It’s 2025: some contact centers already have advanced customer experience (CX) analytics technologies and processes to analyze the Voice of the Customer (VoC) – however, these very rich datasets are rarely used to evaluate operational performance. Instead, we are still using traditional quality assurance metrics for this measurement.
Traditionally, contact centers measure quality assurance through metrics like average response speed, average handling time, first-call resolution rate, likelihood of the customer recommending the service, and the Customer Effort Score. Relevant data that could be extracted from CX analysis hasn’t been used to assess service quality. Why?
Because even with so much information, without proper solutions, vision, and strategy, contact centers end up becoming a ‘black hole’ of data.
Without proper processing, data remains fragmented in silos, making it difficult to get a holistic view of performance and customer experience.
Data from various channels, such as phone calls, emails, chats, and social media, often isn’t effectively correlated, resulting in superficial and disconnected analyses. Additionally, the lack of standardization in collecting and processing this data can lead to inconsistencies and impair the quality of information used in evaluations.
According to the Brazilian Association of Teleservices (ABT), the national contact center market employs millions of people and moves significant revenue, especially after the growth of e-commerce and the digitalization of consumer relationship processes. In this complex reality, the pursuit of efficiency is no longer just about reducing operational costs, but also ensuring a more satisfactory customer experience and gathering valuable insights for strategic decision-making.
Quality Intelligence: how to measure it?
Last June, an analytical report by Gartner proposed a completely new measurement for contact centers: Quality Intelligence.
The report by Gartner presents interesting insights from a survey conducted with support service and contact center leaders. The first finding is that only 19% of respondents consider agent performance as the main driver of service quality assurance, while 52% highlight CX and VoC as essential measures.
Moreover, current quality measurement processes tend to focus on voice channel analysis, leaving digital interactions aside. Adding to this scenario, at least 85% of leaders rely solely on manual evaluations.
Fundamentally, Quality Intelligence measurement in contact centers combines three main data streams: 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 provided directly by customers.
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—this happens because this analytical methodology not only consolidates data from different communication channels but also applies advanced analytics to identify patterns and trends that can significantly improve overall service performance.
Additionally, Quality Intelligence enables the correlation of data from multiple sources, such as phone calls, emails, chats, and social media interactions. By unifying this information, a more complete and accurate view of the customer experience is possible, allowing companies to take proactive actions to solve problems 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 all data is considered in evaluations.
How a CX platform can contribute to the process
It’s clear that the Quality Intelligence approach is rooted in technological advancements that enable agile analysis of large datasets.
While in the past it was common to evaluate customer service agents through modest call or interaction samples, today there are tools that analyze 100% of contacts, whether by voice, chat, email, or social media.
The most advanced CX platforms offer robust tools for collecting, integrating, and analyzing data from multiple communication channels. Using an intelligent customer experience management platform allows contact centers to establish uniform criteria and optimize their processes, resulting in a more cohesive and satisfactory customer experience.
Generally, more robust CX solutions include integrated Speech Analytics—voice and sentiment analysis can, for example, predict which customers are more likely to cancel a service or which type of agent generates higher satisfaction among contacting customers. If a particular conversation pattern or approach proves more effective, these insights can be leveraged to train the entire team, raising overall performance levels.
Thus, Quality Intelligence not only measures what happened but also indicates which actions can be implemented for better results. This type of intervention is crucial for managers who need to make high-impact decisions in competitive environments. In Brazil, where staff turnover is notoriously high, these insights provide foundations for more refined retention, training, and hiring strategies.
Considering all these points, it’s clear that Quality Intelligence represents a significant evolution in how contact center performance is viewed.
Analysis no longer focuses solely on productivity metrics but on understanding emotional, contextual, and strategic factors in company-customer relationships. This broader and deeper understanding has the potential to directly impact financial results, customer satisfaction, and institutional reputation.
Despite the initial effort required to shift from a purely quantitative model to an integrated evaluation of data and behaviors, the benefits are substantial and support more informed and assertive decisions. Thus, Quality Intelligence is poised to become a benchmark for managers who see customer service as a pillar of differentiation and added value—far beyond the traditional operational metrics that once guided sector strategies.
