Decoding Statistical Power: The Key to Precision in Marketing Studies

Author(s): Deepak Chopra | Talking Data Science

Originally published on Towards AI.

Marketing Measurement-4: A layman’s guide to Statistical Power and its interplay with other factors while measuring marketing effectiveness.

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Photo by Thomas Kelley on Unsplash

This article is a continuation of the series on ‘Measuring Marketing Effectiveness’, in case you missed the previous parts, here is a quick recap:

Part 1 highlighted the superiority of experimental design, AB testing, or test-control analysis as the best-in-class methodology for measuring marketing interventions.Part 2 double-clicked into “Marketing Incrementally” via the Test-Control framework and emphasized the importance of formulating hypotheses (both Null and Alternate) in Part 2.Part 3 touched on why “significance” is important for marketing incrementality, what it represents, and how to get to it.

Null Hypothesis (H0) is defined as the hypothesis of… Read the full blog for free on Medium.

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Published via Towards AI