Backtracking Metrics for Product Iterations

Achieving specific metrics can be a time-intensive endeavor, often requiring iterative refinements. Take, for instance, the pursuit of 1-month retention metrics, which often necessitate multiple incremental adjustments over an extended period.

One strategy to enhance product efficacy and development can be backtracking from the desired metric to its associated metrics. For instance, backtrack from 1-month retention to 1-week retention, then further to 1-day retention. There’s a significant correlation between Day 1 (D1) retention and Day 0 (D0) time spent on the app, so closely monitoring the D0 time on app could be a good lever as well.

By establishing the correlation between D0 time on the app and D1 retention, we gain insight into extrapolating outcomes, such as estimating D7 retention and subsequently, Day 30 retention.

The overarching implication is that optimizing for 30-day retention typically influences various other metrics, facilitating easier and quicker measurement and subsequent improvement in the long term.

This is, ofcourse, app and product specific, but can be something useful to keep in mind.