We developed integrated solution which utilized a bottom-up forecasting approach as the core analytics engine

  • Customer base of the client was segmented into various vintages, depending upon their transaction and feature profiles. Time series techniques were then used to generate day level forecast for the clients.
  • Business drivers such as Quality of Sale, Adoption rate, Product mix were created and impact of the drivers on forecast was estimated. A model was then used to refine the long-term forecast using the business drivers.
  • Final long-term forecast was again broken down to give customer level forecast.


  • The automated model cut down the time required to build forecast from a month-long exercise to few days
  • Scenario planning tool built on top of forecasting model helped planning and strategy team take data backed decisions


The impact of solution was twofold:

  • Automated model proved out have ~90% accuracy overall, leading to very accurate target setting for sales teams
  • Scenario planning tool helped marketing and sales organization streamline the effort and resource investment towards growth