The omnichannel strategy is a well-known business model for retailers. An omnichannel retailer uses traditional channels and digital channels to serve customer needs. One of the challenges in retail today is how best to apply an omnichannel strategy to customer’ needs by understanding their preferences and habits. Retailers are using new technologies such as Artificial Intelligence and Machine Learning to improve their understanding of their customers and provide personalized experiences based on these insights. This presents an opportunity for retailers and brands to differentiate themselves by offering truly personalized service to their customers.
However, the use of these technologies in retail is evolving rapidly and many are still at the pilot stage. Artificial Intelligence and Machine Learning can help provide actionable insights about customer behavior and purchasing patterns. For example, it could identify customers who are likely to abandon their carts and offer specific incentives to try to convert them into customers. Although this may seem obvious to some retailers, there are still other who have been slow to adopt technologies such as mobile wallets, chatbots or voice-assisted shopping assistants.
Walmart is using facial recognition technology to identify customers who are annoyed and intervene accordingly. It used this technology at one of its stores and were able to scan the faces of customers at checkout lanes. Mood tracking enables a shop representative to get notified and talk to annoyed customers, improving the overall customer experience (Chuprina & Roman, 2022).
The challenge ahead for retailers will be to develop a clear understanding of their customer’s needs and personal preferences and then use this insight to design innovative products and services to deliver a truly personalized experience. One way is by using AI technology, enabling stores to recognize and greet customers, suggest products provide recommendations, and perform other tasks with few or no interactions with staff. In the future, we may see the development of such “Intelligent Retail” stores where the shopping experience is tailored exactly to the customer’s needs.
References
Chuprina, Roman (2022): Artificial Intelligence for Retail in 2022: 12 Real-World Use Cases – SPD Group Blog, Full-cycle Software Development Solutions, https://spd.group/artificial-intelligence/ai-for-retail/
