A landmark deal is reshaping the future of measurement.
Circana completed its acquisition of Nielsen’s Marketing Mix Modeling (MMM) business in August 2025. This, along with their purchase of NCSolutions in June, creates the most complete measurement platform in the industry, covering everything from planning to post-campaign analysis.
This isn’t just consolidation. It’s a move built for the cookieless future. MMMs are back in demand as brands chase unified measurement across fragmented media. Google’s Meridian launch, combined with the fact that 60% of US advertisers already use MMMs, proves the timing is perfect.
This acquisition will reveal how brands plan, execute, and measure their campaigns, the resurgence of MMMs, and what competitors might do.
The Strategic Rationale Behind The Deal
Circana CEO Stuart Aitken explicitly stated their goal to create “the industry’s leading media measurement business.” The MMM acquisition, following NCSolutions, gives them control over the entire measurement value chain, from audience targeting through post-campaign analysis.
Cookieless Future Positioning
As third-party cookies disappear and attribution becomes more complex, MMMs offer statistical modeling that doesn’t rely on individual user tracking. Brands need measurement solutions that work across all channels, especially as media becomes more fragmented.
Client Demand Acceleration
The revival of MMMs isn’t theoretical. Alaska Airlines identified $100 million in addressable advertising revenue using Google’s MMM platform. When major brands are seeing eight-figure returns from better measurement, demand for sophisticated modeling becomes inevitable.
Technology Integration Advantages
Circana combines its retail data, insights into consumer behavior, and NCS’s measurement tools to create more accurate models. Unlike standalone MMM providers, this approach allows for better statistical modeling and more actionable results.
What Changes For Media Planning
Previously, brands used separate tools for audience research, media planning, and measurement forecasting. Circana’s integrated platform means planners can model campaign performance before launch using the same statistical frameworks that will measure actual results.
Real-Time Optimization Capabilities
The NCS integration lets media teams adjust campaigns in real-time using insights from Marketing Mix Modeling (MMM). Instead of waiting for post-campaign reports, teams can shift their spending based on which channels perform well or poorly.
Cross-Channel Attribution Clarity
MMMs excel at measuring channels that resist traditional attribution, such as TV, radio, out-of-home, and brand marketing. Circana’s platform can now attribute sales lift across all touchpoints using a consistent statistical methodology, rather than relying on last-click digital attribution.
Budget Allocation Intelligence
Advanced statistical modeling helps planners understand diminishing returns curves for each channel, optimal frequency caps, and seasonal adjustment factors before campaigns launch. It improves ROI predictions and budget efficiency.
Campaign Optimization Revolution
Traditional digital attribution focuses on clicks and conversions, missing upper-funnel effects and cross-device behavior. MMMs use statistical correlation to assess total incremental impact, including brand lift, consideration changes, and long-term customer value.
Channel Interaction Effects
The most sophisticated aspect of MMMs is measuring how channels work together. TV might drive search behavior, social media might amplify radio campaigns, or OOH might increase digital conversion rates.
These interaction effects are invisible to channel-specific measurement but crucial for optimization.
Automated Spend Reallocation
When combined with programmatic buying systems, insights from marketing mix models can automatically shift budgets from underperforming channels to those that are performing well. It happens during active campaigns and helps maximize efficiency in real-time.
Incrementality vs. Correlation
MMMs distinguish between correlation and causation using control groups, holdout markets, and statistical controls. It prevents common optimization mistakes, such as increasing spend on channels that capture existing demand instead of creating new demand.
Post-Campaign Analysis Transformation
Traditional campaign analysis focuses on cost-per-acquisition (CPA) and return on ad spend (ROAS). MMMs measure total incremental revenue, brand lift, customer lifetime value changes, and competitive conquest effects, providing a comprehensive picture of ROI.
Long-term Impact tracking
Statistical models can measure carryover effects, which show how campaigns continue to drive results weeks or months after they end. This is crucial for understanding true campaign value and planning subsequent efforts.
Cross-Campaign Learning
MMM databases help analyze multiple campaigns. They identify which creative ideas, media mixes, or timing strategies work best in different market conditions.
Predictive Capabilities
Historical MMM data trains predictive models for future campaign planning. Brands can forecast performance scenarios before committing budgets, reducing risk and improving strategic decision-making.
Industry Competitive Response
Circana’s move won’t go unanswered. From Google to agencies, the measurement industry is already gearing up its competitive responses.
Google’s Meridian momentum
Google launched its free MMM platform to defend against Apple’s attribution restrictions and privacy changes. Circana’s comprehensive offering directly competes with this strategy by providing more sophisticated modeling integrated with retail data.
Measurement Consolidation Wave
Expect more measurement companies to make similar acquisitions. The measurement industry is coming together into platforms that can manage planning, optimization, and analysis in a unified way.
Agency Holding Company Reactions
WPP’s “Open Intelligence” and similar agency initiatives attempt to build proprietary measurement capabilities. Independent platforms like Circana’s threaten agency control over measurement, potentially forcing more acquisitions or partnerships.
Technology Platform Integration
Demand for measurement APIs that integrate with planning and buying systems will accelerate. Standalone measurement tools that don’t integrate into workflow platforms will struggle to compete.
What Brands Should Do Now?
Inventory existing measurement tools, identify gaps between planning and analysis, and evaluate whether current solutions can handle cookieless attribution and cross-channel optimization.
MMM Readiness Assessment
MMMs require clean data feeds, standardized campaign tagging, and consistent KPI definitions across channels. Brands should audit data infrastructure before implementing statistical modeling platforms.
Vendor Evaluation Criteria
When choosing measurement partners, focus on platforms that combine planning, optimization, and analysis. Avoid using separate tools that create workflow issues and keep data trapped in silos.
Team Capability Development
MMMs require statistical literacy and cross-channel thinking. Marketing teams need training on interpreting statistical models, understanding confidence intervals, and translating mathematical insights into media strategies.
Testing and learning protocols
Use structured testing methods like control groups and holdout markets to confirm MMM insights. It will help build trust in our measurements and ensure we use effective statistical approaches.
Conclusion
Circana’s acquisition of Nielsen MMM signals the measurement industry’s evolution from fragmented point solutions to comprehensive platforms that span planning through analysis. As cookieless attribution and cross-channel complexity increase, statistical modeling becomes essential, not optional.
Brands that adapt their measurement strategies by auditing their data infrastructure and implementing unified platforms will gain a competitive advantage in campaign effectiveness and ROI.
The measurement landscape is evolving rapidly, and early adopters of integrated workflows for planning, optimization, and analysis will gain a significant advantage. In contrast, competitors may struggle with disconnected measurement tools and unclear attribution.
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