I ran parallel brand-lift studies in Q4 on the same creative and audience and saw +6 pts from Upwave and +1 pt from Kantar across YouTube and CTV. For brand positioning and competitive read (SOV vs consideration), which tool are you treating as decision-grade, and do you normalize results to a house MMM or attention metric? I’m trying to lock a consistent source of truth before a head-to-head with our closest competitor next month.
When I see a “+6 vs +1” split on the same YouTube/CTV flights, I treat Kantar as decision-grade for positioning/SOV and calibrate Upwave with a fixed factor we built from a Q4 overlap tied to our MMM baseline so everything rolls up on one incrementality scale. Small caveat: re-estimate that factor each half when the creative rotates, and I’m curious if you had YouTube Brand Lift running to set the CTV multiplier.
I’ve had better consistency by running a small dual-read cell (same audience, same flight) that both @Upwave and Kantar survey, then aligning their lifts by frequency/device buckets and anchoring the overall magnitude to our “house MMM” elasticity for brand→sales. It’s one extra setup call, but after we set the ratios we can reuse them across quarters without re-normalizing unless creative or mix shifts materially.
In Q4 I closed a +6 vs +1 gap by having @Upwave and Kantar re-cut on a common exposure rule and reporting lift per 100 TRPs by platform (YouTube vs CTV), then I feed that into MMM as the decision input. It won’t solve wording bias on positioning vs consideration, but once TRPs were split the spread tightened to about 3 pts and became a stable “source of truth” for planning.