Four stages. Pick where you stand.
Each stage holds a small set of engagements. Open any one for what it does and what you leave with.
A two-phase engagement. First, a landscape evaluation: we review your stack, interview your key stakeholders, and map what you have against what your decisions actually require. Then a facilitated Clarity Workshop with your CMO, growth lead, and a finance stakeholder — where you agree the standard: what decisions the business needs measurement to support, and what evidence those decisions demand.
You leave with: a landscape evaluation and a two-page alignment summary — and a shared, senior definition of what good looks like. The gap between that standard and where you are today becomes the mandate for what comes next.
A forward-looking blueprint that starts from the decisions you need to make, not from tools. It maps the capabilities those decisions require, the gap between that and where you are, and a sequenced plan to close it — including the build-or-buy call for each capability, and an architecture you can defend to Finance.
You leave with: a measurement architecture, a maturity-sequenced roadmap over a twelve-month horizon, and an investment case anchored to your business decisions — plus a readout to align your team behind it.
For brands that already have a marketing mix model and struggle to convert it into investment decisions. We start by aligning on the actual decision — with Finance in the room — then pressure-test the evidence, map the scenarios, and translate the model into a confidence-scored business recommendation.
You leave with: a clear recommendation, the tradeoff space behind it, and an honest confidence level for each path — not another interpretation of the model, but a decision you can act on.
You leave with: a strategic read for the CMO and a tactical appendix for the performance team — two tiers, one analysis.
Reconcile every signal you have — models, studies, platform numbers — into a single, calibrated view of performance per channel, in a way that’s repeatable and defensible. The Program gives you the framework to do it by hand: assess each signal, decide which to trust per channel, and calibrate your live reporting to it — plus a reconciled starting state, run once on your own data, so you leave with a working baseline, not just a method. You’ll never be handed a number the evidence can’t back: where a channel isn’t measured well enough to call, the framework says so — and tells you what would fix it.
You leave with: the methodology, the working templates, and a reconciled starting state — everything your team needs to keep reconciling every signal into one calibrated read per channel. Triangulation, operationalized.
The Measurement Decision Program, built into software and configured to your specific signals, channels, and benchmarks. Plenty of tools will reconcile your signals into a view; almost none give you a repeatable, defensible way to do it — deciding which signal to trust for each channel, this period, and why. This does. It’s vendor-agnostic — it works with the measurement you already have, whatever tools produced it, with no migration and no lock-in. Your team uploads the measurement; the engine reconciles it into a confidence-weighted read per channel, refreshed whenever you upload — and where no signal can measure a channel at the level you decide at, it tells you, instead of inventing a number. Fully deterministic — the same inputs always produce the same answer, so the number is auditable, repeatable, and defensible. Nothing calls an external service, so you can refresh it as often as you like at no added cost.
You leave with: a working decision system your team runs to reconcile every measurement output into a single, continuously calibrated view of performance per channel — triangulation, operationalized and automated.