Marketing Measurement & Attribution Consulting
Numbers you can steer the business by, not just report on.
Start a projectMost mid-market brands aren’t short on data — they’re short on data they trust. The ad platforms each claim credit for the same sale. GA4 says one thing, the CRM says another, and last-click quietly tells you to cut the top of the funnel that feeds everything below it. When the numbers can’t be trusted, budget decisions get made on instinct and the loudest meeting voice. That’s expensive, and it compounds.
Measurement is the part of consulting and steering that makes the rest of it real. We build a measurement system you can actually run the business on: a defined metric tree with owners and source-of-truth definitions, an attribution approach matched to how you genuinely buy, a tracking layer that survives iOS and cookie loss, and incrementality testing that separates ads that drive demand from ads that just take the credit. We are direct about what each model hides — the goal is good decisions, not flattering charts.
Then we operate it. Tags break, platforms change their rules, and metric definitions drift the moment two teams start using them differently — measurement systems rot fast when no one owns them. We stay on a standing cadence: QA the tracking, re-test the attribution assumptions, and keep the metric tree honest as the business changes. That build-and-run model is the difference between a clean report this quarter and numbers you can still steer by next year.
Built and run, end to end.
Measurement model and metric tree
We map your funnel to a defined metric tree: one north-star outcome, the input metrics that move it, and the guardrails that catch trouble early. Every metric gets an owner, a definition, and a source. No more two dashboards that disagree on what a 'lead' is.
Attribution that matches how you actually buy
Last-click flatters the bottom of the funnel and starves the top. We choose an attribution approach that fits your sales cycle and budget reality — position-based, data-driven, time-decay, or media mix where the data supports it. We tell you what each model hides, not just what it shows.
Tracking and data layer rebuild
GA4, server-side tagging via GTM, consent mode, and a clean event taxonomy that survives iOS and cookie loss. We rebuild the data layer so conversions fire once, fire correctly, and reconcile against your CRM and ad platforms — not three different truths.
Incrementality and holdout testing
Platform-reported ROAS counts conversions that would have happened anyway. We design geo holdouts and conversion-lift tests to separate ads that drive demand from ads that take credit for it. The output is a spend decision, not a vanity number.
Reporting that drives decisions
One executive view tied to revenue, plus working dashboards each channel owner actually uses. Definitions documented, refresh automated, anomalies flagged. Built so a Monday standup ends in a decision, not a debate about whose number is right.
We run it after we build it
Measurement decays — platforms change, tags break, definitions drift. We operate the system on a standing cadence: QA the tracking, recheck attribution assumptions against fresh holdouts, and keep the metric tree honest as the business changes. Build-and-run, not build-and-leave.
Questions, answered.
How is this different from just setting up GA4 and a dashboard?
Setup is the easy part. The hard part is deciding which metrics deserve a budget conversation, choosing an attribution model that won't lie to you, and proving with holdouts that your spend is actually causing growth. We do the implementation, but the value is the measurement framework and the senior judgment behind it. A clean dashboard on a broken model just makes wrong numbers easier to read.
We're worried our current numbers are wrong. Where do you start?
With an audit. We trace every important conversion from the moment it fires to where it lands in your reporting and your CRM, and we reconcile the three against each other. Most engagements surface duplicate tracking, conversions counted in multiple platforms, or a 'lead' that means something different in every tool. You get a written list of what's broken, what it's costing you in misallocated spend, and the order to fix it in — before we touch anything.
Can you actually prove our ad spend is working?
As well as the data allows, and we're honest about the limits. Platform-reported ROAS is self-graded and almost always overstated. The reliable test is incrementality — geo holdouts or conversion-lift studies that compare exposed and unexposed audiences. Where your volume supports it, we run those tests and give you a defensible read on what each channel truly contributes. Where it doesn't, we tell you that too rather than dress up a guess.
Do we have to switch analytics or attribution tools?
Usually not. We work with GA4, GTM server-side, your ad platforms, and your existing BI or CRM stack. We bring opinions on tooling but we don't sell software, so the recommendation is driven by your data and budget, not a referral fee. If a tool is genuinely the wrong fit we'll say so, but most problems are model and implementation problems, not tool problems.
Does AI replace the analysts in this?
No. We use AI to do the tedious, high-frequency work — flagging tracking anomalies, monitoring for tag breakage, and drafting the routine reporting — so our analysts spend their time on the judgment calls: which model to trust, what an unexpected lift means, what to do about it. The interpretation and the accountability stay with people. AI brings the cadence; the people bring the call.
What does an engagement look like and how long until we trust the numbers?
Most start with a 2-to-4 week audit and measurement-model build, then a tracking rebuild that takes a few weeks more depending on stack complexity. Trustworthy day-to-day reporting typically lands inside the first quarter; clean incrementality reads take longer because they need enough test data to be conclusive. After build, we move to a standing operating cadence — the part most consultancies skip, and the reason measurement systems usually rot within a year.