Often, a call center is conditioned to receive calls, find solutions, note the reason, and quickly pass them on to the next customer in line. But with contacts lasting only a few minutes, it's difficult to obtain relevant information. What if there was a technology that transformed these interactions into learning experiences for the future?
This technology already exists and goes beyond phone calls; any type of conversation between a customer and a company can be analyzed. Furthermore, it's not just the tone of voice that defines whether an experience was positive or negative, but rather the overall context of the communication. Factors such as regionalisms and cultural expressions play a fundamental role in this interpretation, as a person may sound agitated when commenting on an event without necessarily being dissatisfied, or may use colloquial expressions without negative connotations.
With Generative Artificial Intelligence—which not only automates tasks but also analyzes data and generates insights—companies can, in addition to resolving specific issues, examine thousands of files and data points, identify patterns of dissatisfaction in conversations, anticipate needs, and help companies improve the customer journey.
“AI performs a detailed analysis of each interaction, something that a human analyst, due to the volume of data, could not do with the same scope and in the same time. By identifying opportunities, even in the smallest conversations, the tool transforms these insights into actionable intelligence for the company,” explains Carlos Sena, founder of AIDA , a platform specializing in the use of Generative AI to transform interactions into actionable intelligence.
Brazil is already emerging as one of the global leaders in adopting this "arm" of AI: the country is among those that use generative artificial intelligence the most in the world, according to a survey commissioned by Google — 54% of respondents said they had used the technology last year, while the global average was 48%.
Applied to customer service, generative AI can go beyond its more traditional use, which involves chatbots and virtual assistants to automate contact. This is because, even in automated interactions, the user experience is not always satisfactory. Therefore, more complex service requests—or even the customer themselves—still require human intervention.
And it is in these cases that the less obvious use of AI can be valuable: generative AI analyzes customer behavior in conversations with agents, identifies patterns of dissatisfaction, and maps points of friction, allowing for continuous adjustments to make the journey more efficient. The data analysis performed by the tool helps brands understand bottlenecks and points of greatest dissatisfaction in customer service, without having to "guess" anything. Thus, improvement decisions are better informed and, consequently, have a greater chance of producing positive effects.
“More than just responding to user requests, Artificial Intelligence allows companies to transform each interaction into an opportunity to improve their services, ultimately creating a true source of information and getting to the 'root of the problem' to solve it. Listening carefully, reflecting, analyzing, and organizing calls can be the difference between losing a customer or winning them over forever. It may seem contradictory, but technology ends up being a great ally in making customer service more humanized,” concludes Sena.
