Intuit Mailchimp launched Analytics AI, a conversational agent that explains what changed and what to do next across campaigns and revenue. The dashboard is being replaced by the question, but the answer is only as good as your data.
The promise is not more data. It is less time spent assembling it and more spent acting on it.
Intuit Mailchimp has launched Analytics AI, a conversational analytics agent built into the platform that connects campaign performance, audience behaviour and revenue, then tells the marketer what changed, why and what to do next. Instead of building dashboards or exporting reports, a marketer asks a question in plain language and gets an answer with a recommendation attached.
The agent reads each customer's own connected ecommerce data from Shopify, WooCommerce and Wix alongside their Mailchimp history, looks for patterns and surfaces next steps that tie marketing activity back to revenue. Mailchimp also rolled out apps inside ChatGPT and Claude, so a marketer can draft and refine omnichannel campaigns conversationally and then launch them in Mailchimp in one action.
This is part of a clear shift across martech. The dashboard is being replaced by the question. Tools are racing to put a conversational layer over the numbers so that insight does not depend on someone knowing how to build a report.
Why it matters
For small and mid-sized Australian businesses, the bottleneck has never been data. It has been the time and skill to interpret it. A founder running their own email and ecommerce rarely has an analyst on hand. A tool that explains what moved and suggests a next step lowers that barrier.
The catch is the same one that follows every AI analytics tool. A confident answer is not always a correct one, and a recommendation built on messy data will be wrong with conviction. The tool is only as good as the tracking feeding it.
AI adoption in marketing has stalled at around 6%, even as conversational tools like this multiply (Supermetrics 2026).
What to do about it
Get your data clean first. Conversational analytics on top of broken tracking just gives you faster wrong answers.
Use it to ask better questions, not to skip thinking. The value is in interrogating the why, not accepting the first answer.
Check the recommendations against your own judgement. Treat the agent as a sharp junior analyst, not an oracle.
Connect your real revenue data. The tool is far more useful when it can tie a campaign to a sale rather than an open rate.
Conversational analytics will become table stakes across martech this year, but the businesses that benefit are the ones whose numbers are worth talking to in the first place.