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A Guide to Product Market Fit Using Retention Rate Metrics


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If you Google “What is product-market fit” (or PMF as we’ll refer to it), you’ll be surprised by the number of articles that talk about a feeling: “We started to feel a pull for the first time,” “It felt like getting pressed into the back of your seat by a fast car or a plane taking off,” “We heard why won't you take my money???”. 

That feeling mentioned above is true for many; it’s equally as common for young founders to believe they have PMF when, in reality, they’re having success with one marketing lever. 

While I understand this feeling, I think that there should be a more concrete indicator, based on data. 

In June, I was lucky to observe how startups use data to reach their PMFs. In this post, I’ll give a guide based on my empirical findings. 

What indicates you’ve got PMF? 

There are a lot of opinions out there about how to measure PMF. Some say it’s a feeling. HubSpot has you sending surveys. Forbes gives a few general metrics

In our opinion, the best metric for determining if you’ve found PMF is Retention Rate.

Measure Product-Market fit with Retention Rate  

Retention rate is growing in popularity as a key indicator. 

“Hilariously simple leading indicator of whether you have a good product is you sold somebody the product, they’ve successfully onboarded, and they’re actively using it.” - Michael Seibel told at Y Combinator.

I’m passing over top-of-funnel metrics like signups or even conversions and snubbing revenue and churn for a couple of reasons. 

When you have PMF your acquisition is going to be ramping up. Your customer support team will feel it. Marketing will love it. It’s a good and fun feeling like the ones I’ve described in our intro. 

However, Retention Rate goes deeper.

  • Retention conveys sound positioning since it ensures that you’re not conflating good marketing & sales with PMF.
  •  It tells you if those people are actually sticking around and actually using your product, and then actually finding enough value here to pay.
  • The longer someone sticks around finding value and paying, the more they’ll share your product, so you will see growth in your acquisition numbers.
  • Retention also predicts lifetime value, which means you have more money to invest in all other areas of your business. 

Retention also points to the lovely dance between customer expectations and product activation. If you were looking at financial metrics for PMF you’d see spikes when pricing changes, seasonality shifts, or marketing runs a promotion. Again, that tends to do more with product marketing than PMF. 

How to Measure Retention

There are many types of retention and various charts to explore. Appcues gives a guide here.

 That said, I’ve seen the most meaningful way to measure and define retention rate is as the percentage of customers who continue paying for a product over a given timeframe.

A retention curve shows the % of sign-ups that come back over time.
A flattening curve is a good proxy of PMF.

There’s more to this chart than what meets the eye. Retention rate requires that you’re getting a number of things right: activation, conversion to paid, and more (which are all early indicators of PMF). 

This chart also requires that you track both the number of paying users and that you define a smart sense of time to measure them over.

So, as I start to measure Retention Rate and our lean into PMF, I’m going to measure and define many other things along the way. Pivotally important for PMF is activation, your Aha! Moment, conversion to paid, and then Retention Rate. 

The Path to Retention

Let’s back into it. Before you look at who is retained, you should define who activates & look at who pays. 

1) Activation

Activation is important because when a user activates, they are active & engaging – and no, those aren’t the same thing.  

Activation will be defined by a certain user action in your product that aligns with your core value, which is why someone will end up paying you for it (hopefully).

This is separate from engagement, which is simply using a product in any capacity. Activation requires that engagement be with the key feature of the product; it’s more strategic than plain engagement.

It’s often, and should be, closely tied with your Aha! Moment. When people get activation wrong, they’re generally choosing the wrong engagement metric as activation. And most of the time, they’re doing this to make their metrics look better than they are. 

For example, if Zapier defined activation as using their builder but not creating a Zap they’d certainly boost their activation numbers but wouldn’t be able to understand why they had such low conversion from activation to payment. The issue here is about how well a new user finds the value, not how well Zapier creates a checkout flow. 

With smart activation definitions, you and your team can look at how well you’re getting signups to that point and an early indicator of conversion (and retention) potential. 

Getting all of this right is essential for PMF. You need to know what customers find valuable and then build an experience that takes them to it. 

2) Aha! Moment

AppCues defines that key moment as:

“The pivotal moment when a new user first realizes the value of your product and why they need it.”

It’s engagement with your core functionality and the moment that makes someone think: Oh, I get it, and I need it.

Like I said, someone needs to hit this key moment, not just engage, to be active. Otherwise, they’re probably not going to understand the value of your product and be ready to pay.

I’d imagine that for Zapier, this is creating a Zap (not touching the builder). For Loom, it’s creating a video, not just installing the extension.

Activation and an active user are defined by reaching the Aha! Moment. 

3) Conversion to Payment

Ideally, after activation, you see an upgrade to payment. Now, I know this is a big IF. Teams struggle to figure out how and when to convert users and struggle to craft smart payment tiers. This is precisely why I like Retention Rate as a metric for PMF. 

It requires teams to have figured out something here that works well enough to not only create value for their users but effectively communicate that value and convert them to customers. 

Lucky for you, it’s a binary. Someone either pays or they don’t. It’s the one part of this process that’s easy to measure because there’s a yes or a no.

4) Retention Rate

And finally, I’m back to our first point: you want to measure the Retention Rate to find PMF. The longevity and the retention of someone throughout your funnel help you see the full picture.

A high Retention Rate forces you to have smart activation, good conversion, and to strategically understand why customers sign up, pay for, and use. 

This is what’s key for PMF. It’s getting all these areas right so customers can seamlessly move into and through your business. 

Retention Rate & Time

The key to measuring your Retention Rate is time. 

Obviously, the Retention Rate being retention/specified time means specifying the right set-up time is essential. 

Surprisingly, it’s something people often get wrong. It can be exciting to look at your product and your Daily Active Users or your Monthly Active Users. However, you’ve got to set your timeframe to what makes sense with your business. For example, perhaps your customers like to come back to check their scheduled Tweets for your social media app once a week. Your retention is going to look very different if you track by day, week, or even two weeks.

For example, a product like Zapier isn’t built to be used daily, in fact, it’s built so you can set up automations and let them run. If Zapier looked at their DAUs, it would misrepresent their success.

You also can’t look for retention too soon. Seeing someone active for two weeks is a good sign but not retention. I prefer looking at retention after the three-month mark. It's annoying for rapid decision-making. But it's good for really understanding how strategic decisions are shifting your business. Plus, if you want to do any kind of projections in the future, you’re going to want to understand how MRR is retained over time. 

Retention Rate Analysis & Cohort Size

When looking at your Retention Rate, you’ll also likely be creating cohorts and running cohort analysis. 

This could be looking at a group of retained users before and after large strategic changes, new features are added, etc.

It’s also another easy place to get things wrong. While you might be eager to see how changes impact your business, you need cohort sizes that are large enough to make strategic decisions from.

In small startups, I’m not always looking for stat sig here. I know this might be surprising. Startup people are data people. I like our numbers to be accurate. But If you’re a startup with a small funnel and maybe only 50 to 100 signups, waiting for stat sig is going to take a very long time. You don’t have that amount of time.

Instead, I like something like over 50 people in a cohort or in a group of people being observed. This isn’t a hard and fast rule, but don’t make product-changing decisions based on three people.  

Retention Benchmarks

In general, you want your Retention Rate at three months to be over 30-40% if you’re a B2C software company. If you’re B2B, you’ll want something closer to 50% since your sales cycle is longer, and it’s unsustainable to burn and churn through users.

From Lenny’s Newsletter

And don’t worry about checking this chart frequently. As I said, you want to keep people retained for months, so watching cohort movements daily feels a bit obsessive. 

So, How Do You Find PMF Within Your Data? 

Think Retention Rate is an annoyingly deep and slow way to look at PMF? Let’s explore why it just might hold the key to your success. 

Most early companies look at their retention metrics, and when 96% of people aren’t retained, they have a little panic. I’m here to tell you to pause. 

Zoom into that 4% that didn’t bounce. 

 It’s common for there to be outrageous retention and activation rates for a small subset of people. 

Chase these people! This is a great place to start looking for PMF.  You’ll want to see if you can find any common patterns in this subset of users.  You’ll want to look at who they are, what their jobs are, what features they’re touching, and their lifestyle. 

Be sure to look at persona data and usage data. 

Persona data, like job title, industry, age, and identity demographic, starts to paint a picture of who resonates with your product. 

Usage data is going to start telling you about the job-to-be-done and how people are using your product to solve a pain point.

Once you start to see this stickiness, you will want to start building for these people. This is how you find your chased-after PMF.

April Dunford’s Example

Recently, I interviewed April Dunford, the Queen of Positioning and author of Obviously Awesome. When she describes how she got into positioning, she describes a product situation like the one I detailed above.

“Like in my very first job at a startup, the company had multiple products, but because I was brand new, I got hired as a product marketer, and I got assigned to a product that was no good.

The product was initially a failure. We launched it into the market and spent a bunch of money marketing it, but it didn't take off. Part of my job was to figure out if people were going to be unhappy if we turned it off. Through talking to customers,  I realized that a very small number of customers used that product in a way we had never predicted.

And so we did a very brave thing as a company and decided to reposition the product into this other market. And the results were like magic. The product started selling like crazy. We started growing. We eventually got acquired on the strength of that product.

So that opened my eyes about positioning. If you get it wrong, it's bad. If you get it right, it's magic.”

While April didn’t point me to exact retention charts, I’d be exceedingly curious to see if it follows our suggestion: even if the Retention Rate looks abysmal, hone in on those sticking around, find out why, and build for them. And then, don’t forget position. 

Run Aha! User Interviews

Once you have a sense that there are people sticking around and paying for quite a long time, it’s important to start defining your person so you can build for this customer.

If you’re familiar with the job-to-be-done framework, you may have run or tried to run, customer interviews that help you pinpoint your Aha! Moment and better understand your customers.

This can be helpful on the route to PMF or even after you’ve found it to help tighten your messaging and positioning. 

So, how do you set these up? 

We like to interview both engaged and unengaged users, free users, and paying customers. This gives us various slices of the demographic. 

We then run through a series of questions about what brought someone to the product, why they signed up, and why they paid (among other things). We ask about what features they use, if they’d recommend our product, and what they would tell someone else.

When you compare and contrast these value points across these segments, you start to see what features people are signing up for and why they pay, which is key to PMF. You’re getting a sense of your own marketing and how that stacks up with what someone expected from you.

Generally, the moment that someone decides they’re ready to pay is you Aha! Moment. This might be different than when your trial or free plan asks them to, but it’s the moment when they see the value and know they need your product. 

Use Activation to Find Aha! Moments

It’s also key to note that your product might not have just one, clear, Aha! Moment. You might have none, or two or more. What’s key is to look at what’s happening in your activation charts.

You’ll know the place you need to get users to when you start to notice cliffs and drop-offs in new user activation patterns.

Build & Market for Your Retained Users

Once you start to understand the people who are sticking around and paying you, then build for them. Slowly growing this segment of users is how you find PMF and build a product that solves a specific pain point. 

You’ll also want to ensure that your positioning aligns with the product you’re creating and updates as your product does. Remember, the “market” is half of PMF. 

To quote April, “If your positioning is unclear, you're going to have customers coming in who look like leads because they think you do something that you don't. And then they come in, get to sales and sales pitches them, and they're like: ‘What? This isn't what I thought it was.’ And then they drop out.”

So, a leaky top-of-funnel can point to your positioning not keeping up with your changing product. Here are a few key ways to determine if that’s the case for you: 

  1. Look at your signups vs. conversions to trialists (not just to new customers).  If this is low, there’s exploration to be done. Why did someone go through the effort of signing up but didn’t want to trial?
  2. You can also look at how reactivation email campaigns are performing. If offering a discount to stale leads doesn’t bring them back in, what were they hoping to get from your product? 
  3. You can also look at your core marketing lever bringing in traffic. Whenever we’re exploring soft conversion rates,  we break it down by funnel. For example, we compare conversion rates when someone moves from a) direct traffic to the homepage to signup flow vs. b) blog to the homepage to signup vs. c) through a pricing page. All three routes create a different level of qualification that can help pinpoint what your ideal customer prefers.  What does the copy say about these conversion properties? What does the copy on your homepage and in your flow say? Is it consistent? 

All of these are especially poignant if you continue seeing long-term retention for that small subset of users. Conversely, how do you know if you’re getting things right? 

An Early Indicator of PMF is Activate Users 

While Retention Rate is our go-to indicator for PMF, you’ll know you’re on the right track when you’re seeing many active users. It means your positioning is getting people through your onboarding, and someone is finding and engaging with your Aha! Moment. 

Active users are the flip side of retention, but instead of giving the percentage of people that stick over time, it provides the number of active users daily, weekly, etc. This number is faster to influence, and you don't have to wait weeks to read it. 

Active users is also a nice rallying cry for teams. You can startup with 50 WAU and aim to grow this number by 10% week over week, so 55 to 55, to 61, etc, which feels achievable but provides strong growth.

That said, you’ll want to be sure to start charting Activation from the moment of signup. 

One of the biggest failures I see founders and teams making is to measure their retention from the moment of activation, rather than signup. 

Why might you want to make this mistake? Well, the charts look better. When you measure retention from the moment of signup, you’ll see many drop-offs. Founders don’t like it. Investors don’t like it. It’s human instinct to zhuzh the definition of these metrics because it’s hard to look at charts that don’t give the answer you want.

 But if you’re not looking at what happens to a new signup and if they hit what you think your Aha! Moment is, you could be missing failures in your positioning, or worse, chasing the wrong thread looking for PMF. 

Product-Market Fit Is Not A Binary

As I wrap up, one of the most important lessons to know about PMF is that it isn’t a binary. It’s not like a puzzle piece where one day everything clicks into place. Most companies take years to find PMF, and that’s after they have a working product. 

From Lenny’s Newsletter

That’s because PMF, and a healthy Retention Rate, take many things going well. 

Jori Lallo, co-founder of Linear, puts this well: 

“PMF has been so gradual; I might even say... linear. There’s not just one hump that we got over and thought, ‘Okay, now it’s clicking.’ It’s more like we’re chipping away at these obstacles and getting more and more people interested. It’s more like, ‘Oh, this is really working for certain segments.’”

Those obstacles are finding your active users and what they love about your product, building signup that makes sense for it, finding pricing plans that make your site convertible, and more.


To sum it up, finding the right balance between making people stick around and pay for your product involves looking at the Retention Rate. This number tells you if folks are genuinely finding your product useful over time. It's not a quick win but a step-by-step process, where you figure out what clicks for your users and build for them. So, keep an eye on that Retention Rate—it's like a guide helping you navigate the tricky path to making your product just what your users need.


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