Consumer healthcare marketing mix model & budget optimizer
Proprietary Marketing Mix Model with budget optimization replacing intuitive allocation with data-driven decision making across multiple countries and touchpoints.
The challenge
A global healthcare company was allocating marketing budgets across multiple countries and touchpoints using traditional approaches - historical patterns, intuitive reasoning, and "au doigt mouillé" methods. Marketing teams lacked visibility into which channels and markets were delivering the strongest incremental impact.
Finance teams needed better transparency into budget performance across country-touchpoint combinations to make informed investment decisions. The organization required a systematic, data-driven approach to replace intuitive budget allocation with evidence-based optimization.
The challenge was building a proprietary solution that could quantify incremental sellout impact by channel, model response curves accurately, and provide actionable insights for both marketing and finance stakeholders.
The solution
Our team developed a proprietary Marketing Mix Model that measured incremental sellout response across multiple countries and touchpoints. The model incorporated sophisticated adstock transformations and saturation curves to accurately capture the relationship between spend and incremental impact.
A key innovation was building an integrated budget optimizer that could digest the response curves from the MMM and recommend optimal allocation strategies. This system enabled marketers to understand which levers were most effective and gave finance teams clear visibility into ROI across different country-channel combinations.
The solution moved the organization from intuitive budget decisions to evidence-based allocation, with clear quantification of incremental impact and optimization recommendations that both marketing and finance stakeholders could trust and act upon.
Technical approach
- Proprietary MMM implementation measuring incremental sellout impact across channels
- Advanced adstock modeling to capture carryover effects by touchpoint
- Saturation curve estimation for diminishing returns analysis
- Multi-country model architecture with country-specific parameters
- Integrated budget optimizer with business constraint handling
- Response curve extraction and visualization for stakeholder communication
Implementation
The project was implemented over 18 months with full team collaboration. Initial phases focused on data architecture and model specification across multiple markets. The team developed the core MMM framework, then built the optimizer module that could process response curves and generate allocation recommendations.
Critical success factors included close collaboration with both marketing and finance stakeholders to ensure the solution met practical business needs. The system was designed for operational use, with quarterly model updates and regular optimization runs to adapt to changing market conditions and business priorities.
Results
Overall impact
The implementation fundamentally changed how the organization approaches budget allocation. Marketers gained clear understanding of which levers were most effective, enabling more strategic decisions about channel investment. Finance teams received unprecedented visibility into budget performance across countries and touchpoints, supporting more informed investment decisions. The solution successfully moved the organization from "au doigt mouillé" allocation to systematic, evidence-based optimization with quantified incremental impact and clear ROI metrics that both marketing and finance stakeholders could trust and act upon.
Key lessons
- 1Stakeholder alignment is critical: Success required buy-in from both marketing and finance teams, each with different priorities and success metrics.
- 2Operational design matters: Building for quarterly updates and regular optimization runs ensured the solution remained relevant as business conditions evolved.
- 3Response curve visualization enables action: Clear presentation of spend vs. incremental impact curves helped stakeholders understand and trust optimization recommendations.
- 4Cross-functional collaboration drives adoption: Working closely with both marketing and finance ensured the solution met practical business needs and gained organizational support.
Tech stack
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