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“Why did ROAS drop?” used to be a three-day project. R-AI is the AI analyst inside Roivenue. It answers plain-language questions about your attributed data, explains what changed and suggests what to check next. Then it builds the dashboard to track it, from one sentence. What’s the first question you’d ask your data if it answered back?

Your AI assistant can help write a strategy, summarize a 90-page report and explain quantum physics. But ask it what's happening in your Roivenue data? Until now, that's been a bit of a situationship. Roivenue 3 MCP lets you query your Roivenue data directly from assistants like ChatGPT, Claude and Microsoft Copilot. Less exporting. Less tab-switching. More actual work. Your spreadsheets can take a little break.

Dashboards tell you what happened. Working out why, and what to do next, was always your job. Roivenue 3 takes on part of it, in four moves: 1/ R-AI explains why a number moved 2/ MCP brings that answer into your AI assistant 3/ Budget Optimizer shows where the next euro goes 4/ Cohorts shows which customers were worth acquiring The model underneath is the same white-box one you can audit. Which one would you open first?

Roivenue 3 patch notes. Shorter than your last attribution meeting. Same auditable attribution model underneath. A completely different way of using it on top: ask instead of dig, plan instead of just report. Which line would you try first?

"Find out why ROAS dropped. Build me a dashboard to track it." In Roivenue 3, an AI agent handles both, working on attribution that counts impressions and cross-device journeys. See it live on 4 November. Join us.

In this live session, we introduce Roivenue 3, the new release of Roivenue Multi-Touch Attribution (Roivenue MTA). You'll see what happens when your AI assistant works on attribution that already counts walled-garden impressions and cross-device journeys.