Everyone has dashboards. Nobody trusts the number.

The data layer, and the reporting that sits on top of it: we build both, so the report leadership reads is one they can act on instead of argue about.

What we do

We build the pipelines, the single source of truth, and the reporting on top of it, so one number means one thing across the business.

Why it's needed

Marketing's figure and finance's figure disagree, the monthly report is assembled by hand, and by the time anyone trusts it the month is over.

What we work with

Warehouse or spreadsheet, GA4 or raw event data, the BI tool you have or the one you should have. We meet the stack where it is.

The problem

A dashboard is not the same as an answer.

Most companies aren't short on charts. They're short on a number they can defend in a room. When the same metric comes out three different ways, the reporting stops being a tool and starts being an argument.

Two teams, two numbers

The same metric comes out different depending on who you ask, and nobody can say which one is right.

The report is handmade

Someone rebuilds it in a spreadsheet every month, and that person has quietly become the pipeline.

Attribution nobody believes

You're spending real money on channels the reporting can't honestly credit one way or the other.

How the engagement works

We make the number mean something.

We trace the decisions back to the metrics, the metrics back to their definitions, and the definitions back to the source data. Then we build.

Trace the number

We follow every reported number back from the decision it's meant to inform to the systems and events it actually comes from.

Define the truth

We pin down what each metric actually means and agree it once, in writing, before anything gets built.

Model, then report

We build one source of truth and the reporting on top of it, so the same metric means the same thing everywhere.

Outcomes: what changes

Where we start depends entirely on where the trust breaks down: sometimes it's the pipeline, sometimes it's the definition of the metric itself, more often it's both. These are the outcomes clients see most.

Sources
Many raw inputs
One metric
Defined and reconciled
Decisions
Clear next actions
The big one

Answers, not just charts

The reporting is built to answer the questions leadership is actually asking, not to fill a screen with metrics.

Reporting that reconciles

The report leadership reads ties back to the systems underneath it, so the numbers hold up when someone checks.

Attribution you can defend

We build a view of what's actually driving revenue that stands up to a hard question about spend.

Pipelines that run themselves

The monthly rebuild goes away. Data moves on its own, so no one person is the reason the report exists.

Metrics defined once

We agree what each metric means and encode it, so revenue means revenue no matter who pulls the report.

Who it's for

Marketing

Prove what spend is doing with attribution finance can review.

Finance & leadership

Make decisions from numbers that reconcile.

Operations

See what is happening now, not in last week's export.

Agencies

Present client reporting you can defend.

Tools we work in
Warehouses
BigQuerySnowflakeRedshiftPostgres
BI & reporting
LookerPower BITableauMetabase
Pipeline & sources
dbtFivetranGA4Ad platforms

Consider this a sample, not a ceiling. If your stack runs on something else, it's still worth a conversation.

Let's talk about the number you don't trust.

Tell us which number you don't trust. We'll find out why, and make it one you can stand behind.

Fix the number