User Analysis for Early Stage Startups

“We must learn what customers really want, not what they say they want or what we think they should want” - Eric Ries

User feedback is essential in designing and refining a product, but a user can tell us a lot more than what they have to say. Most companies run traditional analytics to gain insights on user behavior which are used in decision making for product management. So, what is stopping early-stage startups from employing a similar strategy? The answer is often the small sample size.

Many startups, particularly B2B SaaS startups, don’t exponentially grow their user base during their first few years. In fact, many products are designed for a niche market that does not acquire hundreds of users. However, a small sample size should not prevent startups from doing an effective user analysis.

A simple feedback survey or a Net Promoter Score (NPS) is a starting point but it only gets a small portion of the information we would want to receive from our users. A much more effective strategy is to perform Individual User Analysis on each of the users. Individual User Analysis is studying the user behavior at a much more granular, discrete level. Here, we’re actually analyzing how individuals interact with our platform — as opposed to asking them.

For instance, if a user refers to documentation every time after using a certain feature, then is likely that the user interface is complicated and not intuitive enough for the user. Or, if the user is not using features that we think are valuable, maybe that either shows the user is not fully aware of our value proposition or that we are trying to solve a problem that may not be a problem to start with. Or, understanding the most commonly used features by a user can help us prioritize the development work.

While Individual User Analysis is an effective tool, there are some precautions that must be taken. There is no one single procedure or formula to set up such analysis. So it can be a cumbersome process. Often, the initial users are much more loyal and are non-representative of a later stage user base. In fact, each user is unique, and care must be taken to not build features only for a single user.

At Intrinsik, we work hard to deliver the right product for our users by listening to them, in any way possible, and minimizing guesswork. In cases where traditional analytics are not possible, Individual User Analysis is our best tool.