An attribution model decides how a conversion's credit is distributed when multiple touchpoints (ad clicks, ad views, other channels) preceded it — Meta's own reporting defaults to last-touch attribution within its own platform, which naturally overstates Meta's contribution when a customer also saw ads on other channels or came through organic search.
Because every platform tends to attribute conversions to itself under its own model, comparing self-reported ROAS across Meta, Google, and TikTok side by side without a shared, platform-agnostic attribution model (or falling back to MER) routinely leads to double-counted revenue and inflated combined performance expectations.
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