Jared Randall

Welcome.

I lead the analytics domain at GALE. I write about data, measurement and analytics, and the decisions they inform.

Writing · 4 pieces

  • incrementality Part 2 · Experimentation at Scale

    When You Cannot Easily Randomize People: Experimentation in Marketing

    Ad experiments cost money, lack power and often cannot randomize people. The designs and standing programs that make marketing incrementality testing routine.

    With variance reduction: 79; Without variance reduction: 49; Earlier Yahoo study: 47020406080With variance reduction79Without variance reduction49Earlier Yahoo study47statistical power (%)
    With variance reduction: 79; Without variance reduction: 49; Earlier Yahoo study: 47020406080With variance reduction79Without variance reduction49Earlier Yahoo study47statistical power (%)
    Statistical power of a Yahoo ad experiment with 570,000 users per group to detect ads earning a 50% return: with the paper's variance-reduction methods, without them, and an earlier Yahoo study. Source: Johnson, Lewis & Reiley, Marketing Science 36(1), 2017

    3,247 words 14 min measurementmarketing

  • brand

    The Brand Playbook for the Automated Era

    Fifteen years of swings in brand marketing, and what automated ads and ads in AI answers change. A playbook for CMOs on brand, creative and analytics.

    4,750 words 20 min creativemarketing

  • AI

    Synthetic Audience Testing: What the Evidence Supports, and How to Do It Well

    LLM-simulated respondents get direction and ranking roughly right, and size, spread and subgroups wrong. What the validation studies show, and how to use them.

    5,040 words 21 min measurementmethodology

  • measurement Part 1 · Experimentation at Scale

    Faster Building Needs Faster Learning: How Amazon and Netflix Test at Scale

    AI makes building faster, but most ideas still lose when tested. What Amazon and Netflix built so faster building turns into faster learning.

    1,868 words 8 min methodologyengineering culture

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