The advent of AI advancements, the accelerating pace of market shifts, evolving consumer behavior, and growing complexity of media channels are pushing enterprises to adapt their marketing strategies faster than ever. It is crucial for enterprises to have timely and granular insights to ensure investments are performing at their full potential. Traditional MMM—once the go-to measurement approach—often struggles to deliver at the speed and depth modern marketers require. Its heavy reliance on historical, aggregated data limits visibility into performance at a detailed channel or campaign level. Long, resource-intensive modeling cycles mean insights arrive in staggered intervals, often too late to inform real-time decisions. This dynamic nature of the market has ignited leaders to look at Market Mix Modeling not as an annual or quarterly analysis, but as a dynamic, always-on solution. And in this dynamic era, adoption is not only an advantage but a necessity.
Impact Always On with Always-On MMM
Rather than relying on fixed, point-in-time analyses that take 3–6 months to materialize, Always-On MMM supports ongoing measurement every month, helping marketers course-correct with ease and remain proactive. Addressing the limitations of traditional MMM—often slow, resource-heavy, and retrospective—Always-On models offer a more dynamic way to quantify marketing impact, enabling brands to stay in sync with ever-evolving market trends and consumer behavior, thereby redefining how enterprises measure and optimize their marketing performance.
By leveraging automated data ingestion and continuous analytics, teams can unlock more frequent, granular insights to make data-driven decisions with confidence. These models are less resource-intensive, scalable, and compatible with experimental data inputs, enhancing both reliability and relevance. With the ability to integrate weekly or bi-weekly data refreshes, Always-On MMM empowers marketers to adapt their strategies in tune with market shifts.
However, adopting an Always-On MMM approach requires a thoughtful, well-orchestrated implementation. It is a constantly evolving system that hinges on real-time data pipelines, robust modeling, and organizational readiness to enable dynamic, evidence-based decision-making.
At MathCo, our core capabilities with MMM, along with projects and initiatives with marketing functions of leading CPG brands, have helped us shape a suite of best practices that have delivered remarkable impact and ensured consistency, scalability, and accuracy. Some of them include:
- Tailored Approach: Each market, category, and brand operate within a unique context—with varying data availability, consumer behavior, and campaign objectives—making a one-size-fits-all Always–On MMM approach ineffective. A customized and contextualized model enables greater precision, adaptability, and alignment with business requirements, making the solution more effective and sustainable in dynamic environments.
- Dedicated Models for Short-Term and Long-Term: Separate constructs for these cycles capture distinct marketing effects more accurately. Short-term models track immediate response and tactical performance, while long-term models assess brand equity and sustained impact. This separation enhances precision, supports granular decision-making, and ensures flexibility across planning horizons.
- Model Stability and Explainability: Stability and explainability are critical for Always-On MMM. A stable model delivers consistent insights across refresh cycles, while explainability helps teams understand impact drivers, justify recommendations, and drive adoption. Together, they enable confident, transparent, and scalable decision-making across markets.
- GenAI Integration in Process Workflow: GenAI enhances automation and insight generation within the MMM workflow. It enables auto-generated reports, summaries, and recommendations—reducing manual effort and improving efficiency. GenAI also boosts explainability by converting complex outputs into business-friendly narratives, aiding stakeholder understanding and adoption.
Creating Impact, The MathCo Way
A leading CPG manufacturer aimed to optimize marketing spend across channels using historical ROI, seeking a scalable, in-house solution for granular, quarterly analysis—reducing dependency on agency insights. While their existing traditional MMM solution offered periodic insights for mature markets, it lacked the flexibility to support low-granularity regions due to poor data quality, regional variation, and limited automation. Focused only on short-term impact, it couldn’t adapt to evolving market dynamics, resulting in inefficiencies and missed advertising opportunities.
To address these challenges, the client required an Always-On MMM solution capable of analyzing multiple dimensions—channel, platform, format, audience, and campaign—while supporting product-level customization. MathCo transformed their existing MMM approach and delivered an enhanced solution built within the client’s ecosystem, powered by NucliOS, with monthly model runs scaled to major markets. This enabled continuous, data-driven budget optimization and allowed insights to be delivered at the same level of granularity at which business decisions were made.
Our approach focused on creating a solution that was customized and contextualized for each market and level of granularity. Emphasis was placed on scalability, simplicity, and explainability to ensure adoption across major markets. The solution included automated monthly refreshes, minimizing manual intervention, and incorporated triggers for automatic model rebuilds in case of variance.
Our Key Deliverables
MathCo’s commitment to 100% IP ownership was fulfilled through a complete ownership transfer during the pilot phase. The solution was fully deployed within the client’s ecosystem. Key features included:
- AI-generated reports and insights for all markets, powered by NucliOS
- Comprehensive documentation on ad spends, solution code, algorithms, and calculation methodologies
- Seamless integration into the client’s existing infrastructure
The solution enabled monthly and quarterly reporting to track campaign ROI and generate actionable recommendations. Regular model refreshes ensured performance was continuously evaluated, and historical analysis guided the need for model rebuilds.
Our structured, automation-led approach ensured the MMM solution remained robust, adaptive, and scalable. With integrated monitoring and AI-powered tools, the client was empowered to make informed, data-driven marketing decisions and maximize business impact, including:
- 70% effort reduction in data preparation in every refresh cycle
- 90% improved insights adoption through a dedicated consumption program.
- Delivered ~1.3% boost in revenue through always-on media spend adjustments
- Reduced the time taken for custom analysis from 3 months to less than 2 weeks
- Refresh analysis duration reduced from 4 weeks to less than 4 hours
Interested in learning how MathCo can be your Data and Analytics partner of choice in optimizing your marketing spends through Always–On MMM? Contact us here.
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