If you manage ad campaigns across multiple platforms, you might have run into this headache: if you add up the conversions shown by Meta Ads, Google Ads, and TikTok Ads, the total far exceeds the actual sales in your bank account or Shopify.

Why does this happen? The answer is simple: each platform lies in its favor.

1. The attribution window bias

Each advertising platform uses its own rules and timeframes to attribute a sale:

  • Meta Ads (Facebook/IG): Counts conversions up to 7 days after a click and 1 day after the user only views the ad (without clicking). The latter is known as View-through.
  • Google Ads: Usually counts 30 days after a click. Takes credit for closing the sale (generally brand searches).
  • GA4: Is a neutral tool. It attempts to distribute credit fairly across multiple channels using Data-driven models.

2. Attribution Simulator and Double Counting

Simulate the journey of a user who wants to buy a $100 product. Toggle the interactions they have with your ads and observe how platforms claim the sale.

Step 1: Activate user touchpoints

The user finally purchases on the website (1 real sale of $100).

Conversion Claims
  • Meta Ads claims: $100 (1 sale)
  • TikTok Ads claims: $0 (0 sales)
  • Google Ads claims: $100 (1 sale)
Sales Reported by Channels: 2
Real Sales in Bank: 1
Over-reporting Error: +100%

3. Click-through vs View-through: The visual trap

To understand why Meta or TikTok’s results are inflated, you must separate the nature of the interactions:

  1. Click-through (CTC): The user clicked on the ad and bought within the window. This is highly reliable data of real interest.
  2. View-through (VTV): The user only viewed the ad while scrolling on Instagram, didn’t click, but searched and bought the product the next day on their own. Did the ad really cause the sale, or was the user already going to buy and the ad coincidentally appeared beforehand?

Platforms enable View-through by default to inflate the ROAS of their dashboards and make their campaigns seem more profitable than they are.

4. The Hierarchy of Truth in Analytics

As an analyst, never use the ad dashboard numbers as the definitive truth. Establish a pyramid of trust for your data sources:

  1. LEVEL 1: Your Database / CRM (Shopify, Stripe): The absolute truth. What you actually collected in money.
  2. LEVEL 2: Google Analytics 4 or Server-Side: The neutral measurement from your own domain acting as an impartial referee.
  3. LEVEL 3: Ad platforms (Meta, Google Ads): Useful for internal optimization, but they are biased judges.