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Client Success · Advertising, Publisher

Breaking Data Silos: How Publishers and SSPs Accelerate Analytics Using a Conversational Assistant

MediaMint deployed an AI-powered conversational analytics assistant via the Mia platform, turning manual SQL queries and dashboard hunting into instant, natural-language answers.
Impact at a glance
80%
Daily monitoring time saved
60 min → 10 min/day
50%
Faster ad-hoc turnaround
Queue → instant
~0s
Revenue alert latency
Days → near-instant
The challenge
1
Data density & bandwidth
The team manually parsed thousands of data points across integrations, geographies, and device types. Revenue anomalies were often discovered days after they began.
2
The query bottleneck
Analysts spent the majority of their day writing SQL and pulling routine reports, which left only a fraction of their time for actual decision-making.
3
Non-linear scaling
Root-cause analysis was senior-analyst-dependent and slow. As inventory and partner counts grew, manual overhead consistently outpaced headcount capacity.
What's inside the full case study
The exact before-vs-after breakdown for each of the 3 operational friction points
How the assistant translates natural-language queries into live warehouse queries — no SQL required
Full walkthrough of all 6 unified analytics capabilities built into the Mia platform
Architecture for automated anomaly alerts across revenue, CPM, and fill rates
How RCA was standardized and scaled without linear headcount growth
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Core capabilities — preview
Conversational NLP analytics
Ask performance questions in plain English and get direct, contextual answers instantly. No dashboard hunting.
Automated SQL generation
User intent translated into warehouse queries instantly, with no manual coding or analyst involvement.
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Access the remaining capabilities and full implementation details.
Unlock in full PDF
Unlock in full PDF
Access the remaining capabilities and full implementation details.
Unlock in full PDF