Call quality scoring (QA)
Call quality scoring (QA) A clear explanation for Azerbaijani business — and how Stentor applies it.
What Is Call Quality Scoring (QA)?
Call quality scoring, commonly referred to as contact-centre QA, is the systematic process of evaluating recorded customer conversations against a defined set of criteria. By measuring agent behaviour, compliance adherence, and customer sentiment, businesses can assign a measurable score to each interaction to ensure service standards are met. Traditionally, QA teams were forced to rely on manual sampling, reviewing only a tiny fraction of total calls due to severe time and resource constraints, which often left critical errors or customer frustrations undetected. Modern AI-assisted platforms like Stentor transform this process by eliminating the need for sampling entirely. By transcribing, diarising, and scoring every single conversation automatically, the platform provides Azerbaijani businesses with a complete and objective picture of their customer-service quality. This shift from random checks to 100% coverage allows organisations to identify systemic issues in real-time, ensure total regulatory compliance, and drive agent performance through data-backed insights rather than anecdotal evidence.
Why Call Quality Scoring Matters for Your Business
Total Operational Visibility: Every single call is evaluated, eliminating the blind spots and risks associated with manual sampling.
Elimination of Evaluator Bias: Automated scoring applies identical criteria to every interaction, ensuring consistent standards across the entire team.
Rapid Risk Mitigation: Complaints, negative sentiment, and compliance risks are flagged in near real-time, allowing for immediate intervention.
Evidence-Based Coaching: Supervisors gain access to objective data and specific call moments to guide agent development and training.
Strengthened Regulatory Compliance: A comprehensive, documented audit trail of all scored calls simplifies reporting and dispute resolution.
Optimised for Local Markets: Purpose-built Azerbaijani speech recognition accurately processes the mixed AZ/RU conversations typical of local contact centres.
How Stentor Delivers Call Quality Scoring
100% Call Analysis
Stentor analyses every call — not a random sample — so no problematic interaction goes unnoticed and performance trends reflect the full reality of your operation.
Transcription & Speaker Diarisation
Each recording is automatically transcribed and separated by speaker, giving QA reviewers a clean, readable record of exactly who said what and when.
Hybrid QA Scoring Engine
Scores are produced by combining rule-based logic (e.g. required phrases, forbidden words), semantic AI understanding (intent and context), and human override — balancing automation with expert judgement.
Complaint & Sentiment Detection
The platform automatically detects complaints, negative sentiment, and compliance risk signals within conversations, prioritising the calls that need immediate attention.
Azerbaijani-First Speech Recognition
The underlying speech-to-text engine is purpose-built for Azerbaijani and handles naturally occurring AZ/RU code-switching, ensuring accurate transcripts without manual correction.
Single-Tenant Private Cloud
All data is processed and stored within a dedicated single-tenant environment with no data egress, keeping sensitive customer conversations under your organisation's control.
From Raw Call to Quality Score: The Stentor Process
Frequently Asked Questions About Call Quality Scoring
Does Stentor really score every call, or just a sample?
Stentor analyses 100% of calls. There is no sampling involved; every conversation is transcribed, diarised, and scored to ensure no interaction is missed.
How does the platform handle Azerbaijani and Russian mixed speech?
The speech-to-text engine is purpose-built for Azerbaijani and specifically designed to handle the mixed AZ/RU language patterns common in local contact centres, ensuring high transcript accuracy.
What is hybrid QA scoring and why is it beneficial?
Hybrid QA scoring combines three layers: rule-based checks for specific phrases, semantic AI for context and intent, and human override for expert judgement. This ensures the system is both consistent and flexible.
Where is our call data stored and how is it secured?
Stentor utilizes a single-tenant private cloud architecture with no data egress. Your data is stored in a dedicated environment and never flows to shared infrastructure or third-party systems.
Can supervisors manually adjust an automated score?
Yes. The hybrid model explicitly supports human override, allowing QA specialists to review any call and adjust the score based on nuanced context that the AI may not fully capture.
Ready to Score Every Call — Not Just a Sample?
See how Stentor's hybrid QA scoring can give your team complete visibility into call quality, compliance risk, and customer sentiment across every conversation in your contact centre.
Request a demo