Pricing Page A/B Testing — Experiment Design, Statistical Inference & Growth Analytics

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In this video, I walk through a real-world A/B Testing project focused on optimizing a Pricing Page for a subscription-based product.

We cover the entire experimentation lifecycle—from defining the business problem and hypotheses, to metric design (primary, secondary, and guardrails), sample size calculation, and statistical testing.

We will:
1) Design a clean and unbiased A/B test
2) Define exposure, conversion windows, and attribution rules
3) Choose the right primary, secondary, and guardrail metrics
4) Perform sanity checks (SRM, funnel ordering, data quality)
5) Apply one-tailed z-tests and interpret p-values correctly
6) Translate statistical results into clear product decisions (launch, iterate, or rollback)

#ABTesting #ProductAnalytics #DataScience #GrowthAnalytics #Experimentation #Statistics #ConversionOptimization #PricingStrategy #DataDriven #analytics

🧷 If you like, you can walk through the project's materials:
https://github.com/M3hrdad-Dehghan/Da...
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Also, you can find more videos like this in the below playlists:
✔️    • Data Analysis Projects  
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I'd be pleased if you see my profile:
🔶 https://github.com/M3hrdad-Dehghan
🔶   / mehrdad-dehghan