How to measure your product/market fit
When launching a new digital service, app, or platform, the aspiration for it to become the next big thing is common. Sometimes, this expectation is met with rapid user adoption and enthusiastic word-of-mouth. Other times, however, the product struggles to resonate with users. Achieving product/market fit (PMF) is crucial for success, but it's a journey that requires testing, iteration, and adaptation. But how will you know you’ve reached the magical PMF? This post delves into some concrete methods to measure PMF effectively.
Product/market fit: a prior objective of any product
Whomever you ask what product/market fit is will give you a different definition. We personally love the simplicity of Paul Graham’s definition: “Making something people want.”Making something people want sounds easy enough but it’s much more complicated than it seems.
Product/market fit should be the first and foremost priority of any product or solution you’ll build.
You’ll need to test and iterate on your product until users find a perfect match with their needs. Because only when you reach product/market fit, your product can really start to grow. So, if anything, product/market fit should be the first and foremost priority of any product or solution you’ll build. With that in mind, it seems rather sketchy to only rely on ‘making something people want’. You can’t trust your gut feeling. You need metrics to validate your idea.
Time to open up your strategy toolbox and start measuring your product/market fit (PMF).
How to measure your product/market fit
Once your product is live and in the market, product analytics are the way to determine if your product has PMF. Now, there are different established ways to measure PMF. But there’s no one magic formula providing all the answers. Try finding the truth in a combination of different indicators that can give you PMF affirmation.
It’s all about retention.
What is the main indicator that users are liking your product? The fact that they return. We favour 4 methods that measure this phenomenon:
- Cohort retention,
- Daily user frequency
- User stickiness
- Power users.
But how do they work? Let's go over them, one by one.
Quick sidebar: Note that all these metrics are indicators of product/market fit. The more objectives you reach, the better. However, the importance of all these metrics will be different from product to product.
#1 Cohort retention
What it is
Cohort retention is all about the hockey stick-shaped curve. You measure the percentage of active users returning to the app frequently over a period of time. You can choose whether you want this on an hourly, daily, weekly or monthly basis. Whatever fits your product best. The higher this curve, the more of your users are hooked on your product.
The indicator for PMF is not the height of the curve or a certain % after a certain period, but the shape of the curve. If it flattens after the first weeks/days/months (and has the shape of a hockey stick), you have your first indicator of PMF.
#2 Daily user frequency
A close alternative to cohort retention (or as an extra measurement) is looking into your daily user frequency.
What it is
With daily user frequency, you specifically focus on new users. How impressed are they with your product from the start? Looking at the percentage of new users that return to your product after a specific number of days in the first month, will give you good insights into their first impression.
Generally speaking, various benchmarks indicate that 60% of users should return the next day, 30% the next week and 15% should still return on day 30. Reach these benchmarks, and you’ll have stats to back your PMF.
#3 User stickiness
A third important alternative is user stickiness. This metric will - in a later phase - also be important to understand the active usage of your product.
What it is
User stickiness measures the ratio of daily users compared to the number of users in the last 28 days. The running average gives you an indication of how many times your users make use of your product in a month.
A ratio of 100% means all users use your product daily. Close to 0% means almost no one uses the app more than once a month. Aim for a benchmark of 50% as a PMF indication.
#4 Power User Analysis
Your power users are your product or service’s most loyal users. This small group of people can influence the usage of your product or features a lot. In some of our own products, this group accounts for more than 40% of all sessions! Why is this group so important? Firstly, it’s because they are the perfect group of people to validate new tweaks or features in your product. Secondly, you should learn everything you can about their needs and expectations. They can show you the way to your product’s growth.
What it is
Power users lend their name to the superpowers they have on your product. They are the subset of people who have meaningful interactions with your product every single day. They love your product, are highly engaged and contribute a ton of value to the network.
If you want to take a deep dive into how you can spot your power users and what you can learn from them, we gladly recommend you take a look at Andrew Chen’s work.
Again, we can look at the shape of the power user curve. If the curve has the shape of a smile, you can smile as well because your product has power users. This is also an indication of product market fit.
Okay, but how can I be sure?
The metrics listed above can give you a clear indication of PMF and will also teach you a lot about your product. They will help you understand what is unique about your product and where users find value. These are the metrics you also want to keep tracking after you find product/market fit.
If you’re looking to optimise and shift your product at a higher pace, starting with a Sean Ellis survey will get you a long way.
But let’s be clear, gathering these data requires several months to mature and support a sustainable conclusion. If you’re looking to optimise and shift your product at a higher pace, starting with a Sean Ellis survey will get you a long way.
#5 The Sean Ellis Survey
In our opinion, The Sean Ellis Survey is the most encompassing method to apply when looking for PMF. The baseline is as simple as it is clever. This method asks existing users of your product how they would feel if they could no longer use it. According to Sean Ellis, achieving PMF requires at least 40% of users to note they would be “very disappointed” without your product.
Besides its clever baseline, you only need a small amount of answers. With only 100 participants, you will have statistically significant results (and with only 30 answers, you’ll already have a great indication). From our own experience, this means that you can start with the survey when you have a mere 1000 active users (who recently experienced the core of your product).
On top of that, the survey gives the opportunity to further question users. You can find out which value they find in your solution and who your actual target market is. After all, you can’t really know the answers to these questions without actually asking your customers about them. These insights are key to growing your product further down the line.
You can find a small demo from a Sean Ellis Survey right here.
Every product is unique: measure what matters
No two digital products are completely alike. It’s never the goal to just blindly apply these metrics as some sort of checklist. For every product out there, one metric might give a better representation than another. Or the combination of multiple techniques gives you a more complete picture of the whole PMF.
Remember Marc Andreessens’ view? “You’ll know PMF when you have it.” Well, now you can measure it. Use your data wisely, don’t hold back on user research and you can find out whether your product, idea or solution holds real potential.