Promotion Effectiveness enables enterprises to measure and fully understand the effectiveness of trade promotions. It makes sense of complex and disparate point-of-sale data, to deliver a more accurate analysis across multiple metrics (spend ratio, volume uplift, amongst others). Built on a light weight architecture, it ensures computations and analysis can be run across large data sets.
The application adopts a three stage maturity model, starting with establishing how past promotions were run to leveraging AI modeling techniques to deliver predictive capabilities.
Promotion Effectiveness is designed to leverage advanced ML-based modeling techniques to understand and enhance promotion effectiveness
Proven data platform for data acquisition, cleansing, enriching and harmonizing data across the supply chain network
ML based modeling to understand promotion performance and to identify factors influencing promotion effectiveness
What-if scenario modeling to automatically suggest the most optimal promotions to run under user-defined constraints
Promotion Effectiveness visibility into factors influencing promotion effectiveness and recommending optimized promotion parameters.
Collections teams are now empowered with AI enabled risk segmentation, early prediction of delinquent accounts, suggested treatment plans based on risk segment which helps them improve efficiency
According to recent reports from the Federal Reserve Bank of New York credit card, household debt and auto-loans delinquency rates have been slowly rising, hitting a 7 year high recently.
Organizations – having realized the immense value of sophisticated procurement functions, are transforming their external spend for operations and cost optimizations. There is increased focus now fo