Quality Assurance Score KPI

Quality Assurance Score (QAS) is a critical performance indicator that reflects the effectiveness of quality control processes within an organization.

High QAS values correlate with improved customer satisfaction, reduced defect rates, and enhanced operational efficiency.

Companies leveraging QAS can make data-driven decisions that align with strategic objectives, ultimately driving better financial health.

By embedding quality metrics into management reporting and operational frameworks, organizations can track results and benchmark against industry standards.

A robust QAS not only identifies areas for improvement but also supports forecasting accuracy and variance analysis, enhancing overall business outcomes.

How Quality Assurance Score Connects to Your Strategy

Quality Assurance Score belongs to five KPI groups, and its highest standing is in the Call Center Operations KPI group, where it ranks twenty-fourth of fifty-two. That group leads with Abandon Rate, Customer Satisfaction Score (CSAT), and First Call Resolution (FCR), with Average Handle Time and Service Level close behind. Quality Assurance Score sits well below those headline members, which tells customers it is a diagnostic quality measure rather than a top-line operational gauge: it explains why the leading metrics move rather than being watched first itself.

The KPI also appears in the Customer Feedback KPI group and the Support Ticket Management KPI group, ranking thirty-first of forty-nine and thirty-first of sixty-one respectively. In Customer Feedback the headline co-metrics are Net Promoter Score (NPS), Customer Satisfaction Index, and Customer Complaints; in Support Ticket Management the leaders are Average Resolution Time, First Contact Resolution Rate, and First Response Time. It then surfaces in the Service Quality KPI group at fifty-fourth of fifty-six, led by Customer Satisfaction Score (CSAT) and First Contact Resolution (FCR), and in the Aerospace & Defense KPI group at fifty-third of sixty, led by On-Time Delivery (OTD), Mission Success Rate, and Safety Incident Rate. Across all five, this KPI is a supporting member, not a headline number.

Its balanced scorecard perspective is internal, so it works as a leading process indicator: agent quality graded against defined criteria moves before the lagging outcome metrics that customers report back, such as CSAT and NPS. The genuine tension is with Average Handle Time (AHT), a co-metric in the Call Center Operations KPI group. Pushing handle time down to cut cost pressures agents to close faster, which can erode the careful, criteria-based handling that a high Quality Assurance Score depends on. Reading the two together keeps a speed gain from quietly degrading interaction quality.

Measuring Quality Assurance Score in Practice

The canonical formula divides the sum of quality assurance ratings by the total number of calls evaluated, so the honest version of this KPI lives at the intersection of two data sources: the QA scoring records produced by evaluators or automated grading, and the call log that defines the denominator. The join has to be clean on call identifier and time window, because the denominator is calls evaluated, not calls handled. If evaluators grade a sampled subset, then the denominator must be that same subset, not the full call volume. Mixing an evaluated-sample numerator with a total-volume denominator quietly deflates the score and makes it meaningless for comparison.

Several forks need a decision before anyone measures. First, the scoring criteria and their weights: a compliance-heavy rubric and an empathy-heavy rubric produce different scores from the same call, so the criteria set must be fixed and versioned. Second, sampling: how many calls per agent per period, chosen how, since a biased sample of only escalated or only short calls will not represent the agent. Third, segmentation that actually matters here, which is by agent, by team, by call type, and by tenure, because a blended center-wide score hides the coaching signal that makes this KPI useful in the first place. Because the balanced scorecard perspective is internal, the segmentation should support process improvement, not just reporting.

The instrumentation pitfalls are specific to quality grading. Evaluator drift and inter-rater disagreement mean two people can score the same call differently, so calibration sessions and periodic double-scoring are part of measuring honestly, not optional extras. Automated scoring introduces its own bias when it grades what is easy to detect, such as keyword use, over what matters, such as genuine resolution. And because agents know which calls may be graded, the sampling method has to guard against a rehearsed subset. Track the KPI against evaluation coverage so customers can see whether a rising score reflects real improvement or simply a thinner, kinder sample.

Common Pitfalls

Many organizations misinterpret QAS as a standalone metric, overlooking its interdependencies with other performance indicators.

• Failing to integrate QAS with operational workflows can lead to missed insights. Without real-time data, teams may struggle to identify and address quality issues promptly, impacting customer satisfaction.
• Neglecting to train employees on quality standards results in inconsistent application of processes. This inconsistency can create confusion and increase defect rates, ultimately harming the brand's reputation.
• Overemphasizing quantitative scores without context can distort the understanding of quality. Focusing solely on numbers may mask underlying issues that require qualitative insights for resolution.
• Ignoring customer feedback loops prevents organizations from identifying pain points. Without structured mechanisms to capture and act on complaints, systemic issues persist unnoticed.

Improvement Levers

Enhancing the Quality Assurance Score requires a multifaceted approach that addresses both processes and people.

• Implement regular training sessions to ensure all employees understand quality standards. Continuous education fosters a culture of quality and empowers staff to take ownership of their work.
• Utilize data analytics to identify trends and root causes of defects. By applying quantitative analysis, organizations can pinpoint specific areas for improvement and track progress over time.
• Establish cross-functional teams to review quality processes regularly. Collaborative efforts can uncover insights that drive operational efficiency and improve overall performance.
• Solicit customer feedback to inform quality initiatives. Engaging customers in the process helps organizations align their quality objectives with market expectations.

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Quality Assurance Score Benchmarks

We have 3 relevant benchmarks in our benchmarks database.

Browse the Top Benchmarked KPIs in Call Center Operations

Reading the Benchmarks for Quality Assurance Score

The tracked sources for this metric come from SQM Group, and even a single provider reporting several figures for call center quality can define the underlying measure in more than one way. One figure is presented as a threshold and another as an average, and those are not interchangeable: a threshold describes a bar an operation is expected to clear, while an average describes the center of a distribution. A customer who treats one as the other will misread how demanding the number really is. Before trusting any external quality figure, confirm which of these framings it uses.

The population and scope also shape meaning. SQM Group frames its benchmarking around calls as the unit and a large base of North American call centers, so the figures reflect voice interactions in that region rather than chat, email, or ticket-based support, and rather than operations elsewhere. Quality Assurance Score depends heavily on the scoring rubric behind it: which criteria are graded, how they are weighted, and whether every call or only a sampled subset is evaluated. None of that travels with a headline number. Two centers can report similar scores while grading entirely different behaviors against entirely different scorecards.

Time period is the last quiet trap. The tracked figures carry a publication date, and quality scoring standards drift as rubrics are revised and channels shift. A number that looked representative when it was published may describe a mix of interactions that no longer matches how a given center operates today. The practical takeaway is to distrust any free quality figure that arrives without its definition, its evaluated population, its geography, and its period attached, because those attributes are what let a customer judge whether the comparison is honest at all.

OKRs That Use Quality Assurance Score

Quality Assurance Score works cleanly as a key result under the Call Center Operations objective to enhance contact quality to boost customer satisfaction and loyalty. That objective already gathers quality-facing results such as Call Quality Score and First Call Resolution, and Quality Assurance Score belongs alongside them as the agent-level grading input. A team could frame the key result directionally: lift the quality assurance score on monitored interactions over the quarter while holding first call resolution steady, so the gain reflects better handling rather than shorter calls. Keep any target as the team's own goal, not an external standard.

A second framing draws on the Service Quality objective to optimize service operations to balance cost efficiency with quality delivery. Here Quality Assurance Score is the guardrail key result: as the team drives cost per contact down and pushes service level up, the quality score has to hold or rise, otherwise efficiency is being bought with degraded interactions. Expressed as direction rather than fixed numbers, the aim is to move quality upward while cost per contact moves downward in the same period, which keeps the two co-metrics honest against each other.

See OKR Examples for Call Center Operations

KPI Categories

This KPI is associated with the following categories and industries in our KPI database: