Retail

Retail offers vast opportunities for improving operations and of course customer experience through Deep Learning based systems. Personalization and ease of selection have always been key factors for conversion both in offline and online distribution channels. The ability to understand the users within a few interactions not only while product selection but also in during experience management will make sure that the needed service is offered to the customer at the right step and right time. With Deep Learning, Retailers can imagine vast incremental and transformation enhancements to the current services.


On one side, we see the trend of virtual experiences gaining momentum and at the same time the importance for automation and frictional less experience in physical stores is increasing. Deep Learning is emerging as one of the key technologies of such next generational retail experiences.

Customer Experience

Retailers have been aiming for a zero friction shopping experience and the recently announced offline retail brand by an ecommerce giant underscores how crucial this ability has become.


Right from the identifying potential shoppers entry into the store, to help her navigate the aisles, locate the items she wants to buy, compare options, and check out - all these processes can be reimagined with Deep Learning. Computer Vision based technologies could be used to identify customers through face matching, identify customer actions (is he just browsing the aisles or maybe she cannot find something), identify the items and quantities she is loading onto the cart. While the complete process would require advances in payment technology and IOT sensors, deep learning is what would stitch the entire process together.

Store Operations

Vision technologies could also be used to monitor inventory and trigger replenishment or withdrawals of perishable. Also more intangible, implicit customer feedback could be discerned such as was something placed at the ‘wrong height’, how many times was certain pricked up and put back? Cameras could be used to calculate area exposed to shoppers and correlations with sales. Parking image patterns, outside large stores, could also yield predictive clues about footfall volumes and sales.

Analytics

While analytics is integral to almost all aspects of retail, customer analytics in terms of deciding offers and promotions, operational analytics in terms of pricing and supplier performance, deciding product mix, and display formats constructs, employee productivity and store profitability are areas that can now be improved with Deep Learning based systems.

Interested in how Deep Learning can help you?