Why Your Meta ROAS Doesn’t Match Shopify (And Which Number to Trust)

Open Ads Manager, then open your Shopify dashboard, and you will probably find two different revenue stories. Add Google Ads and Klaviyo and you have four. Most store owners assume one report is broken. In reality, every tool is working as designed, and each is simply counting differently.

Why Do the Numbers Disagree?

Every platform uses its own window and its own model. Picture a shopper who clicks a Meta ad on Monday, a Google Shopping ad on Thursday, and opens a Klaviyo email on Friday before buying. Meta, Google and Klaviyo can each claim that order. Shopify’s channel report gives the sale to the last non-direct click. One purchase, several owners.

That is why adding up platform-reported revenue almost always exceeds what the store actually took.

What Each Tool Counts

Meta’s Own Definitions Changed in 2026

Even within Meta, the ground has shifted. From 12 January 2026, the Ads Insights API stopped returning 7-day and 28-day view windows. Then a rollout from March 2026 narrowed click-through to link clicks and moved likes, shares and saves into a new 1-day engage-through window.

The result: accounts with heavy social engagement saw click-through conversions fall and reported ROAS move, while sales stayed the same. Any trend that crosses those dates mixes two definitions.

A Longer Window Is Not Always Generous

It is tempting to assume platforms over-claim. The data is more mixed. Across 640 Haus experiments, Meta’s 7-day click reporting under-counted measured incrementality by about 15% on average for brands selling only on their own site. Brands with a quarter or more of sales elsewhere saw roughly 32% of Meta’s measured effect land outside their store.

So Meta can be too high on one order and too low on another. Only store data and tests settle it.

Which Number Should You Trust?

Use the store as your anchor. Judge overall performance on blended revenue and new customer revenue, and use Meta’s ROAS to compare campaigns within the account. Then run a simple check: over several weeks, does reported ROAS rise and fall with new customer acquisition in your store data? If it does, steer by it. If ROAS climbs while new customers stay flat, the window is crediting Meta for sales it did not earn.

Watch customer mix too. At a womens fashion brand we work with, first-time customers rose from about 52% of revenue in January to August 2025 to about 78% in the same months of 2026. That figure is blended across all channels and no incrementality test isolated Meta’s share, but a shift that large changes what any window measures.

Conclusion

The mismatch between platforms is normal, not a tracking failure. Pick one window, keep it fixed, record when it changes, and judge success on store revenue. For the full breakdown, see our guide to the Meta attribution window, and our guide to a good ROAS for setting targets from margin. If your reports still disagree, our tracking and attribution service can reconcile them, or book a free growth audit.