Planning & Forecasting for Marketing Mix Modeling (MMM)
Automated planning & forecasting function supporting Marketing Mix Modeling (MMM). Part of the Marketing Mix Modeling (MMM) capability.
Business Outcome
time reduction in model development and validation (from 1-2 weeks to 3-5 days).
Complexity:
MediumTime to Value:
1-2Why This Matters
What It Is
Automated planning & forecasting function supporting Marketing Mix Modeling (MMM). Part of the Marketing Mix Modeling (MMM) capability.
Current State vs Future State Comparison
Current State
(Traditional)- Define objectives and key performance indicators (KPIs) for the marketing mix.
- Gather historical data on marketing spend, sales, and external factors (e.g., seasonality, economic indicators).
- Clean and preprocess data to ensure accuracy and consistency.
- Use statistical methods (e.g., regression analysis) to build the MMM model.
- Validate the model using a holdout dataset to ensure predictive accuracy.
- Conduct scenario analysis to evaluate the impact of different marketing strategies.
- Generate forecasts based on the model outputs.
- Present findings and recommendations to stakeholders for decision-making.
- Monitor performance against forecasts and adjust the model as necessary.
Characteristics
- • Excel
- • R
- • Python
- • Tableau
- • Google Analytics
- • CRM Systems
- • ERP Systems
Pain Points
- ⚠ Manual data entry is time-consuming
- ⚠ Process is error-prone
- ⚠ Limited visibility into process status
- ⚠ Dependence on historical data which may not predict future trends accurately
- ⚠ Complexity of integrating multiple data sources
- ⚠ Limited ability to account for external factors affecting marketing effectiveness
- ⚠ Resource-intensive process requiring specialized skills
Future State
(Agentic)- Orchestrator initiates the process and assigns tasks to the Data Ingestion Agent.
- Data Ingestion Agent gathers data from various sources and preprocesses it.
- Orchestrator confirms data quality with the Data Quality Assurance Agent.
- Model Development Agent builds the MMM using the cleaned data.
- Model Development Agent validates the model and conducts scenario analysis.
- Forecasting Agent generates forecasts based on the model outputs.
- Reporting Agent creates visualizations and reports for stakeholders.
- Orchestrator presents findings to stakeholders and monitors performance against forecasts.
Characteristics
- • System data
- • Historical data
Benefits
- ✓ Reduces time for Planning & Forecasting for Marketing Mix Modeling (MMM)
- ✓ Improves accuracy
- ✓ Enables automation
Is This Right for You?
50% match
This score is based on general applicability (industry fit, implementation complexity, and ROI potential). Use the Preferences button above to set your industry, role, and company profile for personalized matching.
Why this score:
- • Applicable across multiple industries
- • Moderate expected business value
- • Time to value: 1-2
- • (Score based on general applicability - set preferences for personalized matching)
You might benefit from Planning & Forecasting for Marketing Mix Modeling (MMM) if:
- You're experiencing: Manual data entry is time-consuming
- You're experiencing: Process is error-prone
- You're experiencing: Limited visibility into process status
This may not be right for you if:
- Requires human oversight for critical decision points - not fully autonomous
Parent Capability
Marketing Mix Modeling (MMM)
Delivers continuous MMM refresh with instant scenario testing, automated recommendations, and integrated planning achieving significant media efficiency improvement.
What to Do Next
Add to Roadmap
Save this function for implementation planning
Related Functions
Metadata
- Function ID
- function-marketing-mix-modeling-mmm-1