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Customer Experience

Measuring Contact-Centre Quality beyond Handling Times

By KaperX Editorial Team7 min read

Why handling times are not enough

Contact centres have long been managed on productivity: speed of answer, abandoned call rate, average handling time (AHT). These indicators measure the centre's capacity to absorb volume. They do not say whether the customer got what they were looking for.

Supervisors know the trap: an AHT target that is too tight pushes the agent to shorten the call, transfer the difficult case or promise a callback. The customer calls back, volume rises, average AHT goes up again and the centre concludes that it is understaffed. To break out of this cycle, you need indicators that measure outcomes. It is also the precondition for selling higher-value services, as our guide on repositioning a contact centre explains.

First contact resolution

First contact resolution (FCR) is the share of requests settled without the customer having to come back. It is measured in two ways, which should be combined:

  • declared: the customer is asked, after the conversation, whether their request has been settled;
  • behavioural: you check that they do not contact you again for the same reason within a window set in advance (seven days, for example), across all channels.

The gap between the two is revealing. A resolution declared by the agent or the customer, then contradicted by a repeat contact, signals a problem of diagnosis, procedure or information.

Repeat contacts, transfers and complaints

  • Repeat contact rate: the share of customers who come back for the same reason. It is the flip side of FCR and often a centre's first hidden cost.
  • Transfer rate: the share of conversations passed to another agent or department. A high rate reveals unsuitable routing, decision rights that are too limited or missing skills.
  • Complaint rate: complaints relative to the number of contacts. It measures the failures the customer considers serious enough to formalise. Our guide on complaint management explains how to trace these cases back to their causes.

These three indicators are behavioural signals: they reflect what customers do, not just what they say. The guide on behavioural signals places them within a broader listening system.

Customer effort and surveys

CES measures the perceived effort needed to settle a request; CSAT, satisfaction with the conversation. How they work is explained in our guide on NPS, CSAT and CES. Two precautions for a contact centre:

  • Satisfaction scores are almost always concentrated at the top of the scale (Peterson and Wilson, 1992), and surveys administered by telephone tend to produce more positive answers than written questionnaires. The guide on courtesy bias details these effects.
  • In the study by De Haan, Verhoef and Wiesel (2015), conducted with a Dutch panel covering 93 companies, no declared-feedback indicator strongly predicted retention; CES had little or no predictive power. A survey complements behavioural measures; it does not replace them.

Quality assessment of conversations

Quality assessment consists of listening to or rereading a sample of conversations and scoring them against a scorecard. A useful scorecard:

  • distinguishes critical criteria (wrong information, personal data disclosed, unauthorised commitment) from skill criteria (diagnosis, clarity, rephrasing);
  • assesses the outcome for the customer (has the request been settled?) as much as adherence to the script;
  • is the subject of calibration sessions, in which several assessors score the same conversation to align their judgements;
  • feeds individual coaching, not just a ranking.

Recording and listening to calls are processing of personal data: in Morocco, Law 09-08 requires individuals to be informed and the corresponding CNDP formality to be completed. See our CNDP compliance method.

Speech analytics and AI: what the AI Act allows

Automated analysis tools transcribe conversations, classify reasons, spot keywords and can suggest a quality score. For a centre serving European clients, the AI Act draws precise limits.

UseStatus under the AI ActSince / from
Transcription and classification of contact reasonsNo prohibition; general rules—
Sentiment analysis of written textOutside the concept of emotion recognition, which relies on biometric data—
Inferring agents' emotions from their voice or faceProhibited in the workplace, except for medical or safety reasons (Article 5)2 February 2025
Inferring customers' emotions from their voiceNot prohibited; people exposed must be informed (Article 50)2 August 2026
Same use, high-risk regime (Annex III)Deployer obligations: human oversight, logs, information2 December 2027
AI that assesses agents' performance or behaviourHigh risk (Annex III, point 4); prior information of staff representatives and the employees concerned2 December 2027

The detail is in our guide on emotion analysis in call centres. For complaints, see also the safeguards specific to AI applied to complaints.

A balanced dashboard

IndicatorFormulaUsePitfall to avoid
First contact resolutionRequests with no repeat contact for the same reason within the window ÷ requests handledOverall quality, managing the centreWindow too short, reasons poorly coded
Repeat contact rateCustomers who came back for the same reason ÷ customers who made contactSpotting causes not dealt withIgnoring other channels
Transfer rateConversations transferred ÷ conversations handledRouting, decision rights, trainingPenalising an agent who transfers appropriately
Complaint rateComplaints ÷ contacts handledSerious failures, regulatory riskDiscouraging the logging of complaints
Customer effort (CES)Average of responses on the effort scaleSimplifying journeysSample too small
Quality scorePoints scored ÷ points available on the scorecardCoaching, complianceScorecard centred on the script
Average handling timeTalk, hold and after-call work time ÷ conversationsStaff planningMaking it an individual target

Read these indicators together: a fall in AHT accompanied by a rise in repeat contacts is not progress.

Putting it in place in six steps

  1. Code contact reasons consistently across all channels.
  2. Choose the repeat contact window and measure baseline behavioural FCR.
  3. Revise the quality scorecard and hold a first calibration session.
  4. Remove AHT from individual targets and reserve it for planning.
  5. Check every automated analysis tool against the AI Act and Law 09-08.
  6. Present the dashboard every month, with the three main causes of repeat contact and the actions under way.

Further reading

Frequently asked questions

What is the most important quality indicator for a contact centre?

The first contact resolution rate is often the best starting point, because it links the quality the customer perceives, the effort they put in and the cost to the business. It should, however, be read alongside the repeat contact rate, which reveals resolutions that were declared but not real.

Should average handling time be abandoned?

No, but it should be used to plan staffing, not to assess agents. Used as an individual target, it pushes agents to cut calls short and transfer difficult cases, which drives up repeat contacts and complaints.

Does the AI Act allow automated call analysis?

Analysing the content of conversations, such as transcribing and classifying contact reasons, is not prohibited. Inferring employees' emotions from their voice has been prohibited since 2 February 2025. Inferring customers' emotions is not prohibited, but they must be informed since 2 August 2026, and it falls under the high-risk regime from 2 December 2027.

How can first contact resolution be measured without a survey?

By observing the customer's behaviour: if they do not contact the business again for the same reason within a defined window, for example seven days, the contact is considered resolved. This measure requires contact reasons to be coded consistently.

Is NPS enough to manage call-centre quality?

No. NPS measures an overall intention to recommend, influenced by many factors other than customer service. A Dutch study by De Haan, Verhoef and Wiesel (2015) also found a weak link between NPS and retention, barely different from that of a simple satisfaction measure.

General information, not legal advice.

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