Project Overview This project aims to develop a robust agile marketing mix modeling (MMM) platform that enables high-frequency, multi-channel media optimization, incrementality experimentation, and actionable business insights for enterprise brands. Primary Objectives • Deliver a SaaS cloud-based MMM system with rapid, ongoing insight and forecasting for media investments. This includes user management as well as payment and invoicing. • Integrate causal experimentation and incrementality measurement to validate and calibrate model outputs. • Enable real-time media plan optimization and scenario forecasting for planning, spending, and ROI. Key Deliverables • Unified media data ingestion pipeline for cross-channel performance (e.g., TV, Facebook, Search, Social, Display). • Agile MMM engine, using cutting-edge statistical or machine learning models (Bayesian, hierarchical regression, ad-stock modeling). • Experimentation design and holdout support for incrementality testing across channels. • Dynamic dashboard for weekly reporting, scenario analysis, and investment recommendations. • Transparent model documentation, validation workflows, and scorecarding. Data Management & Processing • Build and QA data ETL pipelines covering spend, impressions, clicks, CRM, external factors (macroeconomic, competitive, weather, etc.).[1][4][3] • Implement automated data harmonization and processing to enable weekly modeling refreshes.[2][9] Modeling Engine Development • Develop, calibrate, and validate agile MMM models supporting multiple techniques (e.g., regularized regression, Bayesian, causal inference). • Integrate experimentation workflow to enrich models (e.g., geo holdout, A/B, cross-channel incrementality). • Develop scenario forecast module, including diminishing returns analysis. Experimentation & Incrementality Measurement • Build user-friendly experimentation tools for campaign holdouts, geo-experiments, and split tests. • Automate incrementality reporting and calibration feedback loops. Visualization, Optimization, and Reporting Module • Design dynamic dashboards for performance monitoring, scenario analysis, benchmark comparisons, and cross-channel reporting. • Enable media plan optimization recommendations with actionable, weekly insights. Validation, Transparency, & Documentation • Develop scorecard tools for transparency on model inputs, uncertainty, and QA status. • Document modeling decisions, limitations, and operational guidelines in a customer-facing knowledge base. Deployment, Training, & Support • Deliver the platform via a scalable cloud infrastructure with API access, onboarding, and ongoing support. • Provide six months post-launch technical support and a price framework for work beyond the sixth month. Technology & Tools Recommendations • Scalable cloud infrastructure for data and dashboard management. • Automated reporting, experimentation modules, and integration APIs. Includes front-end and back-end design and development.