Statistically, there is nothing that guarantees that those 10 people are representative of who we think our target users are though. Going back to the checklist above, we need to walk through the steps in Product/Market fit. Can I reach the right people for this solution? Is this an important problem for enough people? Is someone already doing this much better? In the long term, would people find it valuable enough to continue using? There is a slew of questions to answer before being able to establish Product/Market fit. Again, Problem/Solution fit is really just your and those 10 people’s hypothesis of what the market might like. Testing the solution with the market is a separate step.
When we started working on Leanrr.com we had a simple vision. We imagined a world where everybody is healthy and beautiful. By talking to about 100 people we found some of the biggest problems were around misinformation, getting started, and sustainability. We recruited a few colleagues and friends to embark on a weight loss journey with us. After a lot of iteration and failure we found the critical steps to success:
I was able to go from 15% to 8% body fat in 3 months myself. It was easy and felt incredible! We wanted to get the word out.
Unfortunately, product/market fit was an entirely different story. We had 500,000 target users view our ads and 5.6% click through to the landing page. 20% of those who clicked signed up but only 0.1% of them got their BodPod measurement! We were hit with the market reality. The lesson for us was to simultaneously search for a market while continually making the solution simpler. Even if you have a great solution it still takes a lot of work to get to a point where you’re able to get the right people interested and invested.
Another important topic is how to measure whether you’ve improved product/market fit.
For large products where there are several markets and value propositions you can perform Market tests using A/B testing. By focusing on metrics that are representative of the user problem you are trying to fix, you can see if for the majority of users the change was a positive addition. The key thing is looking at your product as a system when evaluating these changes. Don’t just measure how you’ve changed the particular user experience but see how you affect the feature and value proposition involved. (More about Market/Product pyramid here.)
Conventionally, in Outlook it usually takes us 3-5 A/B tests before we’re able to establish whether a feature improved product/market fit. The steps we tend to go through and measure:
If you are a smaller product you can’t use A/B testing. That’s because you don’t have a significant portion of your market captured nor do you have a statistically significant amount of usage. What you would want to observe is how the new user cohort retention reacts to changes. This works quite well in practice because the market and value propositions of the product are simple and you should have a good idea about what caused an improvement or a dip. You can still do this for bigger products but in conjunction with A/B tests to discern what is causing the effects and for whom.
I’ve never directly worked on business model fit so I don’t have any learning to share. I’ll update this part when I do. 🙂