Often, a call center is conditioned to receive calls, find solutions, note the reason, and move on to the next customer in line quickly. But, with contacts lasting just a few minutes, it’s hard to gather relevant information. What if there were a technology that could turn these interactions into learnings 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. Moreover, it’s not just the tone of voice that determines whether an experience was positive or negative, but the overall context of the communication. Factors like regionalisms and cultural expressions play a key 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, identify patterns of dissatisfaction in conversations, anticipate needs, and help businesses improve the customer journey.
“AI performs a detailed analysis of every interaction, something a human analyst, due to the volume of data, couldn’t do with the same breadth and speed. 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 specialized in using Generative AI to turn interactions into actionable intelligence.
Brazil is already emerging as one of the global leaders in adopting this ‘branch’ of AI: the country is among those that use generative artificial intelligence the most worldwide, according to a survey commissioned by Google—54% of respondents said they used the technology last year, while the global average was 48%.
Applied to customer service, generative AI can go beyond its most traditional uses, which involve chatbots and virtual assistants to automate contact. After all, even in automated interactions, the user experience isn’t always satisfactory. That’s why more complex service—or even the customer—still requires human presence.
And it’s in these cases that the less obvious use of AI can be valuable: generative AI analyzes customer behavior in conversations with agents, identifies dissatisfaction patterns, and maps friction points, enabling continuous adjustments to make the journey more efficient. The tool’s data analysis helps brands understand bottlenecks and points of greatest dissatisfaction in service without having to ‘guess’ anything. Thus, improvement decisions are better grounded and, consequently, more likely to yield positive results.
“More than just responding to user requests, Artificial Intelligence allows companies to turn every interaction into an opportunity to enhance their services, ultimately creating a true source of information and addressing the ‘root of the problem’ to solve it. Listening well, 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 service more humanized,” concludes Sena.
