Artificial intelligence (AI) already had the capability to understand customer language, assess their demands, and direct them to the most appropriate sectors, making customer service more efficient and agile. This is how it established itself as a pillar for retail organizations. Now, with the rise of Generative AI, the technology has taken a step further: it now offers more personalized interactions, capable of truly understanding consumer behavior. According to the BoF-McKinsey State of Fashion survey, 79% of customers expect AI to understand their needs and offer more accurate recommendations.
“Imagine a scenario where the system detects, for example, that a large portion of customers is dissatisfied with waiting times in lines or lack of stock. Or that a certain product or promotion causes more irritation in tone of voice than average. With such specific information at hand, the tool can suggest a more empathetic approach by sales associates or other improvements to retain this consumer. As a bonus, the store gains access to a valuable, organized database extracted from its own customer interactions,” explains Carlos Sena, founder of AIDA, a Generative Artificial Intelligence (GenAI) platform focused on deciphering the Voice of the Customer.
This solution is not limited to interpreting spoken words, as chatbots do, but also analyzes regionalisms, emotions, and the context of each interaction. This allows for identifying behavioral patterns and critical improvement points, offering insights to enhance customer satisfaction and loyalty.
By analyzing these interactions, it’s possible to anticipate certain customer behaviors and needs, enabling the development of more personalized sales strategies and more satisfying experiences to be used as a reference. “It’s not just about solving problems but learning from them,” continues Sena.
In other words, beyond reducing response times in customer service, AI also contributes to the training of sales and support teams. A McKinsey study proving the long-term effectiveness of this method shows that companies using AI for employee training saw an increase in operational efficiency. Thus, using the data and insights collected about the target audience, the platform can serve as an aid in retail team training.
“With more efficient service, retention and satisfaction rates tend to increase while operational costs are reduced. AI does not replace the salesperson or human attendant—quite the opposite; we believe they are extremely necessary. But it empowers these professionals with the tools they lacked to offer the best possible solutions,” concludes Carlos Sena.
