An F100 consumer health company's media and insights analytics teams were spending significant time on manual MMM synthesis, with no consistent or scalable way to extract actionable insights across 20+ brands. Manual analysis introduced inconsistency across brand and media evaluations, reducing reliability.
Cloverpop deployed a three-agent pipeline (Structuring, Analyst, Insights) that ingested MMM, MTA, and R&F inputs and generated data-backed recommendations. LLM-powered insight generation used vector search, embedding-based analysis, and historical meta-knowledge for high-quality recommendations. Automated refresh pipelines integrated with Domo dashboards for always-current reporting.
Results
3-5% increase in media ROI
~40-50%reduction in analyst effort per cycle
Analyst capacity was freed from manual synthesis, with granular, traceable insights delivered at brand, channel, publisher, and campaign levels. Role-specific reports reached brand, media, and exec teams automatically, Domo BI integration gave stakeholders always-current access, and traceable recommendation logic minimized human bias across brand and media evaluations. Replacing manual MMM synthesis with an AI-driven agentic pipeline delivered more granular, consistent, and traceable media insights across all brands.