Marketing

Sanity-checking attribution logic

Use AI to sanity-check attribution logic and measurement reasoning, helping identify gaps, inconsistencies, or flawed assumptions in how performance is credited.

Why the human is still essential here

Measurement design and accountability remain human-led; AI can point out issues, but humans validate with data and decide what to change.

How people use this

UTM and event taxonomy review

Share your UTM conventions, naming rules, and key event definitions so AI can spot inconsistencies and missing fields that break channel reporting.

ChatGPT / Claude

Attribution model assumption critique

Ask AI to compare your current attribution approach (e.g., last-click vs data-driven) and enumerate expected biases by channel and funnel stage.

ChatGPT / Perplexity

GA4-to-BigQuery discrepancy triage

Describe a reporting mismatch (GA4 vs ad platforms vs CRM) and have AI propose likely causes and the exact queries/checks to isolate the break.

Google Analytics 4 / BigQuery / Gemini

Community stories (1)

LinkedIn

Over the past few months I’ve been using AI a lot more in my day-to-day work in performance marketing.

Over the past few months I’ve been using AI a lot more in my day-to-day work in performance marketing.

Not for content. Not for gimmicks.


Mostly to improve the quality of my thinking.


I’ll run allocation decisions through it before I move budget.

I’ll pressure-test incentive models.

I’ll use it to sanity-check attribution logic.

Sometimes I’ll rewrite an exec update three different ways until it’s tighter.


The biggest benefit hasn’t been automation. It’s clarity.


It forces sharper framing.

It challenges assumptions.

It makes iteration cheaper.


I’m curious how other growth leaders are using AI in practical ways — especially in paid acquisition or forecasting.


Where for you has it genuinely improved decision-making?

RY
Ross YaderGrowth and Performance Leader
Feb 24, 2026