Decode the hidden logic of your customers through experimentation.
An A/B result is only as trustworthy as the system that produced it. This audit framework examines eligibility, assignment, bucketing, identity persistence, exposure, sample-ratio mismatch, metric definitions, conversion windows, and statistical analysis. It also introduces the Zero Experiment: a production A/A calibration test designed to reveal whether the system creates lift where no treatment exists.
PostHog’s JS web SDK now includes getAllFeatureFlags(), which returns every currently loaded flag in one call. Each flag includes its key,…
One of the useful PostHog experiment updates from May 21, 2026 is the new organization-level default minimum detectable effect, or…
This was one of our juicier and more layered experiments. Admittedly, it was a mistake to test multiple hypotheses within…
You can run a trustworthy PostHog A/B test on Shopify without installing a dedicated testing app. The difficult part is…
Running an A/B test on WordPress with PostHog is possible, but the setup needs more care than a simple tracking…
We optimize experiences for a living. Of course we use cookies.
