Contact Centre Quality Assurance: The Complete Guide For 2026

Chandler Galt at Zoom shares how to build a QA program that works at scale – from defining standards and building scorecards to using AI to evaluate every interaction, not just a sample.

Contact centre quality assurance is how you find out where quality breaks down – before your customers do. Your agents handle hundreds of interactions a day: some go exceptionally well, and others don’t.

The challenge for many contact centre managers isn’t knowing that quality varies; it’s knowing where, why, and how often before it shows up in your CSAT score.

Contact centre quality assurance provides a structured way to answer those questions. Quality management solutions can help contact centre teams monitor and evaluate agent interactions, identify coaching opportunities, and maintain consistent service standards — all within the same platform where those interactions take place.

What is Contact Centre Quality Assurance?

Contact center quality assurance is a structured process that organizations use to evaluate agent interactions, measure adherence to service standards, and identify opportunities to improve both agent performance and the customer experience.

A QA program typically covers every channel where agents interact with customers — voice, chat, email, and digital. It involves reviewing recorded or live interactions, scoring them against defined criteria, sharing feedback with agents, and using the resulting data to drive coaching and continuous improvement.

Contact center quality management sits within the broader discipline of workforce engagement management (WEM), which also includes workforce management, agent scheduling, and performance reporting.

QA is the feedback engine of that system: it tells you whether your service delivery matches your standards and what to do when it doesn’t.

Well-designed contact center quality assurance programs do three things well:

• Set measurable standards — defining what “good” looks like for each interaction type
• Evaluate consistently — scoring interactions using clear criteria so feedback is fair and actionable
• Close the loop — turning scores into coaching conversations and tracking whether performance improves over time

Key Components of a Contact Centre QA Program

The fundamentals of a QA program are the same whether you’re running a 20-seat support team or a 2,000-seat enterprise contact center, what changes is how you scale each component.

Contact Centre QA Scorecard Best Practices

A QA scorecard is the foundation of every evaluation. It defines the criteria against which agents are scored — typically covering communication quality, process adherence, compliance, problem resolution, and customer empathy. The best scorecards are:

• Specific enough to be actionable — vague criteria like “good communication” don’t tell an agent what to change
• Weighted to reflect business priorities — compliance items often carry more weight than stylistic preferences
• Consistent across evaluators — calibration sessions help QA teams apply scores the same way
• Reviewed regularly — as products, policies, and customer expectations change, your scorecard should too

Most contact centers use more than one scorecard type — for example, separate templates for inbound support calls, billing disputes, and chat interactions — so that evaluation criteria match the nature of the interaction.

Speech Events are a valuable complement to scorecard scoring. Zoom Quality Management can automatically flag interactions that contain silence above a defined threshold, crosstalk, or periods when a customer was placed on hold — giving supervisors a fast way to find interactions worth reviewing without listening to every call.

Sentiment scoring can add another layer of insight. Sentiment analysis tools, such as those within Zoom Quality Management, use AI analysis of conversation transcripts to identify sentiment patterns, rather than factors such as tone, volume, or talk speed.

This means sentiment data reflects the language used within a conversation, not necessarily how it was delivered — providing a useful signal for identifying patterns associated with customer frustration or potential resolution opportunities.

Interaction Analytics and Topic Tracking

Manual QA relies on sampling — reviewing a small percentage of interactions and extrapolating.

Indicators — identified under the Call Outs section — are customizable keywords or phrases that are highlighted within a conversation’s analysis. Indicators can be used to capture critical moments of a conversation or track mentions of a specific competitor, feature, product, or phrase.

Accounts can use indicators to identify specific elements of conversation that are worth reviewing or tracking.

Topics work at a higher level, grouping interactions by subject matter so managers can see trending issues — a spike in billing inquiries, a cluster of complaints about a recent product change, or a shift in what customers are asking about most.

How AI-Powered Quality Assurance Can Support Contact Centres

Many QA tools are available as separate platforms that pull recordings from a contact centre environment and analyse them elsewhere.

Quality management solutions, such as Zoom Quality Management within the Zoom Workforce Engagement Management (WEM) add-on for Zoom Contact Center, allow QA teams to review and evaluate interactions within the same environment where those interactions take place.

A key focus of these solutions is providing deeper insight at the interaction level. For example, some quality management tools can analyse sentiment changes throughout a conversation, allowing users to explore specific moments where sentiment shifts.

These insights may include links to relevant transcript sections and access to the corresponding part of the conversation, helping supervisors review key moments without manually searching through the entire recording.

Automated quality management can extend this further by using AI to evaluate a wider range of customer interactions beyond those selected manually by supervisors.

Scorecards can be automatically assessed, with AI-generated explanations supporting each evaluation, helping teams review results across larger volumes of interactions.

Quality management solutions can also surface agent interaction metrics, such as talk/listen ratio, longest uninterrupted speech, filler word frequency, and talk speed. These metrics can provide additional context for coaching conversations based on recorded interaction data.

Customisable indicators, such as keywords or phrases highlighted during conversation analysis, can help teams identify specific moments within interactions or track mentions of topics such as competitors, features, products, or recurring themes.

When combined with contact centre analytics and customer experience insights, these tools can provide a broader view of patterns across individual interactions and wider team trends.

How to Improve Contact Centre Quality Assurance: A Decision Framework

Building or improving a QA program requires decisions at every layer — from how you define quality to how you use scores to drive change. These steps are written for contact center managers working through that process.

1. Define What “Good” Looks Like Before You Start Scoring

QA programs fail when evaluators score based on instinct rather than criteria. Before evaluating a single interaction, document the service standards agents are held to — communication style, compliance requirements, resolution steps, and escalation protocols.

Make these specific enough that two different evaluators would score the same interaction the same way.

2. Build Scorecards That Match Interaction Types

A single scorecard rarely fits every channel or interaction type. A billing dispute has different compliance requirements than a technical support call.

Map your scorecard categories to the interactions agents actually handle, and weight criteria to reflect what matters most for each type.

3. Calibrate Regularly to Keep Scores Consistent

Score calibration — where QA evaluators score the same interaction independently and then compare results — is one of the most effective ways to prevent evaluator drift.

Schedule monthly calibration sessions, especially when new evaluators join the team or when scorecards are updated.

4. Move Beyond Random Sampling With AI Coverage

Random sampling gives you a snapshot. AI-powered quality assurance for contact centers provides a broader view.

When every interaction is evaluated — not just the ones that happen to be selected — you can identify outliers, coaching opportunities, and compliance gaps that sampling might miss.

Ask any QA platform vendor what percentage of interactions they can evaluate automatically, and how those evaluations are justified.

Key question to ask any vendor: Can your QA tool evaluate interactions automatically, and does it provide a justification for each score — not just the score itself?

5. Use Interaction Data to Prioritize Coaching, Not Just to Document Performance

A QA score is most valuable when it leads to a coaching conversation. Use call center metrics and interaction analytics to identify which agents need coaching on which skills — and bring specific moments from actual interactions into those conversations, rather than speaking in generalities.

6. Track Improvement Over Time, Not Just Point-In-Time Scores

A single scorecard tells you how an agent performed on one interaction. A trend line tells you whether the coaching is working.

Build your QA reporting so that scores are tracked over time per agent, per team, and per scorecard category — so you can see where performance is improving and where it’s stalling.

7. Connect QA Data to Customer Outcomes

The ultimate test of a QA program is whether it correlates with customer satisfaction. Map your QA scores to CSAT, NPS, and first contact resolution data.

If high QA scores aren’t producing better customer outcomes, the scorecard criteria may need revisiting.

8. Review Your QA Framework Against Your Contact Centre Compliance Requirements

Contact center compliance is not a one-time exercise. Regulatory requirements change, and so do internal policies.

Review your QA standards at least quarterly against your compliance obligations, and make sure your scorecard includes mandatory compliance checks — not just service quality criteria.

Contact Center QA in Action

Ongoing agent performance monitoring: Many QA supervisors use interaction analytics and auto-scored evaluations to track agent performance against scorecard criteria across all interactions — not just sampled calls.

Trend data shows whether individual agents are improving over time and flags outliers for targeted coaching.

Compliance monitoring and risk management: For contact centers in regulated industries — financial services, healthcare, insurance — QA provides an audit trail.

Indicators can be configured to flag interactions where required disclosures weren’t made or prohibited language was used, giving compliance teams a searchable record of adherence.

New agent onboarding and ramp-up: New hire QA programs use early scorecard data to identify where agents need additional support before bad habits become ingrained.

Supervisors can pull specific interaction moments — a missed escalation step, an unclear resolution — and use them directly in coaching sessions, shortening the time it takes new agents to reach full competency.

Voice of the customer and trending topics: Topics and sentiment data give operations leaders visibility into what CX data customers are actually talking about — which issues are growing, which resolutions are working, and where service delivery gaps are emerging. This data can feed directly into call center best practices reviews and product or policy feedback loops.

Cross-channel QA consistency: As contact centres handle interactions across voice, chat, and digital channels, QA programs need to evaluate all of them using consistent criteria.

Interaction analytics that works across channels — rather than being limited to voice — gives managers a unified view of service quality regardless of how the customer chose to connect.

This blog post has been re-published by kind permission of Zoom – View the Original Article

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Call Centre Helper is not responsible for the content of these guest blog posts. The opinions expressed in this article are those of the author, and do not necessarily reflect those of Call Centre Helper.

Author: Zoom
Reviewed by: Robyn Coppell