The retail industry is the second sector most likely to benefit from the transition to AI-driven analytics. AI in retail can enable personalized design and production, anticipate customer demand – predict customers’ orders in advance – and transform inventory and delivery management.
A variety of examples in which AI is being integrated in the retail industry includes the transformation of logistics and delivery (see the ‘Logistics’ section of this briefing), enhancement of payment services and customer verification (see the ‘Banking’ section), as well as sales and CRM management and customer recommendations. You can learn more about potential applications of AI in your company here
AI can be a valuable tool for customer service management and personalization challenges. Improved speech recognition in automated call centers is one example of how the application of AI techniques can lead to a more efficient processing of customers and prioritizing those who need immediate human assistance. Deep learning analysis of audio data can also help assess a customer’s emotional tone; if the customer is having problems with the automated system, the call can be rerouted automatically to human operators. A ‘sales assistant’ software is another useful application designed to automate and enhance sales operations processes by identifying and conversing with internet leads, as well as scheduling follow-up calls with potential customers.
AI can also have a huge impact on other areas of marketing and sales. Frequent interactions between businesses and customers over the Internet generate larger data sets for AI techniques to tap into. E-commerce platforms in particular are likely to benefit from AI solutions in marketing. Combining customer demographic and past transaction data with social media monitoring can help generate individualized product recommendations (we explain this further in the ‘Media’ section). Platforms that collect customer information such as click-throughs or time spent on a web page can then customize promotions and prices, and push specific products through personalized interfaces, adapting to each customer’s needs dynamically and in real time.
