A/B Experiment Register

This template is for logging individual A/B experiments in a structured table so each row captures the same core fields. It helps teams compare experiments by lift, status, and result without digging through docs or chat threads. Use it when you want a single source of truth for growth, product, or marketing tests.

The Owner field is a user column, so each experiment should have one accountable person or small team assigned. In practice, product managers, growth leads, analysts, or marketers often maintain the record while contributors update their own rows. The key is to make ownership visible so experiments do not stall in Draft or Running.

Update the row when the experiment is created, when it starts running, and when it concludes. If your team reviews tests weekly, that cadence works well for keeping Start Date, End Date, Status, and Result current. For faster-moving programs, update the register as soon as a test is launched or stopped.

A good row has a clear hypothesis, one primary metric, a defined owner, and a final result. The Lift Percent field should reflect the measured change for the chosen metric, not a vague impression of success. If the test has multiple outcomes, keep the register focused on the primary decision-making metric and note the rest elsewhere.

Yes, and it should. The Result select includes Win, Loss, and Inconclusive so you can track all outcomes instead of only celebrating successful tests. Recording losses and inconclusive tests helps prevent repeat work and makes it easier to see which ideas are worth revisiting.

A spreadsheet can work for a small number of tests, but it often breaks down when fields are inconsistent or ownership is unclear. This template enforces a narrow set of columns and typed fields, which makes filtering, sorting, and leaderboard views much easier. It also keeps the record format consistent as the experiment program grows.

This register works best when paired with analytics tools, feature flag platforms, or experiment result dashboards. Teams often link the Metric field to the source of truth in their analytics stack and use the Owner field to route follow-up work. If you already track experiments elsewhere, this template can act as the summary layer.

The most common mistake is using free text where a select or number field is more reliable, which makes reporting messy later. Another pitfall is leaving Lift Percent blank or mixing different metrics in the same row, which makes the leaderboard misleading. Keep the register focused on one experiment per row and one primary result per row.

Start by confirming the Status and Result options match your workflow, then adjust the Metric field naming to fit your analytics vocabulary. If your team tracks variants, audience segments, or experiment type, you can add those columns later as long as they stay narrow and typed correctly. Keep the first version small so it is easy to adopt.