We are in 2025: some contact centers already have advanced technologies for analyzing customer experience (CX, in the English acronym) and processes to analyze the Voice of the Customer (VoC) – meanwhile, these data, they are quite rich, are rarely used to assess the performance of the operation. Instead of that, we are still using traditional quality assurance metrics for this measurement
Traditionally, contact centers measure quality assurance through metrics such as average response time, average service time, first call resolution rate, possibility of the client recommending the service, and the customer effort score in being served. Relevant data that can be extracted from CX analysis has not been used to assess service quality. Why
Because even with so much information, without a solution, appropriate vision and strategy, contact centers end up becoming a "black hole" of data
Without the proper treatment, the data remains fragmented in silos, making it difficult to have a holistic view of performance and customer experience
Data from various channels, like phone calls, e-mails, chats and social networks, often they are not correlated effectively, resulting in superficial and disconnected analyses. Furthermore, the lack of standardization in the collection and processing of these data can generate inconsistencies and harm the quality of the information used in evaluations
According to the Brazilian Association of Teleservices (ABT), the national contact center market employs millions of people and generates considerable amounts, especially after the growth of e-commerce and the digitization of consumer relationship processes. In this complex reality, the search for efficiency is no longer limited to reducing operating costs, but to ensure a more satisfying experience for the customer and to collect valuable insights for strategic decision-making
Quality Intelligence: how to measure
In last June, an analytical report from Gartner proposed a completely new measurement for contact centers: Quality Intelligence
The report prepared by the company brings some interesting insights, results of a survey conducted by Gartner with leaders in support services and contact centers. The first point is that only 19% of respondents consider the agent's performance as the main driver of service quality assurance, while 52% highlight CX and VoC as essential measures
Furthermore, the quality measurement processes today end up focusing on the analysis of voice channels, putting digital interactions aside. To complete this scenario, at least 85% of leaders rely solely on manual evaluations
Fundamentally, the measurement of Quality Intelligence in the contact center brings together three main information flows: traditional quality analysis data; Speech Analytics data, that bring sentiment analysis, identify the emotional tone of the conversations, and allows companies to better understand customer reactions; and the VoC data, that represent the feedback provided directly by the customer
In this sense, Quality Intelligence is an innovative approach that integrates advanced technologies and holistic strategies, transforming the vast volume of data from the contact center into actionable insights – and this happens because this analytical methodology not only consolidates data from different communication channels, but also applies advanced analyses to identify patterns and trends that can significantly improve the overall service performance
Furthermore, Quality Intelligence enables the correlation of data from various sources, like phone calls, e-mails, chats and interactions on social media. By unifying this information, it is possible to obtain a more complete and accurate view of the customer experience, allowing companies to take proactive actions to solve problems and improve customer satisfaction. This unification is possible due to better standardization in data collection and processing, with the establishment of uniform criteria for the capture and analysis of information, eliminating inconsistencies and ensuring that all data is considered in the evaluations
How a CX platform can contribute to the process
It is possible to note that the Quality Intelligence approach has roots in technological advancements that enable the analysis of large amounts of data in an agile manner
While in the past it was common to evaluate customer service agents through modest samples of calls or interactions, today there are tools that analyze 100% of the contacts, let them be by voice, chat, email or social media
The most current CX platforms offer robust tools for data collection, integration and analysis of data from multiple communication channels. The use of an intelligent customer experience management platform allows contact centers to establish uniform criteria and optimize their processes, resulting in a more cohesive and satisfying customer experience
In general, more robust CX solutions include integrated Speech Analytics solutions – and discourse and sentiment analysis can, for example, predict which customers are more likely to cancel a service or which type of agent generates the highest satisfaction among the public that makes contact. If a certain pattern of conversation or approach proves to be more efficient, these insights can be used to train the entire team, raising the overall level of performance
Thus, Quality Intelligence not only measures what happened, but indicate which actions can be implemented for better results. This type of intervention is essential for managers who need to make high-impact decisions in competitive environments. In the Brazilian scenario, in which the turnover of professionals is notably high, this type of insight provides support for retention strategies, more refined training and selection of personnel
With all these considerations, it is possible to conclude that Quality Intelligence represents a significant evolution in the way contact center performance is viewed
The analysis no longer focuses solely on evaluating productivity metrics, but in understanding emotional factors, contextual and strategic aspects present in the relationship between companies and customers. This broader and deeper understanding has the potential to directly impact financial results, consumer satisfaction and institutional image
Despite the initial effort to migrate from a merely quantitative model to an integrated assessment of data and behaviors, the benefits are significant and support informed and assertive decisions. In this way, Quality Intelligence tends to establish itself as a reference for managers who see customer service as a pillar of differentiation and added value, far beyond the traditional operational indicators that once guided the sector's strategies
