Metadata
- Author: Olga Berezovsky
- Full Title:: Analytical Case Study on User Engagement - Issue 68
- Category:: 🗞️Articles
- URL:: https://dataanalysis.substack.com/p/analytical-case-study-on-user-engagement
- Finished date:: 2024-04-24
Highlights
When analyzing any metric changes, first things first: you work on ensuring the data you see is correct. Find at least two or more other data sources showing a similar decrease to confirm it’s true (View Highlight)
let’s group our hypotheses into three main groups: product, market, and user. (View Highlight)
If the decline we notice is not related to the product itself, our next hypothesis is market (or competition). To confirm it, we would need to see a gradual decline rather than a sharp drop. It would also affect other activity metrics, like views, retweets, comments, etc (View Highlight)
Check country and user location and region data. Are any specific market groups affected, like teens, for example? Or gamers? Or other specific business types? (View Highlight)
User growth speaks of a user base - essentially, how many users use the product. Work on checking the drop against different user cohorts - registered but not active, active, but lapsing, super active (power users), premium or free, business or individuals, or whatever personas you work with (View Highlight)
User behavior is similar to user growth, but instead of user types, you dig into user actions. Your goal is to show that only some pattern of user behavior is affected. For example, you may notice that along with average tweets per user, average comments per user and average likes per user are also declining, but overall sessions, visits, or time spent on an app don’t change. If that is the case, this is a larger issue you now have on hand which you would need to brainstorm about with different stakeholders and partners. It may lead to users “outgrowing” or “maturing” your product and might be suggesting that it’s time to rethink the product offering (View Highlight)