This is like a financial advisor for your ad budget: it looks at all your past marketing spend and results across channels (TV, search, social, email, etc.) and tells you which ones are actually working, by how much, and where to move money to get better returns.
Brands struggle to understand which marketing channels and tactics are truly driving sales and how to optimally allocate budgets across them. This tool analyzes historical performance and simulates scenarios so marketers can justify spend, cut waste, and plan more effective campaigns based on data rather than guesswork.
If Bonsai directly ingests brands’ first-party data and continuously retrains models, its moat is the proprietary performance dataset and the fact that its MMM sits tightly in the customer’s reporting and planning workflow, making it sticky to replace.
Classical-ML (Scikit/XGBoost)
Structured SQL
High (Custom Models/Infra)
Model retraining and feature engineering complexity as more channels, campaigns, and geographies are added; plus data quality and integration overhead from multiple marketing platforms.
Early Majority
Positioned as a first-party data-centric, SaaS-style MMM platform versus traditional consulting-heavy, cookie-based or panel-based measurement; likely faster to deploy, closer to digital data sources, and more self-service for marketers.