One of the best ways to understand your product usage is to analyze which features are being used.
Doing this for every major feature in your product will create an "audit" of the features.
How to define a Feature Audit
The idea is to take your current product, analyze feature usage and plot it on a graph:
Horizontal axis: Popularity is the ratio of the number of people who used this feature to the number of people who used any feature (not only the ones selected in this report)
Vertical axis: Frequency is the ratio of the number of days an event was performed, divided by the number of days any events were performed in your product
In this way, you'll obtain a map of your features
How to exploit the Feature Audit
The Feature Audit template could help you understand which are the best "places" where to run experiments.
If a feature has a high frequency of use but low popularity probably is very useful for a certain kind of persona and less for another. What you have to do in this case is to understand which type of your users (industry, role, etc) are enjoying that feature and then propose it to similar profiles.
If a feature has high popularity and medium/low frequency then probably it's something that is useful for many people but not crucial. If you are not sure which use cases could appeal to certain new users, push them towards a high-popularity one: you'll have a good chance they find it useful.
To do so, use some messaging (in-app messages, emails, etc) and see if your hypothesis were correct by checking if they actually started using that certain feature. Running such experiments will help you to get to know your customer's preferences.
Make sure to explain well the value of the feature: it might seem obvious to you but most of the time it's not for someone who sees your product for the first time.
How to use the Features Audit template
To obtain an overview of your features all you have to do is to pick the events corresponding to the features you want to analyze and select a specific audience if you wish to.
You can add multiple events and / or pageviews to a single feature and give it a custom name.
Grouping events/pageviews built for the same purpose into a single feature on the report allows you to check their collective frequency and popularity.
Here's the audit setup for our features in June!
Understanding high event frequency
If you notice a high frequency in your report, it’s usually due to one of the following reasons:
Event occurrence vs. Non-occurrence
The event is happening on only slightly more days than it isn’t. For example, if a user is active 10 days in a month and triggers the event on 6 of those days, the frequency will be calculated as 60%. You can verify this by opening a specific user profile, reviewing their activity feed, and ensuring the events are being tracked correctly.
Audience filters
There may be a filter applied to the report, showing only users who are more likely to perform this event. This can skew the results toward higher frequencies, depending on the audience selection.
Implementation differences
The event for this feature might be better implemented compared to others. For instance, it could be tracked from the backend, ensuring consistent tracking, while other events might rely on frontend tracking, which can be blocked by ad blockers or certain browsers like Apple Safari.
Keep in mind that this is based on a day-based axis, meaning the frequency is calculated as the percentage of days the event was triggered out of the total days the user was active.