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.
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.
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.
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.
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!
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, 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.
(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:
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.
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 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!