Measuring user adoption
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This is part 3 in a series of articles about measuring Key Experience Indicators (KEIs). In this series I go deeper into the Google HEART framework for large-scale data analysis. The framework was put in place to help choose and define appropriate metrics that reflect both the quality of user experience and the goals of your product. Each article in the series discusses one of the HEART dimensions — Happiness, Engagement, Adoption, Retention, and Task success. Enjoy and use it!
What is adoption?
In the context of products and services, adoption is the act of beginning to use something new.
Considering new features and new users, there are four types of user adoption (see my user adoption model below):
- Internal adoption: When existing users begin using new features. For example, the percentage of existing Instagram users who adopt a new story feature within 1, 7, or 30 days of its introduction.
- External adoption: When new users begin using existing features. For example, the mean number of days new Instagram users create their first story from when they opened their account.
- Adoption flags: When new users adopt new features. A green flag is raised if they’re successful, and no red flags are raised when they’re not.
- Routine adoption: Happens when existing users adopt existing features.
User adoption is an unbiased behavioral measurement and is therefore trustworthy, valid, and reliable.
Why measure adoption?
Understanding people’s adoption behavior toward a thing (feature, service, process, etc.) is extremely helpful in identifying whether or not the thing is providing value. When people are quick to try something out for the first time, it means they care about the problem it is set to solve and that they have high expectations of it. High adoption numbers mean that your thing has promise.
