Blended vs Platform ROAS: The Attribution Maths Cheatsheet
MER, aMER and platform ROAS formulas, attribution-window comparisons and the reconciliation workflow for spotting a normal reporting gap versus a broken pixel.
Platform ROAS and blended ROAS almost never match, and the gap isn't automatically a tracking bug. This cheatsheet lays out the exact formulas, the attribution-window comparison and the weekly reconciliation workflow we use to tell a normal reporting gap from a genuinely broken pixel.
Why platform ROAS is structurally optimistic
Every ad platform grades its own homework. Meta counts a sale if someone clicked your ad and bought within 7 days, or merely saw it and bought within 1 day — even if they clicked a Google ad in between. TikTok does the same on its own window. Run three platforms at once and you can have three different 'sales' all claiming credit for the same order, while your Shopify dashboard only shows one. None of that is fraud; it's just each platform's attribution model working exactly as designed. The fix isn't to distrust platform ROAS entirely — it's to know how much air is normally baked into the number for your setup, so you can spot when the gap moves outside that normal range.
MER, aMER and blended ROAS aren't the same number
MER (marketing efficiency ratio) is total revenue divided by total ad spend — no attribution model, no per-platform claims, just what came in versus what went out. aMER adjusts that revenue for discounts and returns, so it reflects what you actually kept. Blended ROAS is the same maths as MER expressed as a ratio instead of a percentage. Platform ROAS is a different animal entirely: it's built on that platform's self-reported, windowed attribution and will almost always run hotter than blended. Scaling decisions should be made on blended MER or aMER, never on a single platform's own number in isolation — that number tells you relative creative performance within the platform, not true profitability.
The weekly reconciliation habit that catches broken tracking early
Every Monday, pull two numbers for the prior week: total Shopify revenue divided by total ad spend (blended), and the sum of every platform's self-reported revenue at a matching 7-day-click window divided by the same spend. Compare the gap percentage to last week's gap, not to some universal 'good' number — your own baseline is what matters. A gap that holds steady week over week, even if it's 35-45%, is just how your stack over-reports. A gap that jumps 15+ percentage points in two weeks means something changed: a pixel fired wrong, a CAPI event dropped, or a platform update broke your setup. Catch that in week two, not in month two. Keep this cadence separate from creative testing — if you're batch-producing hook variants in a tool like Klip Kanvas, a tracking blip should never be the reason a genuinely winning hook gets paused.
5 reference tables inside: the core attribution formulas, platform-vs-Shopify gap bands by window, an attribution-window comparison table, the 7-step weekly reconciliation workflow, and MER benchmark bands by margin and spend tier.
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