Is this a customer-facing chatbot?

Not by default. It is an internal answer layer for approved business questions. A public assistant would require a separate product, content, privacy, and support scope.

What keeps it from being confidently wrong?

It reads approved reporting views, is tested against known answers, carries source and freshness context where possible, and is required to say when the available data cannot support the question.

Do we need a dashboard first?

Not necessarily a visual dashboard, but the metrics and reporting layer must be defined first. An AI interface cannot repair an event that was never captured or choose a business definition nobody approved.

Report and maintain

AI-ready marketing reporting

Let approved AI tools answer recurring marketing questions from defined data instead of loose exports and guesswork.

Start the tracking audit

Start with the tracking audit

Why buyers call

The team can ask an AI tool anything, but it is reading loose exports, mixing definitions, and sounding certain when a source is missing.

What gets done

Inside the scope

We give an approved AI tool a restricted set of reporting data and a defined set of questions it is allowed to answer. Each metric has a source, calculation, permission, and freshness status before the interface is added. The build includes known-answer tests and clear missing-data behavior, so a fluent response is never treated as proof by itself.

01
Choose the questions the interface is allowed to answer and the users allowed to ask them
02
Connect approved reporting views instead of giving the tool unrestricted access to conflicting exports
03
Return the data source and freshness where the interface supports it
04
Test known answers, missing data, permission boundaries, and ambiguous questions

How it is proved

Verification standard

The answer layer is tested against questions with known results, stale or missing sources, unauthorized requests, and definitions that could be confused. It must decline when the data cannot support an answer.

What you receive

The handoff

Approved marketing question set
Restricted reporting interface or data context
Known-answer and missing-data test results
Permissions, limitations, and handoff notes

Result

Plain-language answers to recurring reporting questions, with the source and limits clear enough for a person to check.

Questions that come up

Is this a customer-facing chatbot?
Not by default. It is an internal answer layer for approved business questions. A public assistant would require a separate product, content, privacy, and support scope.
What keeps it from being confidently wrong?
It reads approved reporting views, is tested against known answers, carries source and freshness context where possible, and is required to say when the available data cannot support the question.
Do we need a dashboard first?
Not necessarily a visual dashboard, but the metrics and reporting layer must be defined first. An AI interface cannot repair an event that was never captured or choose a business definition nobody approved.

Start the tracking audit

The first paid step checks the journey and defines the smallest useful build.

Send the domain, the customer journey, and the platforms that should receive it. The tracking audit shows what is working, what is missing or duplicated, and the exact build recommended next.

Start the tracking audit

Paid, fixed scope · Within ten business days after complete access