A/B Test

By Dan Kurtz August 6, 2026 1 min read

An A/B test compares two versions of a single element (a headline, a button color, a form length) by splitting incoming traffic and measuring which version produces the better outcome. It isolates a single variable to prove causation.

A/B tests fail more often from bad setup than from tie results. Common mistakes: too many variables changing at once, too little traffic to reach significance, calling the test before it converges.

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Dan Kurtz

Founder, Miss Pepper AI

Dan Kurtz is the founder of Miss Pepper AI. He works on a problem most businesses are only starting to feel: buyers no longer just Google you — they ask an AI, and the AI decides whether you get mentioned at all. Dan built Miss Pepper AI to help companies get found, trusted, and recommended in that new reality, pairing AI-assisted sales and marketing with a practical approach to GEO (generative engine optimization / AI visibility). His focus is plain and unglamorous: make a business genuinely easy to understand, cite, and choose — for search engines, for AI assistants, and for the humans on the other end. He works hands-on with the systems, content, and positioning that move that needle, and writes here about what actually works versus what just sounds good in a pitch deck. No jargon for its own sake, no hype — just what helps you win the recommendation.

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