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Mobile app A/B testing is how you show two versions of something inside your app and measure which one gets more taps, signups, or purchases. Same goal as web A/B testing. Completely different mechanics. It's one piece of app conversion rate optimization, which covers ...

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Statistical power and power analysis for A/B tests: the planning step most teams skip

Power analysis answers a simple question: do I have enough visitors to trust my A/B test results? It tells you how many visitors each version needs and how ...

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Type 1 vs type 2 errors in A/B testing: what they are and why they cost you money

A type 1 error means your A/B test says "we have a winner" when there's no real difference. A type 2 error means your test says "nothing happened" when there ac ...

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UX conversion optimisation: where user experience and conversion goals collide

UX conversion optimisation is the practice of studying your visitors and using what you learn to get more of them to convert. How they behave. What confuses the ...

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Website personalization: why most small teams aren't ready (and what to do instead)

Website personalization means showing different content to different visitors based on who they are or what they've done on your site. A returning customer sees ...

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A/B test sample size formula: how to calculate it (with worked examples)

The A/B test sample size formula is: n = (Zα/2 + Zβ)² × [p₁(1−p₁) + p₂(1−p₂)] / (p₁−p₂)² If that looks like gibberish, you're not al ...

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The best A/B testing software in 2026 (honest buyer's guide)

Kirro, VWO, and Optimizely lead the pack for most teams. But the right A/B testing software depends on your traffic, budget, and willingness ...

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A/B testing conversion rate: how to measure, track, and actually improve it

Your A/B testing conversion rate is the percentage of visitors who do what you want (buy, sign up, click) in each version of your test. Compare the rates betwee ...