Can you measure Product Market Fit?

Vivek Kaushal
May 2, 2023

Product/Market Fit (PMF) has become synonymous with startup success. It's the point at which your product is finally meeting the needs of its target market, leading to exponential growth and potential profitability. The problem though, is that it’s notoriously hard to find.

A contributor to this notoriety is that, more often than not, whether you “have PMF” ends up being a subjective call. The non-intuitive tangent here is that there are often a handful of proxy-metrics which can be leading/lagging indicators of PMF, but are frequently overlooked. Tapping into these can help you experiment and iterate by holding yourself accountable to moving this metric. In the rest of this post, we'll explore some methods for quantifying PMF so that you can build your product more effectively.

Understanding Product-Market-Fit

Product/Market Fit is achieved when a product or service resonates with its target market, addressing a specific problem or fulfilling a need to the extent that customers become loyal advocates. This is the stage where the product's value proposition is crystal clear, and users are not only satisfied but are also actively recommending the product to others.

For example, building on the Sean Ellis Test, Superhuman famously iterated their way to a state where 58% of their surveyed users reported that they’d be “Very Disappointed” if they could no longer use Superhuman. For context, when they started optimising for this value, it was at just 22%! This degree of customer love and loyal advocacy is a hallmark of Product/Market Fit.

Quantifying Product-Market-Fit

Net Promoter Score (NPS)

What is NPS and how do you measure it? - Trustmary
Image: Trustmary

You’re probably already familiar with NPS. It’s a widely used, and delightfully simple quantification of how your customers feel about your product, their satisfaction and loyalty. By asking customers how likely they are to recommend your product to others on a scale of 1-10, you can separate them into three groups: promoters (9-10), passives (7-8), and detractors (1-6). Subtracting the percentage of detractors from the percentage of promoters provides your NPS score, which can range from -100 to +100. A high NPS indicates that your product is resonating with customers, and delivering value. This may be indicative of PMF.

Customer Retention Rate

Employee Retention Rate: All You Need to Know - AIHR
Image: AIHR

A customer is retained if they’ve built a habit of solving a problem using your product, repeatedly, for a sustained amount of time. The ground reality is that, if your product is truly meeting the needs of its target market, customers should continue using it over time. Measuring the percentage of customers who return to your product within a specific timeframe can be an useful indicator of PMF. This timeframe is highly dependent on your product and the market you operate in. For example, for a organisation wiki like Confluence, a weekly cadence for usage is probably a good estimate for a retention cadence. This frequency can be as low as yearly for an annual tax filing product, and as high as daily for a social media app.

Virality Coefficient

Why Word of Mouth Marketing Is So Effective (+How You Can Use It)

Admittedly more useful in a B2C setting, than for a B2B product, virality coefficient is a measure of how many additional users are acquired through word-of-mouth referrals for each new user. If your product is achieving PMF, it's likely that customers are recommending it to others, leading to the elusive phenomena of organic growth. To calculate the virality coefficient, divide the number of new users acquired through referrals by the total number of referring users. A virality coefficient greater than 1 indicates that your product is experiencing viral growth!

Usage Metrics

graphs of performance analytics on a laptop screen
Image: Unsplash

A superset of customer retention, analyzing how customers interact with your product is a great place to start measuring whether your product is meeting your customers’ needs. Metrics such as daily active users (DAU), monthly active users (MAU), and stickiness (DAU/MAU) provide insight into how engaged customers are with your product. Measuring the percentage of users who’re getting activated onto your product, and forming habits can be a strong leading indicator of Product/Market Fit. In a world where software product analytics from tools like Amplitude and Mixpanel are empowering better product decisions, usage metrics is a great place to start your journey into quantifying PMF.

Customer Feedback

Customer feedback, whether collected through surveys, interviews, or online reviews, is an invaluable resource for assessing PMF. Such qualitative feedback is hard to quantify but tools like Enterpret can be leveraged for extracting customer insights, such as common themes and issues that can help you iterate and improve your product. Positive feedback and success stories can also serve as social proof, helping to attract potential customers and investors.

A Few Frameworks

(drumroll) An article that touches on building products is practically incomplete unless it references a handful of frameworks. Here are a few to help you get started:

6 Reference Customers

Marty Cagan suggests using six reference customers to measure Product-Market Fit (PMF) by identifying and working closely with a diverse set of customers who represent the target market, in a B2B setting. This numbers needs to be higher if you’re building in a B2C setting, in the range of 10-50 depending on your product market. These reference customers work closely with you, sharing feedback, helping validate assumptions, refine features, and ensure the product meets real customer needs. By achieving strong satisfaction and success with these reference customers, product teams can build confidence that they have achieved PMF and the product is ready for broader market adoption. The core idea is to get to a state where your reference customers are loyal advocates who love your product.

Sean Ellis Test

The Sean Ellis Test is a method used to measure Product-Market Fit (PMF) by assessing customer satisfaction and quantifying the value of a product to its target market by surveying customers. Typically, this is done by asking how disappointed they would be if they could no longer use the product. Responses are categorized into "Very Disappointed," "Somewhat Disappointed," and "Not Disappointed." A product is considered to have achieved PMF when at least 40% of surveyed customers respond with "Very Disappointed." This indicates a strong demand and high satisfaction, suggesting that the product has found its target market and is meeting their needs effectively. In the example shared earlier in this article, this is the method Superhuman built their PMF quantification on.

The PMF Canvas

The Product/Market Fit (PMF) Canvas is a framework used to measure the degree to which a product or service meets the needs and demands of a target market.Introduced by Dan Olsen in his book "The Lean Product Playbook", the PMF Canvas consists of two main sections: target market and value proposition. The target market section includes customer segments, underserved needs, and market size. The value proposition section consists of the problem, solution, and unique differentiators. By filling out the PMF Canvas, teams can identify gaps in their understanding of the market, refine their value proposition, and iterate on their product to better fit the needs of their customers.


There's no single metric or framework that can definitively determine if your product has achieved Product/Market Fit. But a combination of the methods outlined above can greatly help disambiguate whether your product is actually resonating with its target market. By closely monitoring metrics, listening to customer feedback, and iterating your product based on learnings, you can boost your chances of finding PMF and ultimately create a product that customers love!

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Anna Esrov
Vice President of Customer Experience & Loyalty
Enterpret allowed us to listen to specific issues and come closer to our Members - prioritizing feedback which needed immediate attention, when it came to monitoring reception of new releases: Enterpret picked up insights for new updates and became the eyes of whether new systems and functionality were working well or not.
Louise Sellars
Analyst, Customer Insights
Enterpret is one of the most powerful tools in our toolkit. It's very Member-friendly. We've been able to share how other teams can modify and self-serve in Enterpret. It's bridged a gap to getting access to Member feedback, and I see all our teams finding ways to use Enterpret to answer Member-related questions.
Dina Mohammad-Laity
VP of Data
The big win-win is our VoC program enabled us to leverage our engineering resources to ship significantly awesome and valuable features while minimizing bug fixes and" keep the lights on" work. Magnifying and focusing on the 20% that causes the impact is like finding the needle in a haystack, especially when you have issues coming from all over the place
Abishek Viswanathan
Since launching our Voice of Customer program six months ago, our team has dropped our human inquiry rate by over 40%, improved customer satisfaction, and enabled our team to allocate resources to building features that increase LTV and revenue.
Abishek Viswanathan
Enterpret's Gong Integration is a game changer on so many levels. The automated labeling of feedback saves dozens of hours per week. This is essential in creating a customer feedback database for analytics.
Michael Bartimer
Revenue Operations Lead
Enterpret has made it so much easier to understand our customer feedback. Every month I put together a Voice of Customer report on feedback trends. Before Enterpret it would take me two weeks - with Enterpret I can get it done in 3 days.
Maya Bakir
Product Operations, Notion
The Enterpret platform is like the hero team of data analysts you always wanted - the ability to consolidate customer feedback from diverse touch points and identify both ongoing and emerging trends to ensure we focus on and build the right things has been amazing. We love the tools and support to help us train the results to our unique business and users and the Enterpret team is outstanding in every way.
Larisa Sheckler
COO, Samsung Food
Enterpret makes it easy to understand and prioritize the most important feedback themes. Having data organized in one place, make it easy to dig into the associated feedback to deeply understand the voice of customer so we can delight users, solve issues, and deliver on the most important requests.
Lauren Cunningham
Head of Support and Ops
With Enterpret powering Voice of Customer we're democratizing feedback and making it accessible for everyone across product, customer success, marketing, and leadership to provide evidence and add credibility to their strategies and roadmaps.
Michael Nguyen
Head of Research Ops and Insights, Figma
Boll & Branch takes pride in being a data driven company and Enterpret is helping us unlock an entirely new source of data. Enterpret quantifies our qualitative data while still keeping customer voice just a click away, adding valuable context and helping us get a more complete view of our customers.
Matheson Kuo
Senior Product Analyst, Boll & Branch
Enterpret has transformed our ability to use feedback to prioritize customers and drive product innovation. By using Enterpret to centralize our data, it saves us time, eliminates manual tagging, and boosts accuracy. We now gain near real-time insights, measure product success, and easily merge feedback categories. Enterpret's generative AI technology has streamlined our processes, improved decision-making, and elevated customer satisfaction
Nathan Yoon
Business Operations,
Enterpret helps us have a holistic view from our social media coverage, to our support tickets, to every single interaction that we're plugging into it. Beyond just keywords, we can actually understand: what are the broader sentiments? What are our users saying?
Emma Auscher
Global VP of Customer Experience, Notion
The advantage of Enterpret is that we’re not relying entirely on human categorization. Enterpret is like a second brain that is looking out for themes and trends that I might not be thinking about.
Misty Smith
Head of Product Operations, Notion
As a PM, I want to prioritize work that benefits as many of our customers as possible. It can be too easy to prioritize based on the loudest customer or the flavor of the moment. Because Enterpret is able to compress information across all of our qualitative feedback sources, I can make decisions that are more likely to result in positive outcomes for the customer and our business.
Duncan Stewart
Product Manager
We use Enterpret for our VoC & Root Cause Elimination Program - Solving the issues of aggregating disparate sources of feedback (often tens of thousands per month) and distilling it into specific reasons, with trends, so we can see if our product fixes are reducing reasons.
Nathan Yoon
Business Operations,