AI for marketing data analysis: the #1 use (90%) and how to do it right
Nine in ten marketers use AI to analyze data and generate insights, according to IAB Brasil and Nielsen. It’s the most common use, ahead of content creation (73%). In our reading, using it isn’t enough: analysis is only worth it when it ends in a decision with an owner and a deadline.
What the study shows
The second edition of the IAB Brasil and Nielsen survey on AI in digital advertising came out in September 2026. According to the Consumidor Moderno article, 90% of professionals use AI for data analysis and insight generation, 73% for content creation and 34% to develop marketing systems. Among the benefits, 80% cite efficiency and 56% decision support.
The article doesn’t state the sample. We treat the numbers as a direction signal.
Speed isn’t the same as decision
When efficiency (80%) comes ahead of decision support (56%), the message is clear: AI is shortening the path to the report. The ready report, on its own, doesn’t move any channel’s budget.
Gartner heard 402 CMOs in 2025. The marketing budget sat at 7.7% of revenue, and 59% said it isn’t enough. In that scenario, every analysis has to answer an allocation question: where to put the next real and where to pull the last one.
How to do it right
We believe mature use of AI in marketing data follows four simple rules.
Start from the question. “Which channels bring the customer who stays?” yields more than “show me insights from the base.”
Secure the data before the model. AI reads what exists. If CRM, media and sales don’t talk, it produces a pretty answer over half a truth. Salesforce, in State of Sales 2026, shows that reps spend 60% of their time off selling, in part searching for and checking information. The same friction appears when marketing tries to close a number.
Ask for the source of the figure. Every AI conclusion has to come with the table it came from. Without that, no one on the team can challenge it.
Close with a recorded decision. Who decides, what changes and when it’s measured again.
What stays human
Interpreting business context, choosing what to optimize and taking on the risk of the choice. AI reads patterns fast. It isn’t accountable for the quarter’s revenue.
To take to the team
- Which budget decision last quarter came from an AI-made analysis?
- Where do marketing data and sales data still not meet?
- Who checks the figure before the number reaches leadership?
If your dashboard doesn’t answer these questions yet, see what changes in the CMO’s role. To structure the analysis from scratch, get to know NorthStar’s marketing intelligence.
Frequently asked
What is the main use of AI in Brazilian marketing?
Data analysis and insight generation, at 90%, according to IAB Brasil and Nielsen (2nd edition, Sep/2026).
Does AI replace the marketing data analyst?
The studies we consulted don’t measure that. In our reading, it speeds up analysis and raises the bar on whoever interprets, because someone has to check the figure.
Where to start using AI in marketing data?
With a business question and the bases that already exist: CRM, paid media and sales. Without integrating that data, AI’s answer stays incomplete.
How do you know if the analysis produced a result?
By the record of the decision it motivated and by later measuring the effect. Analysis without a recorded decision is just a report.
Sources
- Consumidor Moderno, on the 2nd edition of the IAB Brasil and Nielsen study, Sep/2026. consumidormoderno.com.br
- Gartner. 2025 CMO Spend Survey, 12/05/2025. gartner.com
- Salesforce. State of Sales 2026 (7th ed.). salesforce.com
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