How to Measure Feature Adoption?

Feature adoption is exactly what it sounds like — it refers to any metric that measures user activation for a specific software feature. It allows you to assess the extent to which your customers are using each feature or function of your software. It’s typically measured through feature adoption rate, a metric that expresses the number of customers using a specific feature as a percentage of total subscribers.

Calculating Feature Adoption

Measuring feature adoption is relatively simple. First, you need to define your feature adoption funnel. How many times must a customer use or access a particular feature before you consider them adopted? What are the different stages of feature adoption?

ProjectBI’s Feature Adoption Funnel is an excellent starting point in this regard, breaking adoption down into four steps:

  1. Users who have been exposed to a feature and viewed the area of your interface where the feature exists.
  2. Users who have accessed the feature at least once are considered activated.
  3. Users who have accessed the feature and then used it at least once have reached pre-adoption (referred to by the funnel as ‘used’).
  4. Users who access and use the feature again after the first time have adopted it.

You may choose to add additional stages to the funnel if you want feature adoption to require more than a few uses of the feature.

Product vs. Feature Adoption

Product adoption and feature adoption are often conflated with one another. In fairness, the two metrics are very closely related. They are also incredibly complimentary when expressed as metrics.

Also known as user adoption, product adoption is known as the moment a customer truly starts deriving value fromr your software — the “aha!” moment where they fully understand what they can do. Product adoption rate, meanwhile, expresses the number of first-time users who perform a set of behaviors indicating adoption. As with feature adoption rate, this is expressed as a percentage.

Why Measure Feature Adoption? 

There are several reasons feature adoption is a valuable metric for your business.

First, it allows you to evaluate feature discovery, potentially identifying problems in your customer education. For instance, say the adoption rate of a particular feature is only 25%, meaning customers may not be aware of that feature. Upon investigation, you’re able to identify an oversight in your onboarding process — it doesn’t adequately walk customers through how the feature works.

Upon correction, you see that feature’s adoption rate increase to 75%.

In addition to defining both successful and overlooked features, measuring feature adoption allows you to identify weaknesses and shortcomings in your software’s user experience. Imagine there’s a different feature that no one seems to be using. However, once you evaluate your training process, you see no indication that the feature’s been overlooked.

Following this, you opt to investigate the software itself. You immediately discover that there’s a critical bug that impedes the use of the feature. Without measuring feature adoption, you likely wouldn’t have learned about the issue until much later, at which point it may have already cost you customers.

Finally, if a feature is neither overlooked by onboarding nor difficult to use, it may be worth considering that the feature simply isn’t relevant to your users. You may be able to remove it from your software altogether without damaging the user experience. Though with that said, you may want to send out a user survey prior to making that decision — just to ensure you don’t alienate someone who may still be using the feature.

Measuring the adoption rates of various core features of your software can also help you determine which of those features are most closely associated with product adoption. You can achieve this through the following process:

  1. Choose a timeframe. Typically, you’ll want to choose one that’s no shorter than a month and no longer than a year.
  2. Look at the prospects that became paying, recurring customers during this timeframe. What features are they using most frequently?
  3. The features most prominently represented amongst prospects who became customers are likely the ones you’ll want to prioritize to improve your product adoption rate.