Introduction
We all know that measuring feature adoption can be a bit of a guessing game. Businesses make changes they think will improve the customer experience, but often fall short when it comes to measuring the impact of those features on the user experience.
Knowing if users are interacting with a feature, and how frequently, is such an important part of improving adoption and ultimately retaining customers. Take a look through these useful charts to get a baseline understanding of how to measure feature adoption!
In-app dashboard template: Feature adoption
| Name | Description |
| Active Usage | An event that you use to define an active user when counting daily/weekly/monthly active users (choose "Session" if you define an active user as any visitor) |
| Feature Start | An event that captures the first step in a feature workflow |
| Feature End | An event that captures the last step in a feature workflow |
Chart 1: Feature Usage
What does it tell you?
This chart surfaces how many times a particular feature has been used each day, over a 30 day period.
How to interpret?
This provides insight into how frequently used your feature is. This can allow you to determine how valuable the feature is perceived by your users. Ideally, you see an upward trend here as you improve your feature set and enable users on the feature.
Chart 2: Workflow Conversion Rate
What does it tell you?
This chart will show you how many of your users complete the start and end steps in your feature’s flow.
How to interpret?
Here you can understand the baseline conversion rate of your feature usage by looking at the number of individual users who make it from your start event to your end event.
Chart 3: User Count
What does it tell you?
We already have a chart that looks at how often the feature is being used on a daily basis, but this chart will tell you how many unique users are interacting with the feature on a daily basis.
How to interpret?
How many users are using the feature? Use this as a baseline to make improvements on.
Chart 4: Workflow Conversion Rate Over Time
What does it tell you?
We already have a chart that looks at the conversion rate of the feature’s usage, but it’s equally important to understand how your conversion rate may fluctuate over time.
How to interpret?
This chart will show you what percentage of users who make it from your start event to your end event over a 30 day period. Do you notice any dips or spikes in conversion? If so, do these dips or spike line up with changes to the feature, the release of additional guidance, or resources?
Chart 5: Usage Frequency
What does it tell you?
We’ve taken a look at how frequently the feature is being used overall, and how many unique users are using the feature, but this chart shows a direct ratio of how many times individual users are engaging with the feature.
How to interpret?
In this line chart you can not only see the changes in day to day usage and overall trends over time, but you can also see the direct ratio of unique users engaging with your feature to the number of times they use the feature - ultimately uncovering the level of engagement on average.
Chart 6: Adoption Rate
What does it tell you?
This chart uncovers, of your active users, what percentage of those users have interacted with your feature.
How to interpret?
The goal here is to see a high ratio of A to B. This will indicate your active users are engaging with your key feature. The higher the percentage, the higher adoption of the feature among your most valuable user base - the active users!
Chart 7: % Sessions Adoption
What does it tell you?
Instead of looking at the percent of active users who perform your feature end event, this chart takes it a step further and looks at the percent of sessions that the feature has been adopted.
How to interpret?
This is important because it is a true indicator of baseline adoption. This directly compares the number of sessions where your active usage event is performed against the number of sessions where your feature end event is performed. While it is nearly impossible to get these 2 numbers to match and have a 1:1 ratio, this can still shed light on how frequently the desired feature is being used in sessions compared to users who are actively engaging with your tool.
Measuring feature adoption is one of the primary goals of any product team. It is just as important to understand what your users are finding valuable as it is what they don’t find valuable. Throughout each of these above charts, it will be important to look at the segments of users who are and are not interacting with certain features and adjust accordingly. If you are finding there is little adoption of your feature, take a deeper look into where drop-off is occurring in the usage funnel, or even try to A/B test walk-through guides.
Then, keep measuring! This is an iterative process. Get the data, look for insights, take action, then go back to the data to measure the results of your work!
Adoption of a feature is one of the primary points of measurement for any business looking to ultimately retain their customers. Knowing if features are being adopted shows a continued value in your tool and ideally results in a lifelong customer base!