Marketing measurement for DTC brands

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I help growth teams get closer to the truth behind their marketing spend—then build the systems that keep the learning going.

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70+: incrementality tests
$123M: personally launched and run in digital campaigns
10+ yrs: in DTC marketing analytics

The problem with certainty

The first question isn't which channel worked. It's what decision you're trying to make.

Should you spend up, spend down, pause a channel, or change strategy? Facebook says it drove 500 sales. Google says 400. You only had 600 total orders. The reports disagree because they are all looking at the same messy reality from different angles.

The answer isn't to pick a winner. It's to put the evidence in conversation.

The Measurement Council

Triangulation, not model wars.

No single source of truth. A disciplined cross-examination of every credible read.

Models

Portfolio-level perspective

MMMs put spend, seasonality, promotions, and demand into one view. They can hear portfolio signals that click data cannot.

Experiments

Causal calibration

Geo holdouts, matched markets, and synthetic controls test what changes when spend changes. They keep the models honest.

Behavioral data

The journey, in detail

MTA and first-party identity data reveal observable paths to purchase and surface the questions worth testing. They do not see every impression or influence.

A familiar way to think about it

Marketing measurement works like a weather forecast.

Weather models disagree all the time. They can be directionally right and still miss the specifics—especially further into the future. We still check them obsessively, because more independent models and more agreement give us more confidence.

Marketing gives us one advantage: we can run tests to break ties. Experiments establish truth baselines, calibrate the models, and give a team the confidence to make the next decision.

When the reads agree, you can act with confidence. When they disagree, that's where the learning starts.

Capabilities

From the API connection to the budget recommendation.

The whole measurement stack.

Incrementality testing

Find out whether a channel created sales—or simply claimed them.

Marketing mix modeling

Understand contribution, saturation, and the strongest allocation of your next dollar.

Attribution systems

Reconcile platform revenue with order-level reality and the customer journey.

Data & AI foundations

Build the warehouse, pipelines, shared context, and repeatable analysis tools that make answers trustworthy.

Which model is right?

Each one sees a different part of the weather.

That doesn't make one of them wrong. It tells you what it can—and cannot—tell you.

MMM

Broad, strategic, and inferential.

A marketing mix model sees the full portfolio over time: spend, seasonality, promotions, and demand. It is built for allocation decisions, not for reconstructing one customer journey or declaring a final truth.

Experiments

Causal, precise, and bounded.

Holdouts and controls answer the question no observational model can settle alone: what changed because we changed spend? They establish a baseline that can calibrate everything else.

MTA

Fast, granular, and incomplete.

Attribution is useful for reading observable customer behavior—especially near the bottom of the funnel. Its usefulness depends on durable first-party identity signals, and it still cannot see every impression or influence.

When the signals disagree, run a test. Marketing has one advantage over weather forecasting: we can create control groups, break ties, and use the result to calibrate the models and the clicks we're observing.

Why Brinker Analytics

I build things that stay.

Most measurement consultants interpret the data. Most data engineers build the pipelines. I do both: tests, models, warehouse, reporting, and AI-ready shared context.

When the engagement ends, your team keeps the systems, the methodology, and the ability to answer the next question without starting over.

Who I am

Eric Brinker

I'm a director-level DTC marketing analytics leader with more than a decade spent helping growth teams learn faster and spend with more confidence.

I've personally launched and run $123M in digital campaigns, led 70+ incrementality tests, and built the measurement and data systems behind high-growth brands.

Based in Nashville, I take on focused fractional engagements with one or two brands at a time.

Let's find the next useful question

Less fog. Better decisions.

Available for focused fractional engagements with one or two DTC brands at a time.

eric@brinkeranalytics.com LinkedIn ↗

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