Most A/B platforms sit on their own event pipeline, so the win-rate they report does not match your dashboard.
Experiments
A/B tests evaluated where your data lives.
Run experiments on the same event stream that powers your analytics. The numbers in the report match the numbers in every chart.
- Every visit included
- Inputs never recorded
- EU-resident by default
Experiments
- Signal
- A/B
- Coverage
- 95%
- Decision
- p99
Why split testing is usually noisy
Late-stage tests need stratified analysis. Cheap tools only do single-segment comparisons.
Statistical significance gets reported, but practical significance (lift size, confidence interval width) usually does not.
How leadmaps does it
Clean first-party evidence, presented clearly enough for the whole team to act on.
01Variants assigned in the SDK.
Stable, sticky assignment per visitor. No flicker on first paint, no leakage across reloads, no double-bucketing.
Stats, every night.
A nightly job computes p-value, lift, and confidence intervals on every active experiment. Wake up to a clear answer instead of poking at spreadsheets.
Stop on win or stop on harm.
Set thresholds for ship-it and kill-it. The system flags the moment you cross either line, so you do not run a losing variant for two extra weeks.
04Segmented analysis, no replumbing.
Filter the experiment view by any event property. The bucketing stays consistent, the conclusions stay honest.
Ready when you are
Turn the next question into a clear answer.
Keep the raw signal, the decision, and the context in one privacy-first workspace.
Signal ready100%