fix those and this metric will grow too.

The definition is straightforward - did you get that nice little alert that means you made that sweet sweet internet money? If so, count it.

Now the trick is to keep them happy. But we’ll talk about churn another day. That’s not what this article is about.

One thing I would say you want to track and improve here, however, is your time to conversion. How long does it take a user to go from trial to paid?

Improving this influences your cash flow, but also your user’s positive experience of your product. Remove everything in the way of this conversion metric. Get them the value as fast as possible and you’ll do well.

NOTE: Look for another article coming soon about “Time-to-Aha” (or what boring people call “time to value”)!

ANOTHER NOTE: These conversion rates are examples from B2B SaaS companies with average customer LTV of $1,100. Your metrics will vary based on factors like pricing tier, sales cycle, and product complexity.

Implementation Steps:

Every week you should write an article, tutorial, or something shareable and valuable. Post it. Don’t forget the CTA!

Week 1-2:

• Set up content analytics tracking

• Create content calendar mapped to features

• Write first 2 tutorials/posts & publish

• Define your success metrics for each stage (see above if you need some industry benchmarks to shoot for)

• Start building/writing downloadable resources

Week 3-4:

• Look at your conversion & engagement metrics

• Launch whatever it is they’ll trade their email for and/or email nurture sequence

• If you have > 30 (true) visits, consider testing changes based on the early data. Better if you have > 100. Definitely test some changes if you have > 300.

• Continue building/writing downloadable resources

Week 5-8:

• Add downloadable resources as a potential CTA where it makes sense (don’t add more than 1 CTA per page though)

• A/B test formats and CTAs if you have enough traffic (ideally 100+ visits / week). Don’t multi-variate split test unless you can send 300+ visits to each variation per week.

• Analyze drop-off points of your funnel. The biggest drop-off percentage is what to focus on. Don’t worry about the rest, just focus on fixing the biggest drop-off step only.

Week 9-12:

• Analyze channel / source metrics. Look for which source of traffic is getting the most trials (or ideally conversions). Again, you’re statistically significant (at 65% confidence) when you get > 30 conversions from a source. Better to get 100. Best to get 300. But you can start make new hypotheses and/or decisions starting at 30 if you find huge disparities between sources.

• Optimize the conversion path again. Same as the last couple weeks. Look for the step with the biggest drop-off percent. That’s your focus until it’s not the biggest drop-off step anymore.

• Plan content expansion. Consider using the Content Pillar strategy here.

• Document successful formats, and keep writing them.

Critical Metrics to Watch:

• Time to first conversion. This is from the moment the user hit your first page till the moment they converted. The goal is to lower this time down as much as possible (by focusing on the biggest bottleneck, as described above).

• Email sequence performance. If you track opens (not always good to do as some email clients consider the tracking pixel an indicator of spam), this will tell you how good your subject line is. Nothing more. Nothing less. If you track clicks, which you definitely should, it’ll tell you how good your body copy is. The conversion from your email will tell you how consistent your copy is from subject to body to landing page, all the way through. It’ll also tell you whether or not your offer is compelling.

Strategy 2: Product-Led Growth That Actually Works

Here’s what successful PLG funnels average out at - so, some targets for you.

User Journey Conversion Rates:

Signup → First value: 60%
First value → Core features: 45%
Core feature → Success milestone: 25%
Success milestone → Paid conversion: 4-8%

Here are the stages and some definitions to work from too:

Signup → First value: 60%

How many of the people who create an account actually get some value out of the product? This is what you’re tracking here.

Set the primary objective/goal where you know the user is getting something of value. Track how many people actually reach that goal. Shoot for 60% or better.

And, try to get them that value well within a 48 hour window. That would be considered “best in class” by ProfitWell/Paddle’s benchmarks.

If they haven’t activated in 4 days, you can likely consider them a lost cause. They’ve already moved on or the pain wasn’t deep enough for them to move quickly.

For example, a social media scheduling tool should aim to have get 60% or more of their users to schedule their first post within 48 hours.

First value → Core feature adoption: 45%

You should already know the core features you have that will provide the most value to the most of your users. It’s not a list of every feature.

Aim to get 45% of your trial users to tick the boxes of having experienced the product’s main features within 3-7 days. They should be integrating it into their workflow and coming back regularly.

This is where DAU (daily active users) metrics come in handy. Just be sure you define “active” according to your product.

If you had an analytics tool, you’d want 40% of your trial users to have setup custom dashboards within 3-7 days that they’d be coming back to check often.

Core feature adoption → Success milestone: 25%

25% of your users should have a meaningful outcome and established usage patterns within 7-14 days.

For example, perhaps the usage pattern is inviting a team member or expanding their usage. These can be leading or lagging indicators. For a CRM, you might consider the user importing and organizing their first 100 contacts a success milestone because it indicates your product is solving their pain. They’ve expanded beyond the first few contacts they’d add to test the product.

Success milestone → Paid conversion: 4-8%

Calendly had a Free-to-paid conversion rate of about 5% at their IPO. Datadog was at about 4%. So, that should be your target. If you get better than that, and keep them, you’re crushing it.

Most of your conversions will likely happen around 2 weeks out. That’s the middle of the bell curve for trial to paid timing.

Ideally once they’ve converted to a paid plan, if your pricing is value-based, you’ll start to find power users expanding their usage into higher tiered plans. Importantly, they should be getting more and more value out of expanded usage.

They’re baked in.

NOTE: These metrics represent boostrapped B2B SaaS companies with monthly pricing between $50-200. Companies with higher price points typically see lower conversion rates but higher LTV (lifetime value), while those with lower price points often see higher conversion rates but need greater volume.

Implementation Steps:

Week 1-2: Onboarding Setup and Tracking

• Setup product analytics for tracking the user journey (I prefer Posthog for this)

• Map critical features to success outcomes

• Understand and document the “aha moment” and when you can say a user has had it.

• Create the onboarding checklist to get the user to that “aha moment”. Remove as many steps as you can to get the timing as low as possible, but without sacrificing the necessary steps to get a user to that moment.

• Document the conversion points and start tracking the drop-off rates

Week 3-4: Activation Path Development

• Build the streamlined first-user experience

• Add progress indicators for the user to do key actions that lead to adoption and getting that “aha moment”

• Add automated onboarding emails based on these key actions, if they didn’t complete them, to nudge them along the path.

• Create in-app guides for core features that can be sent to users who are struggling with a step.

• Setup reactivation triggers to deliver these guides and insights. Keep delivering value to them - how to get what you promised they could get by giving you their email.

Week 5-8: Optimization and Testing

• A/B test onboarding variations.

• Analyze the drop-off points. Focus your energy on testing and fixing the worst performing step in the funnel until it’s no longer the worst step.

• Add contextual help content to the user’s process, if needed.

• Implement user behavior tracking (again, Posthog has this)

• Create segment-specific paths. Look for what problem they are there to solve as to how to segment.

Week 9-12: Scale and Adjust

• Review all steps of all conversion metrics and funnels.

• Look to remove all friction points along the user’s journey.

• Scale up when you find a flow is successful. Send more people through that path when and where relevant.

• Plan expansion features. When you’ve solved someone’s problem, you’ve likely created a new problem. Solve that for them too.

• Document best practices and systematize. Automate where you can. Administrate where you can’t automate.

Strategy 3: Customer Success Stories That Convert

According to MicroConf's State of Independent SaaS data, word-of-mouth and customer references drive 22% of bootstrapped SaaS growth. Here's how successful companies structure this channel:

Customer Success Story Funnel:

Success story published → Prospect engagement: 5-10%
Prospect engagement → Sales conversation: 40-50%
Sales conversation → Trial: 25-30%
Trial → Paid: 15%

Note: These conversion rates come from bootstrapped B2B SaaS companies. Unlike content marketing or PLG, success stories typically drive lower volume but higher quality leads, resulting in better conversion rates.

Success story published → Prospect engagement: 5-10%

With this strategy, you’ll be creating case studies. So, when a case study goes live and is distributed across all your channels you should be tracking views, time on page, and scroll depth.

Target 5-10% of the visitors to your case study turning into engaged prospects.

An engaged prospect is one that downloads/reads the entire case study and requests more information. They might sign up for related webinars or demos.

You’ll want to know the download rate, email open rate, and/or response rate to understand where how to increase this prospect engagement rate.

Prospect engagement → Sales conversation: 40-50%

When we have an engaged prospect, we want to get them into a sales call. You should aim to get 40-50% of your engaged prospects into those calls.

This means they’ll book a discovery call and/or attend a demo.

To know where the process is working or not, track your show-up rate, call duration, and follow-up rate.

Sales conversation → Trial signup: 15-20%

After the sales conversation, if you have a trial period, you’ll want 15-20% of those sales conversations to convert to trials. I’ve seen as high as 50%, but this is a good starting point as you grow.

What you’re looking for here is not just them to trial it, but similar to other user activation steps described in other strategies, you actually want to count those who have started the trial AND completed initial setup. You may even want to count them only if they’ve experienced the first step of the “time to aha” process.

To get better at this step, track implementation progress, feature usage, and engagement with however your product is setup.

Trial signup → Paid conversion: 4-8%

If the previous steps are coherent and connected, and the offer is on point, hitting a pain and solving it the way they want it solved, you should see a trial-to-paid conversion of 4-8%.

Often times, if they get to that “aha moment” super quickly, users will skip lower tiers entirely and jump straight to higher tiered plans.

To see how well you’re doing in this stage, track which plans your customers are choosing immediately after trial, time to conversion, and initial contract value.

Implementation Steps

Week 1-2:

• Identify top 5 successful customers

• Create a case study template

• Conduct the customer interviews

• Document the implementation journey you’ll be building

Week 3-4:

• Write the initial case studies

• Create the distribution plan of where and how you’ll promote them

• Setup tracking systems for the funnel

• Build up any sales enablement materials you’ll need

Week 5-8:

• Launch the first 2-3 case studies (with CTAs on them!)

• Track the engagement metrics

• Create the follow-up sequences

• Create and launch tests of different formats if you have enough traffic to do so with statistical significance (ideally 100+ visitors per case study per week at least)

Week 9-12:

• Analyze the conversion data & focus on the worst performing part of the funnel.

• Use the best performing format (if you’ve tested them)

Note: These metrics represent typical results for B2B SaaS products priced between $50-500 monthly. Enterprise products often see longer sales cycles but higher conversion rates, while lower-priced products typically need higher volume at each stage.

Strategy 4: Referral Programs That Drive Growth

Well-structured referral programs can generate 15-25% of new customers for bootstrapped SaaS companies. Here's how successful referral funnels work:

Referral Program Funnel:

Customer base → Active referrers: 10-15%
Active referrers → Referred leads: 30-40%
Referred leads → Trial: 20-25%
Trial → Paid: 12-15%

Note: These conversion rates reflect bootstrapped B2B SaaS companies. Referral programs typically produce higher quality leads than cold acquisition channels, resulting in better conversion rates and longer customer retention.

Customer base → Active referrers: 10-15%

These should be active, paying customers. They should have at least 60 days of usage, and should be defined, to you, as your Ideal Customer Profile (ICP) and receiving value regularly from your product.

Check your customer satisfaction scores, product usage, and engagement levels to see who would be a good referrer. Use the top 10-15% of your customer base.

Hopefully 10-15% of your customer base will opt into your referral program and share a unique referral link.

Check your participation rate, sharing frequency, and referral quality to see what’s working and what’s not.

Active referrers → Referred leads: 30-40%

Finding who you think would be an active referrer and who actually brings in leads are usually drastically different. Aim for 30-40% of those willing who will actually send in leads.

Note that you very will could find the Pareto Principle (80/20 rule) here as well, where 20% of your “referrers” are driving 80% of your referred leads.

A referred lead should be someone who clicked the referral link and engages with the product info. They might not have signed up for a trial or become a paid member yet. That definition is used for payouts, but for internal use, let’s say they are just engaged.

To see where the process is working or not, keep an eye on click-through rate, page engagement, and qualification rates.

Referred leads → Trial signup: 20-25%

If your active referrers are talking about the product in a way that resonates with the lead, you should find a 20-25% trial signup rate challenging, but doable.

These people will start the product trial, complete the onboarding, and use the first core feature that leads to their “aha moment".

Double check time-to-activation, feature adoption rates, and engagement depth to make sure you’re not leaving anything on the table with leads you want to become trial users, using our definition here.

Trial signup → Paid conversion: 12-15%

If everything has gone well so far, and you’re helping trial users get to that “aha moment” quickly, you should get a 12-15% conversion rate from trial to paid.

Many times you’ll find the converted user will match the referrer’s tier here. This is another reason you want your best customers referring you in the beginning of this funnel.

Keep an eye on conversion rate, initial plan choices, and time to conversion to see where any issues might exist in the process from trial to paid conversion.

Implementation Steps:

Week 1-2:

• Define the referral program and reward structure. What’s the commission amount? When will you pay out? What is considered a conversion that counts for a referral trigger?

• Set up tracking systems. (I have used Rewardful successfully in the past, but there are plenty of other options out there too. Some are industry specific, which can be helpful.)

• Create referral materials. A critical mistake many founders make with referral programs is not creating material for their affiliates. Don’t make this mistake. Give them things that are shareable, something that makes them look good, not sleazy. Don’t overdo it, but do something.

• Select your potential ICP from within your current customer base.

Week 3-4:

• Launch to a test group of your potential referrers. Get basic metrics and feedback about your referral materials and what they think is compelling to share. Help them help you and gather that feedback into one place.

• Adjust incentives and structure as needed.

Week 5-8:

• Roll out to full customer base, or the ICP inside your customer base.

• Implement automated rewards whenever possible (tip: Rewardful does not do automated payouts, which is the downside to going with them even though they do other things really well).

• Track program metrics and iterate on referral materials as needed.

Week 9-12:

• Analyze performance data. Adjust user journeys as necessary.

• Optimize reward structure to incentivize based on the best referrers, how they market you, what they say, and how the leads they referred in are converting.

Note: These metrics are typical for B2B SaaS products with average customer LTV between $500-2000. Products with higher price points might see lower participation rates but higher-value referrals, while lower-priced products typically need higher volume of referrals to achieve meaningful impact.

Strategy 5: SaaS-Specific Paid Advertising

Stripe's report on early-stage SaaS companies (<$1M ARR), as bootstrapped-specific advertising data is limited, but these metrics represent companies spending $1000-5000 monthly on ads. I thought it was good enough data to include and use in this strategy.

Paid Acquisition Funnel:

Ad impression → Click (landing page visit): 1-2%
Landing page visit → Trial conversion: 20-25%
Trial → Paid: 8-10%

Ad impression → Click (landing page visit): 1-2%

If you’re able to target the right person with a proper audience match and a clear and compelling offer, you can expect 1-2% conversion on ads over time. It could be higher at first and drop off thanks to banner blindness and ad fatigue, but 1-2% is a good average target over the course of a campaign.

Make sure you’re tracking CTR (click-through-ratio), frequency, and audience overlap to start. But also, to make sure you’re getting quality traffic, make sure you’re getting > 30 seconds time on page from that traffic and they’re coming from geographically relevant locations.

Track the bounce rate, engagement, and scroll depth if you want to go deeper into the quality of a traffic source.

Landing page visit → Trial conversion: 20-25%

A good conversion rate with ads is 20-25%. Less than that and you have some work to do.

Consider refining what a “trial conversion” really is beyond just a user signing up.

Trial → Paid: 8-10%

As with other strategies, you want those who are in a trial to get to that “aha moment” as fast as possible. The best trial accounts will not only sign up, but complete the initial setup and experience the first core feature or step along the “aha moment” path.

If your activation rates, feature usage, and support requests are on target, you should see an 8-10% conversion rate from trial to paid.

Additionally, as always, watch your CAC (customer acquisition cost), time to conversion, and initial plan value to make sure you’re getting the right people in the door.

Implementation Steps:

Week 1-2:

• Create initial ad sets based on verbiage your ideal customer profiles use. How do they speak about your product? If you don’t know, don’t run ads right now. Do some customer interviews first and/or choose a different strategy.

• Build landing pages using your customer’s own words. Highlight the pain and the solution. Use testimonials, logos, and remember people buy with their emotion and justify their purchase with “logic”. So, use emotional conversion words (something I will likely write about another day as this is so important to get right).

• Define your success metrics. I mean, I gave a bunch throughout this article, so there’s a starting point for you. But your mileage may vary. Adjust according to your industry and what you know about your customer.

• Set up conversion tracking inside all the ad platforms and on your site in the appropriate places. Test this thoroughly before turning on the spend.

Week 3-4:

• Launch test campaigns (please, for the love of all that is good in the world, start slow and small)

• Monitor key metrics. Look for where you’re not seeing conversions and test the pixels or tracking tools. Pause the campaign if needed. Get them fixed.

• Adjust targeting if needed. Split your campaigns into smaller groups to get a tighter target.

• Optimize landing pages. Use Posthog or another screen recorder to see where people get confused, what they click on, and how long they stay on the page.

Week 5-8:

• Scale working campaigns. This is the fun part. Cut the stuff that isn’t working and double down on what is working well.

• A/B test messaging to get even better. Always Be Testing!

• Refine audience targeting even more. Again, chop up ad groups into smaller groups to understand the best converting audience and get hyper targeted on them.

• Track CAC (customer acquisition cost) by channel. Aim to reduce that cost without losing high quality leads.

Week 9-12:

• Analyze channel performance. Again, double down on what’s working. Cut what’s not working. Target smaller segments.

• Keep A/B testing everything you can.

Note: These metrics assume a product priced between $50-200 monthly. Higher-priced products typically see higher CAC but better ROAS, while lower-priced products need significantly better conversion rates to maintain profitability.

Warning Signs of a Bad Campaign:

• CAC exceeding 4 months of customer revenue. This is arguable, but remember that your business runs off of cash flow. The best thing is to have more revenue than it costs to acquire the customer. Second best thing is for your LTV (lifetime value) to be greater than your CAC. But LTV > CAC (without cash coming in the door first) means you’ll need someone else’s cash to scale up. And that’s a different discussion for a different day. This article is already too long.

• Conversion rates below 5%. I mean, it can be done. I’ve seen it. But a conversion rate this low means something is wrong and you’re likely burning money. Try to figure out what discontinuities you have in the ad to conversion messaging before you continue. Or, check that your offer is actually compelling (read up on Hermozi’s “Grand Slam Offer” if you need to fix your offer)

• Ad fatigue within first week. This usually means your source isn’t going to be sustainable. You could likely spend your time somewhere else and have a better chance of having a more evergreen campaign running. You’d be optimizing your time better if you spent it elsewhere if you’re getting ad fatigue (a drop-off of your click-through rates) in the first week. Something is wrong here.

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Putting It All Together…

The data is clear: successful bootstrapped SaaS companies don't win by being everywhere - they win by being exceptional somewhere.

Your path forward should look like this:

1. Choose your primary channel using the decision framework

2. Execute that single channel for 90 days.

3. Only add a second channel when you have:

   • Predictable acquisition metrics

   • Automated tracking systems

   • Resources to expand without diluting focus

   • Clear evidence of channel saturation

Remember: Your goal isn't to follow every trend or be on every platform. It's to acquire customers profitably and sustainably.

Start with one channel.

Master it.

Then expand methodically.

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Next Steps

If you're generating consistent revenue but haven't scaled your marketing spend, you might be leaving money on the table too.

Want help figuring out your scaling potential?

I'll help you identify which marketing initiatives you should scale, help your marketing lead understand the models, and give them a system to scale up too.

If you're a $1-5M/year founder who needs help getting to the next level, get in touch today.

→ I want to get unstuck, let's talk

We’d have to get board approval to spend more than that.

Those words from the marketing manager of a $2M per year company stopped me in my tracks. We were reviewing their analytics, and we just found they were getting a 10:1 return on ad spend.

Let that sink in.

For every dollar they spent on marketing, they were making ten dollars back.

And they weren't planning to massively scale their spend.

And, I don’t believe this is an isolated incident. After working with many companies in the $1-5M ARR range, I've seen this pattern before.

Maybe you’re one of them experiencing this?

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The $500k Pattern

These companies share striking similarities:

• Healthy growth, or perhaps some stagnation in the short term

• Recently hired or inexperienced (but obviously smart) marketing lead

• Strong product-market fit

• Positive unit economics

• Conservative marketing spend

On paper, they're doing everything right. But they're leaving massive amounts of money on the table.

Let's break down the real numbers from that $2M company:

Average monthly metrics:

- Advertising budget: $1,500
- Revenue from ads: $11,500
- Customer LTV: $300
- CAC: $30

*LTV = Lifetime Value
**CAC = Customer Acquisition Cost

Marketing managers in this situation can be concerned about a few things:

1. What if we scale and the conversion rates drop? 

2. What if we saturate our market? (not a question in this case, but can be in others)

3. What if we go over our allotted budget?

Valid concerns. But let's look at the opportunity cost:

Conservative scaling scenario:

- Current annual revenue from ads: $138k
- Potential annual revenue at 4x spend: $552k
- Annual opportunity cost: $414k

Simply spending 4x more, they would have earned $414,000 more revenue this year.

Why Smart People Make This Mistake

It's not about intelligence. It's about experience and psychology.

Three factors typically drive this behavior:

1. Risk Perception Bias

   • Early-stage founders (and employees) remember when cash was tight

   • Past marketing missteps and/or lack of confidence can create overcaution

   • Focus on potential losses over potential gains

2. Data Misinterpretation

   • Looking at absolute spend instead of ROAS (Return on Ad Spend)

   • Focusing on conversion rates over total profit

   • Not accounting for customer lifetime value

3. Organizational Inertia

   • Fear of disrupting what's working

   • Lack of systems for scaling

   • Conservative budget approval processes

The Framework: Scaling With Confidence

Now, I didn’t have to use this framework with this particular company because of the seasonality of their product which was coming to a close (which is also why I’m averaging and projecting future revenues in this case), but here’s a process which can help your company scale your marketing spend without the usual anxiety:

1. Risk Reversal Testing

Before scaling broadly, run micro-tests:

• Split your best-performing campaign into 3 segments

• Increase spend by 20% on one segment

• Track metrics daily for 2 weeks

• Document everything that changes (good and bad)

Example: 

Test Results (2 weeks):

- Segment A (Control): $5,000 spend → $45,000 revenue
- Segment B (+20%): $6,000 spend → $52,000 revenue
- Segment C (Control): $5,000 spend → $44,000 revenue

2. Data-Driven Scaling

Create a scaling dashboard tracking these metrics:

• ROAS (Return on Ad Spend) by channel and campaign

• CAC (Customer Acquisition Cost) trending over time

• Conversion rate by traffic source

• Customer quality metrics (ARPU - Average Revenue Per Unit, churn)

• Market saturation indicators

Critical metrics to watch:

Red flags:

- ROAS drops below 3:1
- CAC increases >25% week over week
- Conversion rate drops >40%
- Customer satisfaction drops >15%

Green lights:

- ROAS stays above 4:1
- CAC increases <10% month over month
- New customer quality metrics are stable

3. System Creation

Document these processes:

• Campaign monitoring frequency

• Scaling thresholds

• Emergency pause criteria

• Budget adjustment protocols

• Testing procedures

Example system template:

Daily monitoring:

- Check ROAS by campaign
- Review conversion rates
- Monitor CPCs (Cost Per Click)
- Check quality scores

Weekly actions:

- Calculate blended CAC
- Review customer quality
- Adjust bids based on ROAS
- Plan next week's tests

Monthly review:

- Calculate total ROAS
- Adjust budgets
- Update scaling plans

Next Action Steps

Ok, do this… ask yourself these questions:

1. What's your current ROAS across all channels?

2. How much are you spending relative to revenue?

3. What systems do you have for scaling spend?

Red flags to watch for:

• Marketing spend <10% of revenue with positive ROAS

• No documented scaling process

• No regular testing protocol

• Fear-based decision making about spend

The Results

Here's what happened in 30 days, walking through the identification steps and turning up the dial:

Before:
- Average monthly marketing spend: $1,500
- Average monthly new revenue: $11,500
- ROAS: 7.6:1

After:
- Average monthly marketing spend: $6,375
- Average monthly new revenue: $45,500
- ROAS: 7.1:1

Yes, ROAS dropped slightly. But they're now generating an additional $408,000 in annual revenue!

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Next Steps

If you're generating consistent revenue but haven't scaled your marketing spend, you might be leaving money on the table too.

Want help figuring out your scaling potential?

I'll help you identify which marketing initiatives you should scale, help your marketing lead understand the models, and give them a system to scale up too.

If you're a $1-5M/year founder who needs help getting to the next level, get in touch today.

→ I want to get unstuck, let's talk

Ever notice how most SaaS dashboards feel like they were built for someone else?

That's because they were.

They're typically either built for massive enterprises with dedicated data teams, or VC-backed startups measuring their burn rate.

The rest of us are left cobbling together metrics from multiple tools, trying to figure out what actually matters.

But what about those of us who still need practical metrics we can actually use to make decisions?

Today, I'm sharing a spreadsheet template I use with founders. It's designed for bootstrapped SaaS companies making between $20k-100k MRR.

But first….

Why Track Metrics at All?

My first SaaS tracked everything. Literally everything.

Page views, users, sessions, time on site, bounce rate, social shares... you name it, we tracked it.

But here's the thing - we were drowning in data and starving for insights.

Sound familiar?

The truth is, tracking too many metrics is just as bad as tracking none at all.

You need focus.

What Actually Matters

After working with dozens of bootstrapped founders, I've noticed patterns in what metrics actually drive decisions.

Here's what consistently matters:

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1. Financial Health

• MRR growth trends (aim for >10% monthly at early stages)

• Gross profit margins (should be >70% for most SaaS)

• Customer acquisition costs (CAC)

• CAC payback period (aim for <6 months when bootstrapped)

Why these matter: They tell you if your business model actually works. If your margins are too low or your CAC payback period is too long, you'll run out of cash before hitting scale.

2. Operational Efficiency

• Server uptime (target >99.9%)

• Support response times (<1 hour during business hours)

• Development velocity (features shipped per month)

Why these matter: They indicate if you can scale without everything breaking. Poor operational metrics lead to customer churn.

3. Customer & Market Success

• Net Revenue Retention (aim for >100%)

• Customer Retention Rate (>99% annually is solid)

• Trial to Paid Conversion Rate (>25% is good for most B2B SaaS)

• Organic vs paid acquisition mix (aim for >60% organic)

Why these matter: These show if you're building something people actually want and can acquire customers sustainably.

4. Product Usage

• Daily Active Users / Monthly Active Users (>50% is healthy)

• Core Feature Adoption Rate (aim for >80%)

• Activation Rate (% of users who reach key value milestones)

Why these matter: Usage metrics predict churn and expansion revenue. Low usage today means lost revenue tomorrow.

5. Funding Independence

• Revenue from Operations vs External Funding (>80% from ops)

• Cash Runway (maintain >12 months)

• Break-even Point Tracking

Why these matter: As bootstrappers, we need to know if we can sustain growth from revenue alone.

6. Customer Success

• Net Promoter Score (>30 is good for B2B SaaS)

• Customer Satisfaction Score (aim for >85%)

• Customer Health Score (composite metric you define)

Why these matter: Happy customers stick around and refer others. Unhappy ones leave and tell everyone why.

The Free SaaS Metrics Template

I've put all these metrics into this, simple Google Sheet. It includes:

• Formulas for calculating key metrics

• Industry standard targets to aim for

• Monthly tracking columns to spot trends

• Progress indicators showing how close you are to goals

But here's what makes it different:

It's customizable for your specific needs. It focuses on metrics that drive decisions, and leading indicators. It’s designed for non-technical founders. And, it’s simple enough to actually use.

How To Use the Free SaaS KPIs Template

1. Make a copy of the template

   • Don't get overwhelmed by all the metrics

   • Start with what you can track today

2. Delete metrics that don't matter for your business

   • Running a dev tools SaaS? CSAT might not matter as much

   • Selling to enterprises? Daily active users might not be relevant

3. Add metrics specific to your needs

   • Have a viral loop (I hope so!)? Add viral coefficient

   • Using a freemium model? Add free-to-paid conversion

4. Set your own targets based on your market

   • B2B targets will differ from B2C

   • Enterprise targets will differ from SMB

5. Track monthly (no need to obsess daily)

   • Set a calendar reminder for updates

   • Spend max 1 hour per month on this

How to Get Started

The hardest part of tracking metrics is knowing where to begin.

Start with just these three:

1. MRR Growth Rate

   • Are you growing fast enough to succeed?

   • What's driving/blocking growth?

2. Customer Churn

   • Are customers sticking around?

   • Why are they leaving?

3. CAC Payback Period

   • Can you afford to acquire customers?

   • Is your pricing right?

These will tell you if you're growing sustainably, keeping customers happy, and acquiring customers profitably.

Everything else can wait until these basics are solid.

UPDATE: Dummy Data & Supporting Metrics

You’ll notice in the template, there’s also now a 2nd tab titled “Dummy Data Filled” which has some additional sample metrics filled in, along with color coded (red/green) % to target columns.

There’s also a 3rd tab titled “Supporting Statistics Needed” which is a list of data you’ll need to be able to make the calculations for the metrics. (Update: This wasn’t enough. Someone asked for an API to create those calculations, which I made today too. See below.)

UPDATE: Supporting API Calculations

I just added a new API to help people calculate some of the basic metrics. You’ll need the basic data set as shown in the 3rd tab, but if you have that data, you can run it through the free API I just created at https://saas-kpis.founderlabs.io.

What's Next

Here's where you come in.

I'd love to hear which metrics matter most for your SaaS? What would make tracking easier? How do you currently track metrics?

Your feedback will help evolve this template into something even more useful for bootstrapped founders.

Leave a comment on the template, or here in this article. I’ll edit it as fast as I get suggestions. Thank you!

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The Future Vision of this Template

Eventually, this could become a proper dashboard - something between basic spreadsheets and enterprise business intelligence (BI) tools.

But for now, let's start simple.

Get the metrics right first, then worry about making them pretty.

Download the template and let me know what you think by leaving a comment.

Tracking the right metrics won't magically make your SaaS successful. But tracking the wrong ones will definitely make it harder to succeed.

Start with the basics, add what matters for your specific business, and use the data to make better decisions.

That's how bootstrapped founders win.

And hey, if you want to dive deeper into strategies for growing or getting your SaaS business unstuck, grab some time and let’s chat.

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AI isn't just a buzzword anymore; it's a game-changer for SaaS companies looking to scale.

But here's the kicker - most founders I talk to are either overwhelmed by the possibilities or unsure how to start.

If that's you, buckle up.

We're about to dive into a no-nonsense guide on how to leverage AI for explosive SaaS growth.

1. Identifying AI-ready processes in your SaaS

2. Implementing AI for personalized user experiences

3. Using AI to optimize pricing and reduce churn

4. Leveraging AI for predictive analytics and forecasting

5. AI-powered customer support and engagement

6. Overcoming challenges in AI implementation

Let’s get to it…

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Identifying AI-ready processes in your SaaS

Before you jump headfirst into AI implementation, you need to identify which processes in your SaaS are ripe for AI enhancement.

Here's a quick exercise to get you started:

1. List all your core business processes (e.g., user onboarding, customer support, pricing, etc.)

2. For each process, ask:

   1. Is it data-driven?

   2. Is it repetitive?

   3. Does it require pattern recognition?

   4. Would automation significantly improve efficiency?

If you answered 'yes' to at least two of these questions, congratulations - you've found an AI-ready process.

AI for personalized user experiences

Once you've identified your AI-ready processes, it's time to implement.

Let's start with personalization, because it's a low-hanging fruit that can yield immediate results.

Here's a step-by-step approach:

1. Data collection: Gather user data points like behavior, preferences, and demographics.

2. Segmentation: Use AI clustering algorithms to group users based on similar characteristics.

3. Content mapping: Create a matrix of content/features that align with each segment.

4. Implementation: Use AI to dynamically serve personalized content or features to each user.

For example, let's say you run a project management SaaS. You could use AI to analyze user behavior and automatically suggest relevant features or templates based on their project type and team size.

AI for optimizing pricing & reducing churn

Pricing optimization and churn reduction are two areas where AI can have a massive impact on your bottom line. Here's how to approach it:

a) Pricing optimization:

• Collect data on user behavior, feature usage, and willingness to pay.

• Use AI algorithms to analyze this data and identify optimal price points for different user segments.

• Implement dynamic pricing based on these insights.

b) Churn reduction:

• Use AI to analyze user behavior patterns that indicate a high likelihood of churn.

• Develop a predictive model that assigns a 'churn risk score' to each user.

• Implement automated interventions (e.g., targeted offers, personalized outreach) for high-risk users.

I implemented an AI-driven churn prediction model that decreased churn by 15% into one of our SaaS companies. The key was early intervention based on AI-identified risk factors.

AI for predictive analytics & forecasting

Predictive analytics with AI can really help.

Identify key metrics you want to predict (e.g., revenue, user growth, feature adoption) and then gather historical data related to these metrics.

Then, choose an appropriate AI model (e.g., regression for continuous variables, classification for categorical outcomes) and train and validate your model using your historical data.

You can use this type of model to make predictions and inform decision-making.

For example, you could use AI to predict which features are likely to be most popular with different user segments, allowing you to prioritize your development roadmap more effectively.

AI-powered customer support

Customer support is another area ripe for AI disruption.

Here's a typical and tactical approach:

AI chatbots

Start with a rule-based system for common queries. Gradually introduce natural language processing (NLP) for more complex interactions. Then, use machine learning to continuously improve responses based on user feedback.

Next, build an AI-driven knowledge base:

• Analyze support tickets and identify common issues.

• Automatically generate and update FAQ articles based on these insights.

• Implement an AI-powered search function to help users find relevant information quickly.

Finally, you can use all this for proactive engagement, too. Analyze user behavior and trigger personalized in-app messages or emails. Or, implement AI-driven onboarding flows that adapt based on user actions and preferences.

There’s so much to be done here, and it’s worth building these bots to keep the churn low. Just remember, the goal is to help people, not just offload costs.

Overcoming challenges in AI implementation

Let's be real - implementing AI isn't all sunshine and rainbows.

Here are a couple common challenges people have, and a few tips on how to overcome them:

For data quality issues:

Do a data audit before implementation. Look at the outputs and tweak the prompts until the outputs make sense. Keep an eye on any “thumbs down” votes on responses or FAQs when users indicate they aren’t helpful.

Implement data cleaning and validation processes. Sometimes by adding different AI tools for different purposes you can fix common issues. For instance, have ChatGPT review a ClaudAI output or vice versa, and suggest changes to it to make the output better.

There are likely even AI tools specifically designed for data cleaning and preparation.

When you have a lack of AI expertise:

Start with off-the-shelf AI solutions that require less technical expertise. I’d even suggest using Make.com’s ChatGPT integration to do whatever you can, since you don’t have to worry about developing any code around the API.

If you need to, partner with AI consultants or agencies for more complex projects.

Oh, and don’t forget to introduce some AI training for your team, too. Let them get creative about solving some automation problems from their perspective too. Free them up to do work they’d rather be doing and you’ll have a better culture.

Bonus: They won’t think AI is coming for their jobs. They’ll be making their jobs more exciting, and leveling themselves up, by understanding AI.

Problems integrating with existing systems:

Start with a thorough assessment of your current tech stack. Choose AI solutions with robust API capabilities (or, like I said, just use Make to no-code solutions wherever you can).

Maybe consider implementing in phases too. Automate where you can. Delegate where you can’t (and then automate later when it makes sense).

Ethical considerations:

One thing I don’t see companies do much at all right now is developing clear guidelines for AI use in their organizations. I think they ought to, though.

Be more transparent in how AI is being used to make decisions, both internally and externally.

One fun thing I did recently was check out some audits of AI systems for bias and fairness. You can search YouTube for this and find some super interesting information on AI system’s biases. Even politically biased, which is kinda scary, honestly.

An AI-powered growth roadmap

Now that we've covered the tactical details, let's put it all together into an actionable roadmap:

1. Month 1-2: ID AI-ready processes and prioritize which areas will come first.

2. Month 3-4: Implement AI-based personalization for your users, and start collecting data on conversion rates on the user journey.

3. Month 5-6: Create or use an AI-driven churn prediction model.

4. Month 7-8: Launch an AI-powered customer support chatbot & knowledge base.

5. Month 9-10: Implement predictive analytics for key business metrics - this is my favorite one.

6. Month 11-12: Iterate, refine, and optimize based on the data.

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Remember, this isn't a one-size-fits-all approach.

Tailor this roadmap to your specific SaaS and don't be afraid to iterate as you go.

Leveraging AI for SaaS growth isn't just about implementing fancy tech - it's about solving real problems for your users and your business.

Start small, focus on high-impact areas, and always keep your users' needs at the forefront.

And for the sake of all that is good in this world, don’t put “AI Powered” anything on your marketing. Just let it be awesome for your users. They don’t care that it’s AI powered at all. They want the outcome they are hiring your SaaS to provide.

Now, stop reading and start implementing.

And hey, if you want to dive deeper into strategies for growing your agency with recurring revenue, or getting your SaaS business unstuck, grab some time and let’s chat.

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