Log experiment results

Record the A/B landing test results from last week: test name, variant A and B conversion rates, sample sizes, start and end dates, primary metric lift, statistical significance, and the implementation decision. Link each result to the Growth experiments database and tag it with 'retention' or 'acquisition'. Verify the metric math and mark the record complete for Friday’s review.

Before I add last week’s experiment to the experiments log, make the outcome readable for the product and marketing leads: put the headline result first (e.g., Variant B +12% signups), show the raw counts and confidence interval right below, call out any secondary metrics harmed, and flag what would make a stakeholder hesitate to build it out.

We ran an A/B test where signups increased but revenue per user dropped 6%. The PM wants to ship the winning signup flow; marketing wants the growth. I’m unsure which metric to prioritize in the record and afraid I’ll bias the log to please the PM. What’s the most likely correct diagnosis of the trade-off, and what precise wording and tags should I use so future reviewers can see both effects without taking sides?

Over time our experiments log became a mess: different metrics, inconsistent tags, unclear decisions. That costs me hours reconciling results before roadmap meetings. Where do we repeatedly lose value, what single template or habit would make 80% of entries usable by anyone, and how do I get product and marketing to adopt it without policing every entry?