
As you ship new things, it is key to understand the penetration of the features within the right audience 🚢.




The most basic measure of a product feature is whether anyone is even using it. 




Luckily, this is very easy to track using June.






## What is feature adoption




Feature adoption is what it sounds like. It’s how much engagement your product gets from its users.




In simpler terms, it’s a measure of how your users interact with your product at the most basic level.




Measuring feature adoption means breaking down your product to see what users are doing. 




It means observing your users so you understand how they interact with your product.







## How to use it




Feature adoption is the degree to which users interact with your product. The more engagement the better.




Managing it involve taking the learnings from your measurement, and improve upon them. 




It means you tweak the product in such a way that your users engage with your product even more, and on a deeper level.







## Taking action on adoption data




Feature adoption data is actionable. Here are some examples for actions you can take with it:




1️⃣ Prioritize work. When certain features show high engagement,  users signal that these features are valuable. It means you may consider developing these features more to make them even more valuable.




2️⃣ Sunset features. The other side of the scale are features that have low or even zero engagement. It means it’s time to stop investing in them and put them to eternal sleep. Less is more.




3️⃣ Inform split tests. Split tests are helpful in choosing between different variations of a feature or element. Adoption data helps in focusing these experiments on product areas that matter to your users.







## Key mistake when measuring feature adoption




User engagement metrics are helpful for organizations. But when businesses first report on total count of actions only it's a mistake. 




When you report the total count, growth usually indicates growth in the number of users rather than usage. 




This doesn't give you the best insight on product health. 




This is why you should run a Feature Audit together with a feature adoption analysis.















Measure how much a feature is used over time

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Find out if a feature get used

Get the most out of your Feature adoption report

Feature release

Find out if a feature get .css-1plvz19{color:var(--chakra-colors-primary);}used

Get the most out of your Feature adoption report

Feature release

Find out if a feature get used