From hawkers to roadside stalls to branded showrooms to ecommerce portals, the process of selling consumer goods and services through retail channels has followed an interesting evolution over the years. It is worth noting that with every refinement, the task has continually become more complex and specialised, requiring newer techniques by the sellers. In the age of customer-centric businesses, the role of the retailer becomes extremely critical as the last link in the supply chain; for consumer-facing businesses, this leaves no scope for errors and inaccuracies. In an immensely competitive market which spoils the consumer for choice, brands must embrace AI and data-driven solutions to deliver the best customer experience while keeping the costs low. Here are five case studies that demonstrate effective and innovative AI use by Indian retail brands.
- Video analytics and emotional AI for Bata: The footwear retail company Bata deployed an AI-based video analytics solution to improve the company’s in-store sales, operations, and customer satisfaction. Developed by Agrex.ai, the solution utilised the store’s existing video infrastructure to implement data harvesting and insight generation on smart conversion and audience segmentation. An “Emotions Chart” adjudged the number of customers showing interest in the merchandise and the type of merchandise. The store compared the responses to products and determined which products evoked happy/satisfied emotions.
- Personalised customer engagement program for Blackberrys: The menswear fashion chain Blackberrys utilised AI to raise its revenue with omnichannel engagement. Capillary Technologies implemented the Engage+ platform for Blackberrys, powered by its proprietary AI platform – Zero AI. The adoption of Machine Learning and Artificial Intelligence algorithms created the best campaigns for Blackberrys. The platform’s advanced algorithm automatically picked the best channel mix for a customer by analysing multiple factors like Reachability, Responsiveness Score, and Conversion Probability. Journey Builder enabled Blackberrys to automate engagement across the consumer’s purchase lifecycle and communicate the next best message.
- Combining customer and product intelligence for Tata Cliq: Tata Cliq, the eCommerce arm of the Tata conglomerate, deployed Vue.ai’s Personalization Suite-enabled product discovery for the shoppers on its site. Using Image Recognition and Data Science the solution extracted catalog data, analyzed it with user behavior and enabled the marketing, product and cataloging teams to get actionable insights. These insights improved customer experiences, drove conversions and reduced costs. Customer Intelligence was combined with Product Intelligence to create unique profiles for every customer.
- Customer support automation platform for Nykaa: Nykaa decided to automate its customer support to focus more time on other important aspects of customer experience. Therefore, Nykaa collaborated with Verloop.io to increase customer engagement by solving customer problems over chat. Verloop.io implemented a solution in which Nykaa was able to use bot-qualified questions to handle repetitive requests, including cancellations, returns, shipping inquiries, replacements, refunds, and payment issues. The automation and Verloop’s Natural Language Understanding (NLU) modules were built equally on classical machine learning as well as modern deep learning ideas. The solution has resulted in higher post-purchase customer satisfaction and improved customer loyalty.
- Image-based styling solution for Abof.com: All About Fashion (Abof) is the online venture of the Aditya Birla Group. Abof leveraged Streamoid’s AI-powered recommendation engine, Outfitter, to create complete looks for every product in the inventory. Outfitter is an AI-powered recommendation engine which has helped abof (all about fashion) drive up sales significantly. The online retailer was able to hyper-personalise the shopping experience by recommending the right products, and therefore, increase the conversion rate.
Source: indiaai.gov.in
