If you're building a product, there's one milestone that changes everything: Product-Market Fit (PMF). It’s the moment your product truly resonates with your market—when users not only adopt but stick around, pay for it, and even advocate for it.
But while PMF feels magical, it's not some vague, unmeasurable idea. The smartest founders and product teams use data and behavioral patterns to know when they’ve reached it. So, how can you measure it meaningfully?
Let’s break down what the experts say.
Building upon the Lean Startup Methodology discussed in the previous chapter, we now dive into how to measure Product-Market Fit (PMF). Eric Ries's approach, with its emphasis on validated learning and iterative cycles, sets the stage for our exploration into quantifying success. In this chapter, we'll navigate through various metrics proposed by experts like Enzo Avigo and Tom Blomfield, gaining insights into how these indicators can help us understand a product's resonance in the market. Additionally, we'll examine real-world examples and explore diverse perspectives on the most effective metrics to determine PMF. Enzo Avigo (2023) provides different goal metrics and shows how they relate to PMF in the Figure below.
That “very disappointed” metric has become a cult favorite. Ask your users, “How would you feel if you could no longer use this product?” If 40% or more say they’d be very disappointed, that’s a green light.
Tracking these essential metrics is a solid beginning for measurement in the initial months. Revenue growth, in particular, serves as a strong indicator. Peter Reinhardt, Segment's co-founder and CEO (2023), provides an illustration of how the introduction of a new feature in an existing product can enhance the product-market fit. The first graph displays revenue before the new feature's implementation, while the second demonstrates revenue after its introduction.
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Peter believes that this is how you can tell if you have something truly transformative for your customers. Using data, helps to understand that you have made something people want in an unbiased way. But it's also important to acknowledge that the success metric can vary across companies and products. Therefore one needs to interpret data based on realistic goals for different market contexts.
Gustaf Alströmer (2019) discusses measuring product-market fit by identifying the key metric that reflects your company's value. Second, determine how often customers should ideally engage with your product. Gustaf presents a table comparing various companies based on these value metrics and user interaction frequencies.
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Take Airbnb, for instance. Gustaf's team measured retention by asking how frequently people traveled. On average, it turned out to be once a year. So, they realized that checking annually was the ideal frequency to monitor. Now, in the case of Lyft, the assumed metric was rides. But, the crucial factor was actually the riders themselves—how often the same person took a ride. This turned out to be weekly or monthly. After finding these two metrics specific to your product, it's useful to plot them on a graph. This graph is what investors often request to see. In Figure below, Gustaf (2019) demonstrates an example of a bad product.
However the green line on the second graph shows an example of a good product, because there is a flat line of people using the product continuously every single week.
He goes on by showing a graph with 2 different companies. One with a retention of 30% after 2 months and 21% after 20 months. Which is pretty good. The company he's talking about is Doordash.
Gustaf (2019) shows another graph (Figure 22) with 80% retention after 1 month and 30% after 60 months. Which is very good. This product is sticky and it's Github.
Not all PMF metrics are created equal. Your product’s context defines what matters most.
Mixpanel recommends a layered metric approach:
To illustrate a practical application of this framework in action, the guide examines a subscription-based video streaming product
Here’s your quick PMF measurement checklist:
✅ 40%+ of users say they’d be very disappointed if you disappeared
✅ Retention curve flattens—users stick around
✅ 5–10% WoW active user growth
✅ 6-month retention > 40%
✅ People are paying—and renewing
✅ Revenue grows post-feature launches
✅ Metrics align with your product’s usage frequency
