AI for Data

Every marketing question should have an answer in minutes — not on Monday.

You don't have an analyst. Most weeks you don't even have a clean dashboard. My promise: you and I sit down together and define the data playbook — the mental model, the attribution, the AI interface — until your small team stops waiting on answers.

Who this is for

Marketing teams of five or fewer.

Teams with no dedicated analyst. Teams where the head of marketing is also the person staring at Looker at 11pm. You don't need another tool — you need someone to challenge what you're measuring, rebuild the mental model, and leave behind a data layer your team actually trusts.

The missed opportunity

Your team is asking the right questions. The answers are arriving three weeks too late.

Every small marketing team in 2026 has the same problem: the data exists, the tooling exists, the models exist — but nothing talks. So the head of marketing still asks, the answer still takes until Friday, and by then the decision was already made on gut. AI-native teams closed that loop years ago. Everyone else is paying the tax every week.

The question arrives Monday. The answer lands Friday. — The decision was already made Tuesday. Your small team is waiting on data instead of being served by it.

There is no analyst on the team — So the head of marketing does it — badly, at midnight — or it doesn't get done. Either way, you're losing.

Attribution leaks; nobody trusts the number; everybody quotes it anyway — Every decision carries an asterisk no one says out loud. That's not data-driven marketing. That's theatre with numbers.

Beautiful, wrong dashboards — The team has learned to work around them instead of fixing them. Institutional blindness disguised as process.

"A small team without trustworthy data doesn't make decisions — it performs them."

What we work on together

From 'ask the analyst' to a data layer any teammate can interrogate.

Here's my promise: you and I sit down together, challenge what's being measured and why, and define the data playbook your team runs on afterwards — the attribution model, the AI interface, the governance. I don't hand you a dashboard and leave. We build the thinking together, and it stays with you. For the operational rebuild — pipelines, warehouse engineering, infrastructure — Intellix takes over.

01

Data infrastructure mental model

We map where the data should live (BigQuery, Snowflake or similar), what the single source of truth looks like, and what the team needs to stop arguing about.

02

Text-to-SQL and text-to-insight thinking

I teach the team to use AI agents as the interface to the warehouse. Governed, explainable, trusted — not magic.

03

Automated anomaly detection

A weekly insight pack the stack generates on its own. Surprises find your team — not the other way round.

04

Forecasting in plain language

'What happens to CAC if paid drops 30%?' — a question your team learns to answer in seconds, not spreadsheets.

05

Attribution you can defend

A model your CFO nods at, the team uses, and that survives platform updates.

06

Marketing data literacy

Every teammate ends the engagement able to read the data — not just nod at the deck.

The data playbook you and I define together.

Need hands-on execution?

Candoro is the sparring partner. Intellix is the delivery studio.

Candoro is coaching, consulting and knowledge transfer — I sharpen the thinking and leave your team with the mental model. When the work actually needs hands — pipelines, warehouse builds, dashboard engineering — my partner studio Intellix handles the operational side.

Let's define your data playbook together.

The small teams that win the next cycle aren't the ones with more data — they're the ones who sat down and defined how they'd use it. Let's be the people who did that in time.