Snapshot Contact Centers QA Benchmark Study – At a Glance
SQM's QA Snapshot Benchmarking Service delivers a fast, low-effort, and high-impact diagnostic of your contact center's QA performance. This one-time assessment reveals how your QA performance stacks up against a database of over 500 contact centers, using key performance indications. Leveraging Generative AI (GenAI) technology, we assess a statistically valid sample of 450 recorded calls over a few weeks to evaluate your center's customer experience (CX) delivery and call compliance adherence against industry benchmarks and top-tier peers.
Since 1996, SQM's Snapshot Contact Center Quality Assurance (QA) Benchmark Study has been the gold standard for evaluating, benchmarking, and enhancing customer satisfaction (CSAT) and first-contact resolution (FCR) in contact centers across phone, chat, and email channels. Participating organizations gain powerful insights into their QA performance relative to industry leaders. Those achieving exceptional results are recognized with the prestigious SQM Contact Center QA Customer Experience of Excellence Award and/or Certification.
GenAI enables detailed performance rankings, gap analysis, and actionable insights to enhance both customer experience and regulatory compliance. Importantly, we enforce a strict zero-transcription data retention policy, and no call data is used for training our AI models.
The QA Scoring Framework
Our approach utilizes a GenAI-driven architecture that delivers better-than-human-level QA scoring while mitigating bias and enhancing consistency across evaluations.
Step-by-Step Process:
1. Input Ingestion & Preprocessing
- Audio Transcription: Speech-to-text applied to call recordings
- Speaker Diarization: Differentiates between agent and customer
- Data Redaction: Sensitive data (e.g., names, credit card info, PHI) is removed
- Text Normalization: Structured transcripts prepared for analysis for GenAI analysis
2. Intent & Behavior Detection
- Natural Language Understanding (NLU): Identifies key intents (e.g., inquiry, resolution)
- Sentiment Analysis: Captures the emotional tone of both parties
- Behavioral Tagging: Detects QA-relevant behaviors like empathy, greeting, active listening
3. Scoring Methodologies
- Rule-Based Logic: Evaluates deterministic metrics (e.g., identity verification)
- Predictive Scoring Using ML/LLMs: Scores complex or subjective elements like empathy or confidence using models trained on thousands of human-scored QA interactions. (YOUR QA DATA IS NOT USED FOR MODELING)
- CSAT Prediction: Proprietary models forecast agent and call center satisfaction with up to 95% accuracy (we recommend all new clients conduct surveys to assess accuracy against QA scores and CSAT predictions).
4. Aggregation & Benchmarking
- Metric Consolidation: Grouped by categories (compliance, soft skills, CX)
- Composite QA Score: Weighted summary of all QA dimensions
- Benchmarking: Performance compared across peers, industry norms, and world class contact centers
Key Benefits
Benchmarking automated quality assurance in a contact center delivers a wide range of benefits that enhance performance, customer satisfaction, and operational efficiency.
- Rapid Deployment, Minimal Disruption: No system integration is required; we start within days and have results within two weeks.
- Third-Party Validation: Gain objective insights to complement or challenge internal and external QA results.
- Actionable Recommendations: Use findings to guide coaching, tech investments, or process improvements.
- Comprehensive Benchmarking: Measure performance across industry verticals (e.g., Banking, Telecom, Healthcare, Insurance) and world-class contact centers in North America.
- Awards & Certifications: Companies that have demonstrated high QA and CSAT results will be awarded and/or certified as World Class companies for CX delivery.