1.1 Case Summary
This case presents the results achieved in the performance of quality monitoring processes at HCosta's operations. The company, a BPO specialist representing some of Brazil's largest banks in collections, adopted the 2clix solution — a technology platform focused on quality management and auditing. With the goal of transforming its quality management and boosting operational performance, HCosta turned to 2clix to automate its monitoring process, which until then was done manually, with low coverage and limited reach.
In just 12 months, the AI-based solution enabled 100% automation of evaluation volume, a 29% reduction in quality resource costs, a 51% decrease in average evaluation and feedback time, plus a 17% improvement in quality performance.
The integration between quality analysis and performance indicators consolidated a new data-driven management culture, accelerating team maturity and promoting smarter decision-making.
Partnership
For over 10 years, 2clix has specialized in technology and artificial intelligence applied to data analysis and quality monitoring. A multidisciplinary team with extensive contact center and technology development experience. A fast-to-implement SaaS model, with real-time insights and close support for every client.
HCosta is a BPO company specialized in relationship management, with over 30 years of operation. Since 1995, a specialist in customer relationships and legal representation for financial institutions, with the purpose of acting as an agent of social transformation.
Diagnosis
HCosta excels at relationship management, specializing in multichannel collection operations involving high volumes of service across different delinquency ranges. With a structured operating model, the company organizes its activities into portfolios segmented by client and delinquency profile.
Within this ecosystem, the Quality team plays a key role in sustaining results, responsible for monitoring, evaluating, and developing operator performance. However, the limitations of manual sample-based analysis made the process slow and less efficient given the growing volume of interactions and the need for faster training of new operators.
With recent economic impacts and growing demand for faster, more scalable results, investing in technology solutions that could ensure standardization, agility, and precision in quality evaluation became strategic.
Diagnosis
Before implementing the 2clix solution, HCosta faced critical challenges in managing the quality of its service operations due to manual processes, which resulted in several bottlenecks:
Manual monitoring covered only a portion of evaluations, resulting in a limited view of performance. Analysis was unrepresentative, making it hard to identify patterns and critical areas.
Feedback turnaround time was high — an average of approximately 11min20s — compromising failure correction and agile employee development.
Each analyst handled both evaluation and feedback, creating overload. The volume, combined with the lack of automation, resulted in an analysis error rate above 25%.
Impact on KPIs
These problems directly affected the operation's KPIs. The pilot portfolio's average conversion rate was just 30%, and the operators' maturity curve was 30% below ideal.
Diagnosis
The critical analysis revealed that the main performance gaps were linked to a lack of scalability and the absence of a data-driven approach to monitoring and feedback. Some of the main impact points were:
The operation needed a solution capable of handling much larger volumes of interactions, given the company's growth and customer demand.
Without an automated tool, managers had only a partial view of operational performance, making real-time analysis difficult.
The low frequency and limited quality of feedback affected operator learning, delaying their maturity curve.
The impact on conversion was evident, with a high AHT of 26 minutes per interaction, resulting in higher operational costs.
Diagnosis
The implementation of the 2clix solution at HCosta followed a structured methodology focused on optimizing quality monitoring, since the chosen portfolio involved guaranteed judicial recovery. The implementation phases were:
Presenting 2clix's objectives and how AI can be an ally for quality and performance. Machine learning concepts for Speech Analytics.
Aligning technical and behavioral criteria. A checklist based on the critical indicators of the guaranteed judicial portfolio.
The quality team analyzed real calls from the pilot portfolio; their scoring trained the AI model through review and rework cycles.
The team compared AI scoring with human evaluations via cross-sampling, fine-tuning false positives/negatives.
Formalizing guidelines for the ongoing use of AI in the operation, including best practices, model limitations, and retraining triggers.
3.1 Strategic Objectives
The implementation of the 2clix solution at HCosta was guided by clear strategic objectives, focused on raising operational productivity, expanding AI-powered monitoring capacity, and boosting team performance:
Replace the manual sample-listening model with an automated voice and text analysis system, with broader, more precise, and impartial coverage.
Previously, fewer than 50% of analysts met the monthly target. With AI, the goal is up to 100% coverage, without expanding the analyst team.
By reducing manual operational workload, the analyst's role becomes more strategic. An estimated 60% of time will be redirected to coaching and manager support.
The full cycle, which previously took up to 00:11:20, will be reduced to under 00:07:00, thanks to automated reports and real-time dashboards.
Automatic categorization and personalized scores will enable training paths based on real data, increasing training effectiveness by up to 40%.
It will be possible to identify operators with greater affinity for certain customer profiles, boosting efficiency and conversion by up to 27%.
Target Audience
The implementation of 2clix's AI solution at HCosta generated significant impacts across different fronts, extending benefits beyond the internal operation: Collection Operators (base), Internal Audience — quality analysts and operational leaders (middle), and B2B (top).
| Segment (internal audience) | Direct impacts | Observed benefits |
|---|---|---|
| Quality Analysts | 60% reduction in repetitive operational workload; greater focus on strategic analysis | A more consultative role; involvement in coaching and team development |
| Collection Operators | Faster feedback (within 24h); access to personalized reports | More clarity on goals; continuous improvement; less rework |
| Leaders and Managers | Real-time indicator dashboards; structured data for precise decisions | Proactive management; faster interventions; increased performance |
| Dimension (external audience) | Perceived transformations | Potential benefits |
|---|---|---|
| Customer Experience | 46% reduction in overall average AHT; more objective, empathetic service | Faster service; higher satisfaction and engagement |
| Conversion and Efficiency | Operator-customer profile matching; reduced friction in service | Higher recovery rate; more assertive service |
| Corporate Clients | More robust, impartial monitoring; greater data traceability | Increased trust in the partner; broader quality and compliance visibility |
Solution
To scale the Quality team's work, HCosta implemented the AI-Powered Automatic Monitoring solution, provided by 2clix. The solution automates the analysis of interactions quickly and in depth, generating strategic, actionable insights. As a result, analysts began focusing on what really matters: development and performance, leaving repetitive operational tasks behind.
Beyond automation, the tool was integrated with operational indicators, enabling real-time tracking of its direct impact on key KPIs such as conversion, average handling time, success rate, script adherence, and customer satisfaction (CSAT).
Ability to monitor 100% of evaluations with intelligence.
Automatic identification of behavioral patterns and improvement opportunities.
Automated feedback tailored to each operator's profile.
The AI was configured to analyze voice and text interactions in bulk, extracting behavioral and technical data with a high degree of accuracy. This automation eliminated manual bottlenecks and doubled monthly listening capacity per operator.
The new model ensured greater agility, analytical depth, and precision in quality decision-making.
Solution
The solution was woven across operational flows, creating a continuous, integrated circuit between service, quality, and management. This flow enabled a data-driven continuous improvement journey, where every stage — from listening to correction — connects in real time.
41% reduction in average analysis and feedback time.
Dynamic access to critical indicators and predictive alerts.
+28% increase in operational forecast accuracy.
Results
The implementation of AI Monitoring, combined with the partnership with 2clix, redesigned the dynamics of operational quality management. The result was a continuous improvement cycle with significant impacts on key indicators, team behavior, and the company's strategic performance.
Results
| Indicator | Before | After implementation | Change |
|---|---|---|---|
| Conversion via profile match | 28.04% | 38.48% | 27.13% |
| AHT reduction | 00:26:09 | 00:20:10 | -34% |
| Average evaluation and feedback time | 00:11:20 | 00:05:26 | 41% |
| Quality resource cost reduction | R$ 2,624,400.00 | R$ 2,041,200.00 | -29% |
Results
From evaluator to strategic performance analyst, actively engaged in coaching, development, and designing personalized training paths.
Fast, personalized, relevant feedback: +18% engagement in feedback sessions and +21% adoption of correction learning paths.
With AI's smart alerts, management began anticipating deviations and planning corrections ahead of time: +28% accuracy in operational forecasts.
Management with real-time dashboards, expanding the capacity for data-driven decisions and reducing reaction time to performance variations.
Results
Results
Beyond operational indicators and gains, the solution implemented drove tangible changes in culture and organizational climate. The perception of those involved shows that artificial intelligence, when well applied, amplifies human agency and strengthens ties to performance and purpose.
“Today I can dedicate more time to developing the team, based on concrete data. It's a turning point.”
“With faster feedback, I learn more and feel more prepared for calls.”
“We were able to speed up new operator training and improve the team's overall performance in record time.”
Mindset Shift
These statements show a mindset shift: from a reactive model to a more analytical environment oriented toward continuous learning, focused on sustainable performance and valuing people.
Recognition
At Smart Customer 2025, 2clix took the stage alongside HCosta with a case that won Silver in the Customer Experience Automation category — the same AI-based automatic monitoring case presented in this material.
The project was built with a focus on efficiency without losing the human side, showing in practice how smart automation, combined with strategic monitoring, can transform a company's operations and results.
“AI isn't here to replace the human evaluator — it's here to give the team the power of strategic analysis.”
“More than optimizing indicators, this case reinforces the view that intelligence and business knowledge, together, turn operations into sustainable performance.”
