A/B Experiment Register

This template is for logging individual A/B experiments as records, one row per test. It captures the hypothesis, owner, target metric, baseline, measured lift, status, and outcome so the experiment history stays searchable. It is useful when you want a repeatable register instead of scattered docs, spreadsheets, and Slack threads.

The Owner field should be the person responsible for running the test and closing it out, usually a growth manager, product manager, analyst, or marketer. Because it is a user field, you can assign accountability directly instead of writing names in free text. That makes follow-up and review easier.

Update the row when the experiment is planned, when it starts running, and when results are finalized. If your team runs many tests, update status as soon as the test moves between stages so the register reflects current work. The template works best when it is treated as the source of truth, not a retrospective archive.

It fits growth, product, pricing, onboarding, messaging, and conversion experiments where you can define a target metric and measure lift. It is less useful for exploratory research, open-ended discovery work, or qualitative interviews that do not produce a measurable outcome. If the work does not have a clear hypothesis and result, a different tracker is a better fit.

The biggest mistake is storing everything as text, which makes status, outcome, and ownership harder to filter and report on. Another common issue is logging the experiment after it ends but never recording the measured lift or outcome. Teams also often skip a baseline value, which makes the result hard to interpret later.

Yes. You can rename Target Metric to match your team’s language, add fields for variant, audience, sample size, or confidence threshold, and adjust the outcome options if needed. Keep the field types narrow so the register stays easy to sort, filter, and compare across tests.

The leaderboards surface which experiments produced the strongest measured lift and how outcomes are distributed across the register. That helps teams review what worked, what did not, and where to invest next. They are especially useful during weekly growth reviews or experiment readouts.

A spreadsheet can hold the same information, but this template gives you a cleaner record model with typed fields, select options, and owner assignment. That reduces inconsistent entries like mixed date formats, free-text statuses, and vague outcomes. It also makes reporting and review easier because the data is structured from the start.

Common additions include variant names, sample size, confidence level, launch channel, audience segment, and a link to the experiment brief. If you need governance, you can also add approval or review fields before launch. Keep the register focused on the facts you will actually use in decision-making.