Data processing and analysis to find common patterns, dependencies and areas for optimization: preventing out of stock, diving into promotions’ effectiveness, demand drivers’ decomposition etc.
Forecasting models based on machine learning algorithms: demand forecast, pricing, promotional sales, new products forecast, inventory forecast etc.
Recommendation models maximize profit, revenue, or costs reduction: promotional investment optimization, inventory optimization in a warehouse or store, “smart” pricing etc.
Each project is unique, but each time we develop a custom ML model, we help audit and, if necessary, adjust the target business process, in an attempt to eliminate hurdles while launching and adopting the new technology.
Auditing and adjusting business processes while implementing ML technologies (to ensure effectiveness).
Developing, doing integration work and commissioning ML-enabled forecasting or optimization models.
Providing support for ML models after the launch: Technical support and Methodological support for business teams (outsourcing the role of a demand planner or data scientist).
Data science and Machine learning methods can effectively tackle a number of core business challenges – from demand forecasting to optimizing multi-million budgets spent on price promotions.
Depending on the task and available data, our data scientists develop ML models with unique features and algorithms. An exact business objective can be attained using regressions, decision trees, and/or neural networks.
INTEGRATION
INTEGRATION
Big multinational and local companies in Russia and the USA leverage our solutions for forecasting and optimization.
