AI Use Case
Optimise retail network based on demand modelling
Optimise retail network locations based on multiple signals of demand (e.g., social data, footfall, transactions). This would - for example - help a retailer to plan their expansion in to a new market. Alternatuvely this might enable cost savings across a retail banking operation where it would likely cover both branches and ATMs - at the risk of medium to long term revenue loss and potential negative customer and press reaction.
Function
Operations
Network Operations
Benefits
Cost - Optimise geographic footprint ,Revenue - Better targeting,Operational - Network optimisation
Case Studies
Stanford University~Researchers at Stanford and Columbia predict restaurant affinity among lunch-goers in the Bay area using machine learning
Potential Vendors
Industry
Financial Services
Banking
Data Sets
Structured / Semi-structured,Time series,Text
AI Technologies
Traditional AI,Machine Learning (ML),ML Task - Action Selection - Reinforcement Learning