We are in 2025: some contact centers already have advanced technologies for analyzing the customer experience (CX) and processes to analyze the voice of the customer (VOC) – however, this data, which is quite rich, is little used to evaluate the performance of the operation. Instead, we are still using traditional quality assurance metrics for this measurement.
Traditionally, contact centers measure quality assurance through metrics such as average speed of response, average service time, first call resolution rate, possibility for the customer to recommend the service, and the customer’s effort score to be met. Relevant data can be extracted from CX analysis have not been used to assess service quality. why?
Because even with so much information, without a proper solution, vision and strategy, contact centers end up becoming a “black hole” of data.
Without proper treatment, the data remains fragmented in silos, making it difficult to see a holistic view of performance and customer experience.
Data from various channels, such as telephone calls, emails, chats and social networks, are often not correlated effectively, resulting in superficial and disconnected analysis. In addition, the lack of standardization in the collection and treatment of this data can generate inconsistencies and impair the quality of the information used in the evaluations.
According to the Brazilian Association of Teleservices (ABT), the national market for contact center employs millions of people and moves considerable figures, 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 ensuring a more satisfactory customer experience and collecting valuable insights for strategic decision making.
Quality Intelligence: How to measure?
Last June, a Gartner analytical report proposed a completely new measurement measure for contact centers: quality intelligence.
The report prepared by the company brings some interesting insights, the result of a survey carried out by Gartner with leaders of support services and contact center. The first point is that only 19% of respondents consider the agent’s performance to be the main vector of service quality assurance, while 52% highlight CX and VOC as essential measures.
In addition, the quality measurement processes today end up focusing on the analysis of voice channels, leaving digital interactions aside. To complete this scenario, at least 85% of leaders have only manual assessments.
Fundamentally, the measurement of quality intelligence in the contact center brings together three main flows of information: traditional quality analysis data; Speech Analytics data, which bring the analysis of feelings, identifies the emotional tone of conversations, and allows companies to better understand customer reactions; and VOC data, which 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 contact center data into actionable insights – and this is because this analytical methodology not only consolidates data from different communication channels, but also applies advanced to identify patterns and trends that can significantly improve the performance of the service as a whole.
In addition, quality intelligence makes it possible to correlate data from different sources, such as phone calls, emails, chats and interactions on social networks. 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 solve problems and improve customer satisfaction. This unification is possible by the best standardization in data collection and treatment, with the establishment of uniform criteria for the capture and analysis of information, eliminating consistencies and ensuring that all data are considered in the evaluations.
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 masses of data in an agile way.
While in the past it was common to evaluate the service agents through modest sampling of calls or interactions, today there are tools that perform analysis of 100% of the contacts, whether by voice, chat, email or social networks.
The most current 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.
In general, more robust CX solutions rely on already integrated Speech Analytics solutions – and speech and sentiment analysis can, for example, predict which customers are more likely to cancel a service or which type of agent generates greater satisfaction in the public that comes in 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 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 scenario, in which the turnover of professionals is notoriously high, this type of insight provides subsidies for retention strategies, training and selection of more accurate personnel.
With all these considerations, it is possible to conclude that quality intelligence represents a significant evolution in the way contact center performance is seen.
The analysis is no longer focused on evaluating only productivity metrics, but on understanding emotional, contextual and strategic factors present in the relationship between companies and customers. This broader and deeper understanding has the potential to directly impact financial results, consumer satisfaction and the institutional image.
Despite the initial effort to migrate from a merely quantitative model to an integrated assessment of data and behaviors, the benefits are expressive and support based and assertive decisions. In this way, quality intelligence tends to consolidate itself as a reference for managers who see customer service a pillar of differentiation and added value, far beyond the traditional operational indicators that once guided the sector’s strategies.
