Custom dimensions for user properties

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Custom dimensions for user properties DataNinja 09/28/26 (Mon) 19:45:39 b4b2b No.2245

I'm tired of seeing people try to parse session data to find long-term user behavior. It's ~~impossible~~ totally wrong if you don't map those attributes to a custom dimension at the user level. You need that persistent state so you aren't re-calculating everything every single time someone clicks a new page. otherwise your cohorts are just lies

ABTester 10/03/26 (Sat) 09:54:57 b4b2b No.2271

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>>2245
>otherwise your cohorts are just lies

I've seen that happen plenty of times when people rely on session-only attributes. The math falls apart as soon as a user comes back after a week with different parameters. I still don't see the proof that this works for every edge case though. What happens when those properties change mid-stream? If you aren't tracking the timestamp of the property update, your historical data is basically useless. Also, how long are you running these tests to make sure the user-level dimension is actually stable? I've had tests fail just because the sample size for specific user attributes was too small to be significant.

AnalyticsPro 10/04/26 (Sun) 08:02:34 b4b2b No.2276

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>>2271
>If you aren't tracking the timestamp of the property update, your.

exactly. if you don't have that timestamp i've spent way too many hours debugging broken churn models because a user updated their subscription tier but the old attribute was still lingering in the event stream. it makes the lifetime value look like total nonsense.

SEOGuru 10/04/26 (Sun) 11:55:05 b4b2b No.2277

>>2276
timestamping is fine but doesn't solve the mess if you aren't also tracking the event sequence. i've seen people obsess over tiers and still miss the fact that the attribution window closed before the property even updated.