The Signal

MiQ is scaling its AI platform, Sigma, by integrating cross-channel behavioral data—specifically TV, streaming, and browsing—to combat signal fragmentation. For operators, this marks a transition where programmatic buying is no longer just about inventory access, but about proprietary, predictive intelligence across the entire consumer journey.

What Happened

MiQ updated its Sigma platform with three new core modules: Watching Intelligence (cross-platform video behavior), Browsing Intelligence (consideration-stage behavior), and Total Measurement (unified ROI tracking). The infrastructure now processes 2.5 petabytes of data across 600+ feeds, bolstered by new partnerships with Circana, TitanOS, and Evertune. Since June 2025, the platform has supported 40,000 campaigns for 2,300 advertisers.

Why It Matters

First-order: Advertisers gain a cohesive view of their spend across fragmented environments like linear TV, YouTube, and commerce platforms. This reduces the “walled garden” problem where performance data often sits in silos.

Second-order: The $2.22 ROAS reported by MiQ suggests that AI-driven signal processing is becoming the primary lever for performance improvement as third-party cookies depreciate. Agencies and ad-tech vendors relying on basic tracking will find it increasingly difficult to compete against players with deep, multi-source data infrastructure.

Third-order: The focus on the Indian market suggests a broader strategy to win in high-complexity, multi-language, and multi-device digital landscapes, potentially setting the stage for similar expansion into other fragmented high-growth markets.

The Numbers

  • $2.22 ROAS for every $1 spent on Sigma campaigns (Source: MiQ)
  • 2.5 petabytes of data infrastructure (Source: MiQ)
  • 40,000+ campaigns powered since June 2025 (Source: MiQ)
  • 16 media environments currently supported (Source: MiQ)

What To Watch

  • Data Provider Consolidation: Expect MiQ to acquire or enter deeper exclusive partnerships with retail media networks to expand their ‘Browsing Intelligence’ capabilities.
  • Market Adoption: Monitor if their ‘Total Measurement’ suite succeeds in displacing incumbents like The Trade Desk or internal Google-provided attribution tools in the Indian enterprise segment.
  • AI Architecture: The integration with Databricks suggests MiQ is positioning itself as a data-agnostic layer rather than just an execution platform. Look for further “bring your own data” (BYOD) capabilities.