Growth & Marketing

How do I stop platform-reported conversions from lying to me about what's actually driving sales?

A starting point

Meta and Google both over-claim credit, so if you add up every platform's reported conversions you'll spend more than you actually earned. Trust your bank account and your own analytics over the ad dashboards: compare total ad spend to actual new revenue for the period. When in doubt, run a holdout or turn a channel off for a week and watch whether real sales drop.

Go deeper

Hand-picked from around the web, each with a note on why it earns your time.

3 resources 3 link-checked Watch Read

Watch

▶️ Video
✓ Link checked Free Intermediate

Why we picked it Haus runs incrementality tests for a living, and here their founder talks through how you actually separate ads that cause sales from ads that just show up next to sales that were coming anyway. It grounds the holdout idea (withhold ads from a slice of your market, then compare) in how brands really run these experiments. Watch it once to build the mental model before you design your own test.

Measuring Top of Funnel and Incrementality Testing with Zach Epstein from Haus

On Haus on YouTube by Haus (Zach Epstein) Podcast style conversation, roughly 30 to 45 minutes

Measuring Top of Funnel and Incrementality Testing with Zach Epstein from Haus
  • A holdout is simple in principle: keep ads away from one comparable group or geography, run them for another, and the gap is your true incremental lift.
  • Platform-reported numbers flatter top of funnel spend the most, since that is where overlap with organic demand is largest.
  • You do not need perfect infrastructure to start. A clean geo split and a few weeks of patience gets you a real answer.
Watch on YouTube youtube.com →

Read

✍️ Essay
✓ Link checked Free Intermediate

Why we picked it This is the piece that names the exact trap you are in: your ad platforms each claim credit for the same sales, so the numbers add up to more than reality. Kaushik walks through a plain example where 10 conversions get reported but only 3 were actually caused by the marketing, a 70 percent overstatement. It is the clearest starting point for understanding why attribution and incrementality are not the same thing.

Marketing Analytics: Attribution Is Not Incrementality

From Occam's Razor by Avinash Kaushik About a 15 minute read

  • Attribution just splits credit across touchpoints. It never asks whether the sale would have happened anyway, which is the only question that matters.
  • A large share of conversions credited to paid search or social would have converted organically, from brand, word of mouth, or existing demand.
  • Real incrementality needs an experiment or a proper model, not a prettier attribution dashboard.
Open kaushik.net →
📄 Article
✓ Link checked Free Beginner

Why we picked it If full incrementality testing is more than your team can run right now, blended metrics are the honest shortcut, and this article lays them out cleanly. Blended CAC (total spend divided by all new customers) and MER (total revenue divided by total spend) cannot be gamed by any single platform, because they count every rupee of spend against every real customer. For a small team building outside the big startup hubs, this is the most practical way to stop the platforms from grading their own homework.

ROAS vs MER vs Blended CAC: Which Metric Actually Matters

From Eightx by Matt Putra About a 10 minute read

  • Blended CAC counts all spend against all new customers, so no channel gets to claim cheap wins it did not earn.
  • MER gives you the business level truth: is total spend actually turning into total revenue, across paid, organic, email, and referral.
  • Watch both together. A healthy MER can still hide a CAC your unit economics cannot support.
Open eightx.co →

People also ask

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