Attribution breaking down? Here's the one thing that actually fixes it (without arguing about UTMs or last-touch nonsense). Most teams I meet are stuck in the same loop: CAC looks fake, Meta + Google both claim 120% of revenue, and the board wants “efficiency” while every dashboard tells a different story. Incrementality modelling is the only way I’ve ever seen to cut through that fog. I just published a short breakdown on how I build a practical incrementality framework using synthetic control models no academic fluff, just something a growth or demand team can actually run and defend. If you're dealing with budget cuts, channel overlap, or proving paid lift beyond organic intent, this will help.Dropping a quick breakdown from a recent incrementality project for a mid-market SaaS team that kept reporting “channel growth” but wasn’t seeing any revenue uplift. We ran two things:
GEO Holdout Test (4 weeks)
Synthetic Control Modelling (8 weeks)
Headline result: Only 62% of the conversions that Google/Meta claimed were actually incremental. The rest? Cannibalization, retargeting bias, branded leakage, and last-click magic tricks. Key lifts:
+13% true incremental lift after adjusting for organic baseline
CAC dropped from $412 → $274
$180K/month in wasted spend eliminated
Branded search: 17% incremental
Meta retargeting: 22% incremental (yes, really)
Prospecting: 64% incremental
Once the dust settled, payback dropped from 9.1 → 5.8 months, and we shifted budget toward actual net-new creation (content, product activations, partnerships). Takeaway: If you haven’t run a proper holdout or synthetic model in the last 12 months, your ROAS is probably lying to you. If anyone’s working on measurement frameworks or rebuilding attribution models post-cookie death, happy to swap notes.
