The model training step forms the heart of the system where the causals are treated as predictors and is assembled in mathematical form to explain the outcome. One should handle the training data with utmost care and ensure to incorporate methods to detect data outliers. Algorithms should be enabled for modeling the derived causals for training like seasonality, which could decide when the event should be positioned.
Enabling Machine Learning for accurate event prediction
There is a whole lot of buzz around the AI framework called machine learning and often is perceived as a very complex system to be put together. Applying machine learning specifically to trade promotion planning yields a lot of valuable insights, for example allowing the identification of ideal promotion tactics not visible in simple financial analysis, such as which promotional event to plan just after the summer vacation (unlike the traditional approach of planning a promotion event only during the summer vacation, this framework also helps in planning non-standard promotion design).
There are 2 key facets in implementing machine learning based event detection system –
a) Learning algorithm
b) Scalable solution
For trade promotion modeling, a simplistic multi-variation regressive model with a good variable screening system should yield excellent results and is a more easy & scalable solution to implement. The Promax Optimize solution takes your promotion returns to a new growth trajectory with machine learning framework complemented by insights from skilled CPG domain experts and data scientists.
Promax TPO has predictive planning capability – providing users the ability to quickly and efficiently conduct ‘what – if’ analysis, hypothesis based testing to model different promotion scenarios, and tailor the best promotional calendar based on the demography and company needs.
Our data science and professional services teams are led by experienced domain experts to give you a competitive advantage through best practices in trade promotion optimization.
For more information, visit our website http://promax.wipro.com For queries, write to us at WPAS-Promax@wipro.com