Custom Role as "Cookie" for Filtering User Dashboards and Better Metrics

  • 8 January 2024
  • 1 reply

Userlevel 5
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Here’s something new I’m trying this year…

What: Adding a custom role called “Active in 2024” to active users each month (and retroactively applying the same for 2023. 

How: Calendar reminder to do this on the first Monday of each month. 

Control > User Overview > Filter by Last Activity + Does NOT have the custom role already > Bulk add the custom role

It’s a quick 5 minute task. (Could it be automated? Eh… There’s a webhook for log-in events, but it’d cost you a lot of Zapier runs, etc. The Bulk action of adding the custom role is one of my favorite features)

Then, when I’m using the User Analytics dashboard for monthly or year-to-date reporting, I can filter by this custom role. I’m essentially using it like a tracking cookie.  

Why: Improving my analysis of the User Analytics Dashboard. Now, I can actually make use of the % users with at least 1 post metric that comes out of the box (otherwise it’s just noise IMO: the number of users always goes up, some users will become in active, etc.)

Now, I can filter by this custom role and see the % of users with 1 post within the “addressable market” of users who actually logged-in. I can also do some easy math with the number of new registrations and calculate the % of active users that are new users vs legacy users. 


How You Could Use This: You could use this same “cookie” approach for other intervals like months or quarters. It helps solve the challenge of Last Login / Last Activity being a dynamic field that updates (if they’re active this year/quarter/month you won’t be able to filter by them being active last year/quarter/month). 


What are some other use cases for an approach like this? 

Any other questions or feedback? 

1 reply

Userlevel 5
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Hey @DannyPancratz - this is kind of genius.  😀 I’ve never considered or seen anyone do this, but it’s definitely a smart way of getting better insights out of the current out-of-the-box dashboards.  Particularly the % users with at least 1 post data point, which as you indicate, is otherwise not useful when we’re just looking at all-time users.  This also makes me think of what we might be able to do with the data lake - a chart with a rolling percentage of ‘users who registered in the last 12 months with x posts / activities’, for example.  Amazing stuff Danny, as always.  👏