Brochures, promotions and commercial initiatives Original control Tool using 1st class Intelligent retail Management for strategic Marketing, sales, profits and sustainable achievements
AI-Powered Promotion Planning for Retail Decision Makers
BOT1MM helps retail groups plan promotions with greater rigor, speed, and commercial confidence. It combines AI-based sales forecasting with year-ahead promotion planning and optimization, turning historical data and business constraints into decision-ready proposals.
BOT1MM was developed to support sales decision makers who need more than visibility into past performance. The platform helps users build, test, and refine promotion strategies designed to improve sales and profit while staying aligned with real operational constraints.
Built Across Two Product Generations
BOT1MM Generation 1: ANN-Based Sales Predictor
The first generation focuses on artificial neural network forecasting, using historical sales and promotion data to predict product performance under different commercial conditions.
EBOT1MM Generation 2: Year-Ahead Promotion Planner & Optimizer
The second generation expanded this into a full decision-support system that creates and refines promotion plans across future weeks, balancing objectives such as sales uplift, profit improvement, and planning efficiency.
Commercial Value
- Supports sales and profit optimization through data-driven promotion planning
- Reduces planning effort from a full working day to automated proposal generation in minutes
- Helps decision makers evaluate scenarios instead of relying only on manual judgment
- Improves consistency and defensibility in promotion decisions
A Closed-Loop Decision Workflow BOT1MM & EBOT1MM combine AI forecasting, optimization, and user-driven refinement in one process. Decision makers can define targets, apply constraints, review proposals, and regenerate plans based on updated assumptions or in-year results. This keeps human expertise in control while the system handles the complexity of evaluating large numbers of promotion combinations.
More Than a Dashboard. More Than a Forecast. Dashboards show what is happening, but they do not tell teams what to do to reach specific commercial goals. Basic forecasting can estimate outcomes, but it does not produce a promotion strategy. BOT1MM & EBOT1MM bridge that gap by generating practical promotion proposals that can be refined in a closed loop with the decision maker. It allows continuous alignment through mid-year proposal re-generation based on real indicators
Constraint Handling BOT1MM & EBOT1MM are built to work within the constraints that make manual planning slow and difficult, including:
- limits on how many products should be promoted in specific weeks
- avoiding repetition of the same offer in consecutive weeks
- preventing overly similar products from being promoted at the same time
- aligning proposals with multi-criteria business targets
BOT1MM & EBOT1MM are deployed on customer infrastructure and has been operational for several years. It typically runs on a virtual machine inside the client network and works with data files generated by the client’s existing systems. Full multi-user environment with controlled access and audit history.
Bring Strategic Rigor to Promotion Planning BOT1MM helps retail decision makers move from slow, manually constrained planning to a faster, evidence-based promotion workflow focused on better commercial outcomes.
References
Bruzzone, A. G., Sinelshchikov, K., Massei, M., & Schmidt, W. (2020). Artificial intelligence to support retail sales optimization. In Proceedings of the 32nd European Modeling & Simulation Symposium, EMSS. doi: 10.46354/i3m.2020.emss.061
Bruzzone, A. G., Sinelshchikov, K., Massei, M., & Schmidt, W. (2021). Machine Learning and Genetic Algorithms to Improve Strategic Retail Management. In Proceedings of the 20th International Conference on Modelling and Applied Simulation. doi: 10.46354/i3m.2021.mas.023