Stop explaining where the differences come from.
Just show the result.
Data from every source: consistent, validated, ready for analysis. No manual formulas, no custom scripts, no reconciliation before every management report.
Board meeting.
The manager asks about results.
You spend 10 minutes explaining why Google and Meta don’t match.
That isn’t analysis. It is live reconciliation, in front of people who want decisions, not a lecture on attribution. This moment comes back at every meeting, because each source counts conversions differently and nobody but you understands it.
You spend most of the day not on analysis but on cleaning data. An export from GA4, an export from Meta, an export from Google Ads, custom formulas in Sheets to stitch them together. Scripts that broke because Meta renamed a column.
DataOrganizer gives you one consistent data model, validated automatically. That moment in the meeting simply disappears.
Stop being the on-demand reports person.
Go back to being an analyst.
The AI assistant takes over ad hoc questions from the manager and the owner. Those “could you quickly check how we did with this one product” messages disappear from your Slack. You do deeper work.
- The manager asks on Slack 6 times a day. Every question = 15 minutes of your time.
- You build reports someone opens once. Insights that need a week of work keep waiting.
- No promotion, because “you’re good at Excel”. Strategy happens elsewhere.
- When you go on holiday, the company doesn’t know how much it sold last week.
- The manager asks the AI directly in plain language. Ad hoc requests disappear from your Slack.
- You work on a validated data model. You don’t start the day with “where does this number come from”.
- Your value lies in insights, hypotheses and optimisations, not in copying numbers.
- The company keeps running when you’re away. You get back to work that helps you grow.
One data model.
No BigQuery of your own, no custom pipelines.
Most teams build this themselves: connectors to GA4, Meta, Google Ads and the shop, their own warehouse, their own transformations, their own validation. Six months, two full-time roles, endless maintenance. DataOrganizer is a ready-made layer.
“Time to first insight drops dramatically. You don’t configure; you analyse.”
Live in one day.
No BigQuery of your own, no building from scratch.
For an analyst this doesn’t mean “no technical knowledge needed”. It means that on the day you would normally only start writing a connector, your data is already connected and you start looking for insights.
Connect sources with a few clicks
OAuth for Google Ads, Meta, GA4 and the shop. No webhooks, no infrastructure. The first data arrives within minutes.
30 minThe data model is ready
Channel mapping, attribution, costs/revenue, margins, fees: the default model handles it automatically. You check, validate and adjust where needed.
2hFirst report
Dashboards are live. The manager gets their link, the owner theirs. On the same day you answer the first business question instead of writing a connector.
Same dayThe manager asks the AI.
You don’t answer Slack every fifteen minutes.
The AI assistant answers 80% of the ad hoc questions that would normally land on your desk. In plain language, in 5 seconds, from the same validated data. You do what AI can’t: hypotheses, experiments, models.
The technical doubts we hear most often
How do I know your data model is any good?
What if I have an unusual source you don’t support?
Can I pull the data into my own BigQuery / dbt / Python?
What about attribution? Every platform counts differently.
Data security: where is it stored?
Won’t AI reduce my value in the company?
Connect your sources in a single day.
Start analysing, stop cleaning data.
One data model. One source of truth. An AI assistant that takes ad‑hoc questions off your plate. 14 days free, no card required.