We are in 2025: some contact centers already have advanced customer experience (CX) analysis technologies and processes to analyze the Voice of the Customer (VoC) – however, these data, which are quite rich, are rarely used to assess operational performance. Instead, we are still using traditional quality assurance metrics for this measurement.
Traditionally, contact centers measure quality assurance through metrics such as average response speed, average handling time, first call resolution rate, the likelihood of the customer recommending the service, and the customer's effort score in being served. Relevant data can be extracted from CX analysis but have not been used to assess service quality. Why?
Because even with so much information, without an appropriate solution, vision, and strategy, contact centers end up becoming a "black hole" of data.
Without proper treatment, the data remains fragmented in silos, hindering a holistic view of performance and customer experience.
Data from various channels, such as phone calls, emails, chats, and social media, are often not effectively correlated, 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 Tele-services (ABT), the national contact center market employs millions of people and moves significant figures, especially after the growth of e-commerce and the digitization of customer relationship processes. In this complex reality, the pursuit of efficiency is no longer limited to reducing operational costs but also to ensuring a more satisfying customer experience and collecting valuable insights for strategic decision-making.
Quality Intelligence: how to measure it?
Last June, a Gartner analytical report proposed a completely new measurement metric for contact centers: Quality Intelligence.
The report prepared by the company presents some interesting insights, resulting from a survey conducted by Gartner with support service and contact center leaders. The first point is that only 19% of respondents consider the agent's performance as the main factor ensuring service quality, while 52% highlight CX and VoC as essential measures.
Furthermore, quality measurement processes today tend to focus on voice channels, neglecting digital interactions. To complete this scenario, at least 85% of leaders rely solely on manual assessments.
Fundamentally, the measurement of Quality Intelligence in the contact center gathers three main streams of information: traditional quality analysis data; Speech Analytics data, which provides sentiment analysis, identifies the emotional tone of conversations, and allows companies to better understand customer reactions; and VoC data, which represents feedback directly provided by the customer.
In this sense, Quality Intelligence is an innovative approach that integrates advanced technologies and holistic strategies, transforming the vast volume of contact center data 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 overall service performance.
Furthermore, Quality Intelligence enables the correlation of data from various sources, such as phone calls, emails, chats, and social media interactions. By unifying this information, it is possible to obtain a more complete and accurate view of the customer experience, allowing companies to adopt proactive actions to resolve issues and improve customer satisfaction. This unification is possible through better standardization in data collection and processing, with the establishment of uniform criteria for capturing and analyzing information, eliminating inconsistencies and ensuring that all data are considered in the assessments.
How a CX platform can contribute to the process
It is possible to notice that the Quality Intelligence approach has roots in technological advances that enable the analysis of large volumes 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 contacts, whether by voice, chat, email, or social media.
The most current CX platforms offer robust tools for collecting, integrating, and analyzing 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 come with 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 greater satisfaction among the audience that contacts us. If a certain conversation pattern or approach proves to be more effective, 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 also indicates 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 context, where professional turnover is notoriously high, this type of insight provides support for more refined retention, training, and personnel selection strategies.
With all these considerations, it is possible to conclude that Quality Intelligence represents a significant evolution in how contact center performance is viewed.
The analysis no longer focuses solely on evaluating productivity metrics but on understanding emotional, contextual, and strategic factors present in the relationship between companies and clients. This broader and deeper understanding has the potential to directly impact financial results, customer satisfaction, and the institutional image.
Despite the initial effort to shift from a purely quantitative model to an integrated assessment of data and behaviors, the benefits are significant and support well-founded 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.
