I have written a few things about the future of retail earlier, in this post I will like to touch upon the AI (artificial intelligence) use cases in retail
- Customer attraction and acquisition: The retail store marketing campaign and digital channels (D2C platforms, mobile apps, loyalty programs) must acquire enough data points to build AI models that can be used for marketing campaigns, recommendations, and push notifications. AI has massive implications in drawing insights out of consumer behavior data.
- Customer service and chatbots: As NLP and voice recognition capabilities improve the 24*7 customer service agents can be managed by AI. The chatbots that can answer all possible FAQ’s or new queries in an accurate manner can save the retailers significant resources
- Video analytics in-store operations: Computer vision could be very much helpful in Fraud identification, shop-lifting prevention. Auto-inventory management and fulfillment can be done with AI-based solutions
- Checkouts and facial recognition tech: Amazon Go tech for cashless checkouts and payment validation, and Alibaba’s smile to pay tech is based on AI facial recognition
5. Visual search/image recognition: O2O enabled retailers can use this feature to increase store engagement and e-commerce channel shopping. Products can be identified based on the picture, and similar/better recommendations can be made too for more sales.
6. Predictive inventor models, logistics excellence, and minimizing seasonal demand fluctuations: Global fashion and retail brands need to move and stock goods in anticipation of seasonal and regional demands. The AI predictive inventory and demand forecast models can help minimize the ‘inventory fiascos’ or ‘loss of sale due to out of stock disasters’. Millions of data points related to product, consumer are analyzed to make the best prediction. IoT sensors and video analytics can also help in ensuring the ‘integrity’ of the supply chain and last mile delivery.
7. Cash and credit, supplier, vendor management– Suppliers and credit risk models are built using artificial intelligence. When you have thousands of suppliers, it makes sense to let the AI model churn out insights that can help you ‘de-risk’ your cash, credit, and supply chain management.
8. Store footfall optimization and location analytics- Store and location analytics are some more ways in which the retailers are leveraging the AI. Helps in optimizing the store design, operations timing, and even the location.
9. Personal virtual assistant that gets trained every time you shop- Walmart is working on VR tech where a virtual assistant can help with the shopper’s offline journey. Over a period of time, the assistant can be trained based on the ‘ user preferences’ hence a personalized assistant will be the next big rollout. This again keeps the O2O experience engaging and immersive.
Sidhartha Sharma (views are personal)
Digital, Platform and Ecosystem expert