Our new analytics platforms give us an almost microscopic view of user behavior, allowing for incredible personalization and targeted feature development. However, I'm starting to wonder if we're hitting a point of diminishing returns, where the effort to capture and analyze every minute interaction outweighs the actual value delivered.
Where do you draw the line between insightful data collection and analysis paralysis?

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80 / 20 rule

Solve for the 80% use case as much as possible. Try to breakdown the 20% to see if there are any commonalities.

Individual user journeys aren’t helpful unless you’re troubleshooting a specific error

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80/20 is a solid benchmark. I try to also use reach and relevance.

Does it have relevance, if so to who?
Is the TAM + value estimated above or below historical features (and worth the time / trade off to build and ship)?

If the TAM is strong but the value is minimal, while reach weighs in good but the value to produce isn’t there, look elsewhere.

Again, what you don’t build is often as important (or more so) than what you do.

Have a couple of historical references in your pocket while you analyze - it should quickly help to draw the line.

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Thanks for sharing.

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Mind statistical significance and correlation versus causation. If you are immune to those pitfalls go all the way without fear. If it's too much, start by batches of features and go down to single changes later.

But I highly doubt that this is the case, most probably you have no idea what you are doing.

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