UJAS Retail Analytics Business Intelligence solution incorporates rigorous data-driven forecasting methodology that provide our pratners with a more accurate assessment of future demand and thereby help them make better budgeting, planning, pricing and other decisions. Currently the forecasts are based on data mining and time series analysis statistical approach. This is made possible by leveraging data collected over the years that includes:

  • Sales trend
  • Seasonal variations
  • Sales Promotions
  • Promotion types (e.g. price discounts, bogo, multiples, multi-buys, coupons, loyalty points, etc.)
  • Global Events (e.g. holidays, movie release, major sports event, influential person visit, etc.)
  • Demography


Our partners are leveraging the insight gained from statistical Demand Forecasting to make faster informed decisions around:

  • Pricing
  • Capacity requirements
  • Inventory planning
  • Entry/Exit decisions


We are extending the Demand Forecasting to utilize a more sophisticated approach utilizing machine learning and data science, the new enhancement will leverage some of the most efficient forecasting models:

  • Multilayer Perceptron
  • Radial Basis Function
  • Machine Learning
  • Tree algorithm