Why your Google Ads ROAS falls apart when you scale it
True Omnichannel MER is Adbuffs’ measure of real efficiency — net-delivered revenue across D2C, marketplace, and quick-commerce, over fully-loaded spend.
Meta optimises on the conversions it can see. On a typical campaign only about 1% of the people it reaches click through to your site, so it makes spend decisions on a sliver of the real result. Every sale in a store, over the phone, or anywhere off your site is invisible to it.
Offline CAPI feeds those hidden conversions back, so Meta optimises toward people who actually buy, not just people who click. Once it’s running, it stops being a report and becomes part of how the algorithm delivers. Pull it out and performance degrades across the whole account, online included. That’s the difference between treating signal as attribution and treating it as infrastructure.
Most teams file conversion tracking under “measurement,” a thing you set up to see results. That framing is why offline signal gets cut first when budgets tighten: if it’s only a report, losing it feels harmless. It isn’t a report. It’s a feed into a live optimisation engine.
Add up the revenue that happens off-site (store, phone, events) as a share of total. If it's more than a rounding error, Meta is optimising half-blind right now.
Get those off-site purchases to the algorithm as an enriched signal, and keep offline on its own pixel so you can read its contribution honestly.
Once it's feeding delivery, cutting it to "test if it matters" is the exact test the brand above ran. It cost them a quarter of their revenue, for over two months, to fail it.
True Omnichannel MER is Adbuffs’ measure of real efficiency — net-delivered revenue across D2C, marketplace, and quick-commerce, over fully-loaded spend.
True Omnichannel MER is Adbuffs’ measure of real efficiency — net-delivered revenue across D2C, marketplace, and quick-commerce, over fully-loaded spend.
This shows up in every high-repeat category sooner or later, and sanitary pads are a clean example because people reorder within weeks. We ran into it on one account. Excluding existing buyers to chase new ones made the algorithm perform worse, not more targeted. Leaving them in fixed that, but for a reason that turned out to be its own problem.