Eventfieldbase turns A/B Test Measurement for Apps into a weekly practice — clearer hypotheses, honest sample sizes, and readouts that survive executive scrutiny.
What teams notice first
We teach you to separate novelty metrics from decision metrics so onboarding tweaks do not get mistaken for retention wins.
Every exercise ends with a one-page readout template you can paste into Slack or Notion without rewriting the story.
Crash rate, support tickets, and checkout latency sit beside conversion so “winning” variants cannot quietly burn trust.
Store review lag, dual-store rollouts, and bilingual UX get treated as constraints — not footnotes in a US playbook.
Featured programs
Pick a path based on whether you own the backlog, the analytics stack, or both.
Flagship path for PMs and analysts who need reproducible A/B readouts for mobile funnels.
Design non-negotiable health metrics before you flip the exposure switch on a risky checkout change.
Peer reviews of event schemas so your experiment data stops arguing with itself mid-flight.
Quotes reference modules you will actually take — no generic praise.
“The sample-size worksheet in Experiment Signal Lab forced us to cut three vanity tests from the Q2 backlog. Painful, then liberating.”Nattapong K., product lead · Bangkok
“Guardrail Studio helped, though I still wish we had more Android-specific exposure math. The crash-rate pairing alone stopped a bad paywall ship.”Client in fintech · Chiang Mai
From the field
Short essays on confidence intervals, SEA store rollout quirks, and why “ inconclusive” is often the honest answer.
Visit the blog
Tell us where measurement keeps slipping — we will point you to the right course or a consultation slot.
Contact Eventfieldbase