Measurement, clear enough to scale spend.
We build measurement frameworks that tell you whether the spend grew the business — through incrementality testing, media mix modeling, and the integrated data layer that makes both readable in the same place.
Platform attribution tells you who got credit, not whether the spend caused the sale.
Platforms report on sales they got credit for — which is structurally different from whether the spend caused the sale. The gap between platform-attributed performance and incremental contribution is large, structural, and growing.
Real measurement requires designed-in structures: geo holdouts, conversion lift studies, post-purchase survey attribution, MMM. We build that layer — and surface it in dashboards your team can use day to day, clear enough to defend in a boardroom.
Three principles that make measurement clear.
Plan the measurement when you plan the spend.
Bolting measurement on afterward almost always means measuring the wrong thing. We design holdouts, MMM windows, and survey instruments at the same time as the campaign plan.
Use multiple measurement signals, not single-source.
Platform attribution, post-purchase signals, MMM, and incrementality tests together. Each catches what the others miss. Triangulation, not single-source dependence.
Clear enough to defend in a finance review.
Measurement a CMO can scale spend on — and that survives finance, the board, and the inevitable pressure test against what the spend actually moved.
Our approach
- 01Custom measurement frameworks aligned to business model and sales cycle
- 02Incrementality testing — geo holdouts, conversion lift, post-purchase survey attribution
- 03Media mix modeling for long-range planning where causal experiments aren't practical
- 04Multi-source data integration: platform data, first-party data, post-purchase signals, offline conversions
- 05Automated dashboards connecting media spend to business outcomes, not just platform metrics
Outcomes
- A measurement layer that tells you whether the spend grew the business
- Defensible ROI tied to incremental contribution, not platform-attributed credit
- Confidence to scale spend on numbers clear enough to defend in a boardroom
The questions buyers usually ask.
- What's wrong with platform attribution?
- Platforms report on sales they got credit for — which is a different question from whether the spend caused the sale. The gap between platform-attributed performance and incremental contribution is large, structural, and growing. Reporting platform numbers as truth is repetition, not measurement.
- What's the difference between attribution and measurement?
- Attribution reports which channels got credit for a sale. Measurement tells you whether the spend caused the sale. Platform attribution is an unreliable proxy for causation, and the gap is large, structural, and growing. Real measurement requires designed-in structures: holdouts, geo tests, post-purchase surveys, MMM.
- How do you handle multi-touch attribution?
- As one input among several, not as authoritative measurement. MTA models share most of the assumptions that make platform attribution unreliable. We use them alongside holdouts and MMM, not in place of them.
- What is media mix modeling and when do you use it?
- MMM estimates the contribution of each channel using long time-series data and statistical modeling. We use it for long-range planning decisions and where causal experiments aren't practical — paired with incrementality testing on shorter horizons.
- How do dashboards fit in?
- Dashboards translate the measurement work into something a marketing team can use day to day. They connect media metrics to business outcomes — not just platform metrics to other platform metrics. The dashboard is the surface; the measurement infrastructure underneath is the substance.
Talk through your measurement.
Start with a short strategy conversation. We'll assess fit and outline what a measurement layer clear enough to scale spend on would look like for your business.