Explore fresh, expert perspectives on customer engagement and innovation

This partnership brings together two innovators focused on transforming customer experience and operational efficiency for contact centres and enterprise teams worldwide.

Invosys has built a reputation for delivering comprehensive technology solutions that enable SMB organisations to streamline communications, accelerate digital transformation, and enhance customer and workforce experiences. From unified communications and telephony to full-featured CCaaS platforms, Invosys Chorus solution helps businesses modernise how they connect, collaborate, and serve customers across channels.

MaxContact empowers contact centres and customer-facing teams with an AI-driven engagement platform designed to turn conversations into measurable business outcomes. With capabilities such as predictive dialling, omnichannel engagement, intelligent routing, and autonomous AI agents, MaxContact enables organisations to scale efficiently while enhancing revenue generation and customer satisfaction.

Through this partnership, Invosys will integrate MaxContact’s AI-driven contact centre capabilities into its portfolio, giving customers a simpler way to combine intelligent engagement with Invosys' secure cloud communications. Together, the two companies will support organisations looking to elevate sales performance, contact centre productivity and customer experience with reliable, cutting-edge technology.

“We’re thrilled to partner with MaxContact to bring even greater capabilities to our customers,” said Jane Anderson, CEO of Invosys. “By combining Invosys’ trusted Chorus communications platform with MaxContact’s AI-driven engagement technology, organisations will be able to deliver more personalised, efficient, and impactful interactions at every touchpoint.”

MaxContact’s leadership echoed the enthusiasm for the collaboration:

“This partnership with Invosys marks a significant step forward in how we help businesses transform their customer engagement,” said Ben Booth, CEO at MaxContact. “Together, we’re giving customers access to a seamless integration of powerful communications and AI-enabled contact centre solutions, helping teams work smarter, handle more conversations and deliver better outcomes for customers and the business.

The Invosys–MaxContact partnership reinforces both companies’ commitment to innovation, scalability and customer success. Organisations leveraging this combined technology stack can look forward to enhanced performance, deeper insights into customer interactions, and a stronger foundation for long-term CX improvement.

For more information about how Invosys and MaxContact are working together to deliver advanced contact centre solutions, contact our team. 

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We say theoretically, because there’s a caveat here. Reducing AHT mustn’t happen at the expense of service. Rushing calls simply to improve AHT is a recipe for dissatisfaction and, ultimately, unhappy customers.

That’s why modern approaches to AHT reduction increasingly rely on AI Agents, AI Chatbots and intelligent call routing, rather than pressuring (already stretched) agents to work faster.

In the rest of this blog, we’ll define what average handle time is and how it’s calculated. And we’ll also share strategies for reducing average handling time while maintaining or even improving customer satisfaction (CSAT).

What is Average Handle Time (AHT)?

Average Handle Time (AHT) measures the average duration of a single customer interaction. It accounts for total talk time, hold time and after-call work (ACW) divided by the number of calls handled.

Talk time: The total time that agents spend talking to customers.

Hold time: Time customers spend waiting for an agent to deal with their issue(s).

After-call time: The time spent on tasks, such as making notes, sending emails, or categorising the conversation. These are tasks that a call centre agent has to do before handling another call.

Average Handle Time formula:

AHT = (Total Talk Time + Total Hold Time + Total After-Call Work Time) ÷ Number of Calls Handled

What’s considered a good AHT depends to some extent on the industry you’re in. Call Centre Helper’s Erlang calculator lets you enter specific metrics to work out your own AHT, but according to its own example, an AHT of 6m 10s is reasonable.

According to our latest Benchmark Report, around 44% of our respondents reported times between 6 and 9 minutes.

Why is reducing AHT important?

As a general rule, the lower your AHT, the better. It means you can handle more calls, improve efficiency and reduce costs.

AHT also gives you the information to improve resource management, and to help agents improve performance. Taken together, it is one of the key metrics of any call centre operation.

Lowering your Average Handle Time can lead to:

• Increased efficiency, so you can handle more calls with the same number of agents.
• Cost reduction, so you save on operational costs by optimising agent time.‍
• Improved customer satisfaction due to faster resolutions but only if quality is maintained.

Why is reducing AHT difficult?

There are a few common challenges that stop call centres from achieving lower Average Handling Times.

Complex customer issues

Naturally, some customer enquiries take more time to resolve than others, increasing handling time. These complex issues might include technical difficulties, multiple queries or sensitive situations. In these scenarios, focus on delivering a thorough and effective service over minimising call time.

Outdated systems and procedures

Trying to reduce AHT in a call centre that has inefficient processes and outdated systems is never going to go well. Outdated systems that respond slowly or crash frequently mean agents wait for screens to load or systems to reboot. Lack of integration between platforms can also mean switching between platforms to gather information, which takes extra time during calls.

Complicated workflows and manual tasks that could be automated result in more time spent on simple interactions. Without AI-enabled workflows, agents are forced to handle authentication, basic queries and admin tasks manually.

Overcoming agent knowledge gaps

When call agents lack product knowledge, communication skills and familiarity with internal processes, it inevitably leads to longer call durations as agents spend more time finding information, hesitate during conversations, or place customers on hold to seek support.

Inexperienced agents might mishandle calls and give incorrect information, or fail to resolve issues on the first attempt. This leads to repeat contacts that further inflate AHT.

Balancing AHT with customer satisfaction

You should never measure AHT in silo. A focus on call times at the expense of other indicators can certainly lead to a low AHT, but also crash customer satisfaction ratings. Agents should never be incentivised to end calls prematurely or rush through conversations.

‍Agents who feel pressured to end calls quickly are more likely to make mistakes or give bad advice. When that happens, another key call centre metric (first call resolution (FCR) rates) also suffers.

‍But,AHT is important and, if you do need to bring it down, there are ways of doing so that won’t undermine the experience of your customers.

‍And this is where modern contact centre technology starts to change the picture.

How AI-powered contact centre software changes the way AHT is reduced

AI-powered contact centre solutions reduce average handle time without rushing conversations or compromising service quality. Here’s how AI features can influence the customer journey:

AI Agents can handle authentication, intent capture and simple issue resolution before a call reaches a human agent. This reduces talk time.

• AI Chatbots can be a credible option to resolve routine queries digitally, reducing unnecessary calls altogether.
• Conversation Analytics can be used to analyse call recordings and pinpoint effective call handling techniques. Understanding what works and what doesn’t in different scenarios and incorporating those learnings into agent training reduces average call handling time.

6 practical ways  to reduce Average Handling Time in your call centre

1. Remove avoidable call handle time with AI Agents and AI Chatbots

A big driver of high AHT is unnecessary calls reaching agents in the first place.

AI Chatbots and AI Agents can combat this by handling high-volume, predictable interactions end-to-end. Things like identity checks, balance queries, appointment changes or payment prompts, for example. Customers get instant answers, and agents aren’t stuck dealing with the same repetitive routine requests.

2. Get customers to the right place first time

AHT quickly increases when calls are transferred or if agents have to spend the first few minutes determining what the customer actually needs.

Intelligent contact strategies use intent and context to direct each interaction to the right destination, whether that’s an AI Agent, a chatbot or a specialist human agent. When customers arrive in the right place with the right information already captured, conversations are generally shorter and smoother.

Plus, less time spent re-explaining means more time spent resolving.

3. Use workforce management to reduce avoidable wait time

Average Handle Time is affected by how well contact centres are staffed throughout the day.

By analysing demand patterns, Workforce Management (WFM) ensures the right number of agents are available at the right times. When staffing levels reflect actual call volumes, customers spend less time waiting in queues, and agents aren’t put under unnecessary pressure.

When teams are overwhelmed, calls are longer, hold time increases, and call resolution is slower.

Overstaffing, on the other hand, drives up your overheads without improving outcomes.

By planning resources accurately, contact centres can reduce queue time and keep Average Handle Time under control without increasing headcount or paying for hours they don’t need.

4. Use conversation analytics to understand why calls are running long

If AHT is rising, contact centre leaders should understand why before making moves to try to fix it.

Conversation Analytics and Auto QA make it easier to see where time is being lost. You can spot common points of confusion, repeated questions, policy explanations that take too long, or processes that regularly slow conversations down.

Instead of guessing or pushing agents harder, teams can focus on addressing the root causes of long calls.

5. Combine data with agent feedback to remove friction

Agents are often the first to notice what’s slowing calls down, from unclear processes and missing information to repetitive questions.

When agent feedback is combined with insights from conversation analytics, the learnings become much more actionable. Patterns can be confirmed, call scripts refined and workflows simplified.

Improvements based on real experience, rather than assumptions, are far more effective.

6. Set realistic and balanced KPIs

AHT is an important metric to monitor, but it shouldn't be the only focus. Balance it with other key performance indicators (KPIs) such as First Call Resolution (FCR) and Customer Satisfaction Score (CSAT).

How MaxContact can help

Reducing Average Handle Time consistently comes down to how well your contact centre is set up to support agents and customers through each interaction.

MaxContact helps remove some of the friction that typically slows calls down. AI Agents and AI Chatbots take care of routine interactions and capture useful context early, while features like IVR, intelligent routing and workforce management help customers reach the right place without unnecessary delays.

Alongside this, reporting and conversation analytics give teams a clearer view of where handling time is being lost.

This helps contact centres bring Average Handle Time down in a way that feels sustainable: without rushing agents, adding headcount or compromising the customer experience.

If AHT is something you’re actively trying to improve, it’s worth looking at how the right contact centre technology can support that effort.

Explore MaxContact’s AI-powered contact centre solutions.

In our January product webinar, we shared MaxContact's vision for 2026 and the roadmap that will help businesses turn every customer conversation into revenue-driving outcomes. Led by Kayleigh Tait, Marketing Director, and Conor Bowler, Principal Product Manager, the session revealed how we're evolving our platform to address the challenges contact centres face today.

The Challenges Driving Our Roadmap

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Three clear themes dominate conversations with customers across every sector we support:

Costs and customer expectations are rising faster than teams can keep up. Contact centres deal with higher expectations, more channels, and greater variability in customer behaviour. The volume of complex interactions continues to increase as routine queries shift to automation.

Data and insight remain fragmented. When information sits in disconnected systems, fixing problems becomes guesswork. Teams need unified visibility to make confident decisions in real time.

Organisations know AI can help but don't know where to start. The gap between AI adoption intentions and actual implementation remains significant. Businesses need clear, practical pathways to AI deployment with proven ROI.

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Our Product Vision: Maximising Every Moment

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MaxContact's 2026 roadmap centres on three interconnected pillars that work together to deliver smarter contact strategies:

Intelligent Automation: AI handles routine, high-volume interactions automatically, allowing human agents to focus on conversations that require empathy, judgement, and relationship-building. This includes both voice and digital AI agents that can manage everything from FAQs to payment arrangements.

Smart Operations: Workflow automation, real-time agent assistance, and predictive routing ensure teams operate at peak efficiency. We're building capabilities that reduce manual effort, eliminate context-switching, and help agents deliver better outcomes in every interaction.

Connected Insight: Conversation analytics, quality management, and unified reporting transform customer conversations into clear, actionable insight. Teams can understand what's driving performance, identify compliance risks, and make data-backed decisions across the entire operation.

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2026 Roadmap Highlights

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Q1 2026: Foundation and Enhancement

The year begins with significant updates to our core capabilities. AI Agent functionality expands to chatbot channels, enabling businesses to automate digital conversations with the same sophistication they've experienced with voice agents. Conversation analytics introduces custom scorecards, allowing teams to measure what matters most to their specific operations.

AI Assist Notes delivers quick post call notes cuts down after call admin, whilst enhanced dashboard manager gives teams clearer visibility into performance.

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Q2 2026: Real-Time Assist and Advanced Routing

The new Interaction Routing  capabilities allow sophisticated inbound flow management, moving interactions between queues based on real-time conditions.

Real-time agent assist features provide agents with instant guidance, next-best-action recommendations, and contextual information during live conversations.

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Q3 2026: Predictive Intelligence and Quality Automation

The third quarter introduces behavioural driven workflows that responds to signals and customer context. Further quality management automation reduces the manual effort required for call scoring and compliance monitoring whilst improving accuracy and consistency.

Portfolio integration brings all products—Contact Centre, Conversation Analytics, AI Agents, and AI Chatbot—into a single view, providing business-wide insight into customer engagement performance.

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Q4 2026: Agentic AI and Self-Optimising Systems

The final quarter of 2026 begins to deliver the most transformative capabilities. Agentic AI orchestration enables AI agents to work together, handling complex, multi-step processes and hand over to a person where required.

Self-optimising workflows (in development in Q4 2026 and into 2027) use machine learning to continuously improve processes based on outcomes, reducing the need for manual tuning.

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Built for Real-World Impact

Every roadmap item addresses a specific customer challenge. The AI agent features, for example, solve the pressure sales and collections teams face to hit outcomes with fewer resources. The conversation analytics enhancements help teams move beyond guesswork when diagnosing performance issues.

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Design Partner Programme: Shape What's Next

MaxContact is actively seeking design partners who want early access to new features and the opportunity to influence product development. Design partners receive priority availability, direct access to the product team, and the chance to solve their specific challenges with cutting-edge capabilities before general release.

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A Platform That Evolves with You

The 2026 roadmap reflects months of listening to customers, analysing industry trends through research like the Voice of Consumer Report and the annual Benchmark Report, and identifying the capabilities businesses need next.

MaxContact is now a multi-product company—Contact Centre, Conversation Analytics, AI Agents, and AI Chatbot—but it's all one connected platform. The roadmap ensures these capabilities work together seamlessly, supporting smarter contact strategies that drive measurable business outcomes.

Whether your priority is reducing costs, improving customer experience, scaling operations, or ensuring compliance, the 2026 roadmap provides a clear path forward.

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Call centre efficiency isn’t just about doing more with less - it’s about consistently delivering high-quality service while optimising resources. In this blog, we’ll explore how call centre metrics and KPIs are used to measure contact centre performance, the metrics that matter most, and how your call centre can overcome common obstacles to thrive in a competitive industry.

How to measure call centre performance & efficiency

Efficiency in a contact centre can look very different depending on the industry you serve. A sales-driven BPO will measure success differently than a customer service team in retail. But across all sectors, efficiency is defined by one universal goal: delivering excellent service with minimal resources.

This means running a contact centre built on optimised operations, supported by a well-trained, motivated team. Achieving this balance requires focusing on four key pillars:

1. Operational performance: Efficient processes, accurate resource allocation, and adaptability to fluctuating demands ensure your contact centre runs smoothly.
2. Customer experience: Quick, effective, and empathetic service builds loyalty and enhances your brand.
3. Agent productivity: Empowering agents with the right tools and training helps them handle calls effectively while avoiding burnout.

Cost management: Reducing waste through automation and optimising resource use ensures profitability without compromising quality.

Which call centre metrics and KPIs measure performance and efficiency?

The KPIs you choose to measure and track will depend on your contact centre’s focus, whether it’s customer service, outbound sales, or debt collection. However, there are common call centre metrics and KPIs that apply across most operations, as they provide insight into operational performance, customer satisfaction, and agent productivity.

According to our 2025/26 UK Contact Centre KPI Benchmarking Insights Report, the KPIs contact centres most commonly prioritise reflect a balance of customer experience, responsiveness, and operational performance.

The most selected metrics were customer satisfaction (48%), speed of answer (35%), service level achievement (34%), conversion rate (33%), and first call resolution (33%).

While priorities vary by operation, the following KPIs consistently play a central role in measuring overall contact centre efficiency.

1. Average Handle Time (AHT)

AHT measures the average time an agent spends on a call, including hold time and after-call work. It indicates how efficiently customer interactions are handled.

Average handle time varies depending on the type of contact centre. In our 2025/26 benchmark report, the mean inbound AHT was 8 minutes, with outbound operations reporting a similar average.

While a high AHT might indicate inefficiency, it’s not always negative. Agents may need more time to resolve complex or sensitive queries, which can boost customer satisfaction in the long term. In customer care and technical support, over a third of respondents reported higher AHT (10–15 minutes), reflecting the complexity of support queries.

‍Balancing AHT is key - focus on resolving issues thoroughly without rushing customers.

2. Quality Assurance (QA) Score

QA Score measures the quality and consistency of agent interactions, including compliance and customer experience standards.

In the 2025/26 benchmarking report, 29% of decision makers selected compliance scores as one of their most important KPIs, reinforcing that quality and adherence remain central to efficient performance.

Strong QA processes support efficiency by reducing repeat contacts, minimising compliance risk, and improving first-contact outcomes.

High QA scores indicate that agents are meeting both regulatory and customer expectations, building trust and loyalty.

Regular analysis of QA results can uncover coaching opportunities and refine scripts to drive consistent performance.

3.  Customer Satisfaction (CSAT)

CSAT measures how satisfied customers are with their interaction, which is typically gathered through post-call surveys.

In our benchmarking report, customer satisfaction scores were the most selected KPI overall, prioritised by 48% of respondents.

High CSAT scores show that agents are meeting customer needs effectively, but speed doesn’t always equal satisfaction. A personalised and thorough approach is often more impactful than a quick, impersonal resolution.

4. First Contact Resolution (FCR)

FCR measures the percentage of customer issues that are resolved during the first interaction, without the need for follow-ups or escalations.

For inbound customer care and technical support teams, the mean FCR is 41%. While performance varies, 27% of respondents reported inbound FCR levels between 50% and 79%, showing what’s achievable for well-optimised teams.

A strong FCR not only improves customer loyalty but also reduces operational costs by minimising repeat calls. If your FCR is low, assess whether your agents have the tools, training, and support to resolve queries on the first attempt.

Still not decided which other call centre performance metrics to track? Take a look at our guide to call centre reporting metrics and KPIs.

Benchmarking call centre efficiency: Where to begin

To measure the efficiency of your call centre, it's important to benchmark performance so that you can identify opportunities for improvement.

Using AI-driven QA and analytics tools can help you monitor key call centre metrics against industry standards, competitors, or past performance, and make it easier to uncover insights that will drive operational success.

For outbound teams specifically, using purpose-built tools like MaxContact’s outbound engagement solution can help you track and optimise key outbound call centre metrics, such as contact rates, conversion rates, and calls-to-success.

1. Collect the right data

• Use advanced call centre software to track specific KPIs (AHT, FCR, CSAT)
• Segment data by channel, team, or call type to identify trends.

2. Compare performance

• Benchmark metrics against industry standards, competitors or past performance.
• Analyse differences between teams, shifts, or channels to uncover strengths and weaknesses.

3. Set realistic goals

• Align targets with business objectives and Service Level Agreements (SLAs)
• Prioritise actions that balance efficiency with quality.

4. Monitor and adapt continuously

• Use performance analytic dashboards to track metrics in real time.
• Regularly review benchmarks to meet changing customer expectations.

How do you compare?

Gain insight into how your performance measures up and download our Benchmark Report.

What stalls contact centre performance?

Even with the right metrics in place, contact centres face common challenges that can hinder efficiency. Here are some of the pitfalls to watch out for. Learn how it impacts performance and how to overcome it

1. Outdated & unreliable technology

Does your contact centre rely on legacy systems? Do you struggle with limited integration capabilities and slow performance?

While it can be tempting to push on with legacy systems, it’s important to recognise that outdated technology lacks advanced features like AI-driven analytics and real-time reporting. As new technology evolves, your legacy tech will soon have you falling behind competitors who stay up to date.

‍The impact

• Your Average Handle Time remains high due to slow systems and limited customer information access.
• You struggle to improve your poor CSAT as customers consistently experience delays.
• Your legacy system's limited reporting capability doesn't give you the depth of insights needed for decision-making.

Learn how Compare My Insurance improved call centre performance metrics after replacing an unreliable dialler system.

2. Manual processes & inefficient operations

Do you frequently question why your call agents aren’t as productive as you’d hoped? Perhaps you’ve noticed that your call team always seems busy but aren’t delivering quick and efficient call outcomes?

If your contact centre is operating with outdated workflows and ineffective call routing methods, it leads to inconsistent customer service.

Another aspect that damages productivity, is when call centre agents spend too much time completing manual tasks, such as dialling and post-call updates.

‍The impact

• Your FCR reduces as your call agents struggle to resolve queries efficiently.
• Lack of utilised resources and poor operations lead to frustrated customers and higher call abandonment rates.
• You continuously waste money and resources on redundant processes.

See how D2MS improved outbound call centre metrics using MaxContact’s auto-dialler and reporting tools.

3. Training and development gaps

Be honest. Does your call centre overemphasise system training? Do you have a big enough focus on soft skills like conflict resolution?

If agent training in your contact centre is generic and sporadic, the likelihood of development gaps becomes a risk.

‍The impact

• Overall, agent performance is inconsistent and incidents of non-compliance increase.
• Your call agents feel unsupported in skill development, which leads to retention issues.

Discover how Honey Group improved call centre performance and QA metrics using speech analytics.

4. Poor workforce management

For many contact centres, effectively managing the workforce is a struggle. Do you frequently find that your call centre is under-resourced during peak times? Or are there periods of time where your call centre is over-staffed and call agents are idle?

If the answer is yes, then you have fallen into the trap of inaccurate forecasting and inefficient scheduling.

‍The impact

• Your CSAT is poor due to stretched resources and agent fatigue.
• Your contact centre experiences high agent turnover rates, which drives up recruitment and training costs. This pressure is reflected in our latest benchmark data: 53% of respondents said agent workloads have increased over the last year, and mean annual agent turnover sits at 31%.

Modern workforce management tools can help balance workloads and optimise resource use.

MaxContact: Your partner in efficiency

Modern contact centre software is the backbone of operational excellence. MaxContact’s solutions are designed to help teams improve call centre metrics, performance, and customer outcomes:

• Intelligent call routing: Skills-based routing connects customers to the most qualified agents, improving FCR and reducing AHT.
• Real-time analytics: Performance dashboards provide call centre leaders with instant insights, helping them address inefficiencies and optimise resources.
• AI speech analytics: Automatically transcribe speech to text, speeding up QA processes and improving agent performance with data-led feedback.
• Predictive analytics: Anticipates customer needs, refines scripts, and helps overcome objections for better outcomes.

Efficient call centres aren’t built overnight. But with the right tools, strategies, and benchmarks, they’re within reach. Discover how MaxContact can help you boost efficiency, enhance customer satisfaction and future-proof your operations.

Book a Demo

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We’ve compiled an easy-to-follow cheatsheet of metrics you should care about across four key areas to help you stay focused.

• Customer experience
• Agent productivity
• Call initiation
• Call centre operations

While tracking and acting on these metrics is a good place to start, they are only useful when they are measured in context.

Insights from our latest 2025-26 UK benchmarking report show that the highest-performing contact centres consistently outperform the average across multiple KPIs, reinforcing the importance of tracking the right metrics together rather than in isolation.

If you’re looking for a broader view of performance beyond individual KPIs, our guide on how to measure call centre efficiency explores how these metrics work together to drive overall effectiveness.

1. Customer experience metrics and KPIs

Metrics that measure customer satisfaction, loyalty and ease of service.

Customer Satisfaction Score (CSAT)

What is it? CSAT Measures customer satisfaction with a product, service, or interaction.
Why does it matter? It indicates overall customer happiness and loyalty.
Top tip: Use post-interaction surveys to gather feedback and address negative responses quickly.

How to calculate Customer Satisfaction Score (CSAT)
CSAT = (Positive Responses/Total Responses) x 100

CSAT is the most commonly prioritised KPI in UK contact centres. However, it’s crucial to note that it is most effective when it’s tracked alongside other metrics, such as first contact resolution and speed of answer.

Net Promoter Score (NPS)

What is it? NPS measures customer loyalty by asking customers, ‘How likely are you to recommend us?’
Why does it matter? NPS strongly correlates with long-term customer retention.
Top tip: Use follow-up questions to understand the pain points of detractors and convert them into promoters.

How to calculate Net Promoter Score (NPS)
NPS = %Promoters − %Detractors

First Contact Resolution (FCR)

What is it? First Contact Resolution (FCR) is the percentage of issues resolved during the first interaction with a call agent.
Why does it matter? Higher FCR usually has a positive impact on customer satisfaction and reduces repeat calls, resulting in less frustration.

How to calculate First Contact Resolution (FCR)
FCR = (Issues Resolved on First Contact/Total Issues)×100

UK contact centres report an average inbound FCR of around 41%, while over a quarter achieve rates above 50%. This highlights that there is usually a significant performance gap between average and top-performing teams.

First Response Time (FRT)

What is it? First Response Time (FRT) is the average time it takes to respond to a customer’s initial contact.
Why does it matter? The faster your responses, the higher your customer satisfaction scores will be.

How to calculate First Response Time (FRT)
FRT = Total Number of Tickets Responded To/Total Time to First Response for All Tickets

Customer Effort Score (CES)

What is it? Customer Effort Score (CES) measures how much effort it takes a customer to resolve their issue.
Why does it matter? The less effort a customer has to put in, the higher the correlation between satisfaction and loyalty.

How to calculate Customer Effort Score (CES)
CES=Total Number of Responses/ Sum of All Customer Effort Scores

Repeat Call Rate

What is it? Repeat Call Rate is the percentage of customers who call back about unresolved issues.
Why does it matter? A high Repeat Call Rate indicates gaps in problem resolution that could be addressed with agent training.

How to calculate Repeat Call Rate (RCR)
RCR=Total Calls Handled/Number of Repeat Calls×100

Script Adherence Rate

What is it? Script Adherence Rate is the percentage of calls where call agents have followed the approved script.
Why does it matter? It makes sure communication is consistent and regulatory compliant.

How to calculate Script Adherence Rate
Script Adherence Rate (%)= Total Number of Calls Evaluated/Number of Calls Where the Script Was Followed×100

Customer Lifetime Value (CLTV)

What is it? CLTV is the overall revenue a customer is expected to generate during their relationship with the business.
Why does it matter? It helps to prioritise high-value customer interactions and enables more experienced agents to handle those calls.

How to calculate Customer Lifetime Value (CLTV)
CLTV=Average Purchase Value×Average Purchase Frequency×Customer Lifespan

Revenue Per Call (RPC)

What is it? RPC measures revenue generated per call.
Why does it matter? RPC assesses the profitability of call centre operations.

How to calculate Revenue Per Call (RPC)
RPC=Total Number of Calls Handled/Total Revenue Generated

For outbound-focused teams, using metrics like RPC effectively depends on how well data is captured, analysed and subsequently acted on. This is a topic we explore further in 'Is your outbound sales team truly data driven?’

2. Agent productivity metrics

Metrics that provide insight into the performance of call centre teams and individual agents, highlighting strengths and areas for improvement through training.

-Average Handle Time (AHT)

What is it? AHT measures the total time spent on a call and includes talk, hold and wrap-up time.
Why does it matter? AHT can help identify if agents are effectively balancing efficiency and customer satisfaction.

How to calculate Average Handle Time (AHT)
AHT = Talk Time + Hold Time + After-Call Work/Total Calls Handled

Average handle time will always vary depending on call type. UK contact centres report that outbound calls average just over 8 minutes, with inbound support calls tracking slightly under that.

Average Talk Time (ATT)

What is it? ATT tracks the time agents spend actively speaking with customers.
Why does it matter? It indicates efficiency and the complexity of customer issues while providing more context to Average Handle Time.

How to calculate Average Talk Time (ATT)
ATT=Total Number of Calls Handled/Total Talk Time

Quality Assurance (QA) Score

What is it? Quality Assurance Score measures how well a call agent meets the defined quality of service, comparing an agent’s interaction against predefined scorecards.
Why does it matter? Monitoring QA ensures consistency and alignment with industry standards. Analysing quality scores across call agents can identify training needs.

How to calculate Quality Assurance Score (QA)
QA Score (%)=Total Points Available/Total Points Achieved×100

Agent Utilisation Rate

What is it? Agent Utilisation Rate calculates the percentage of an agent’s working time spent handling calls.
Why does it matter? It provides an overview of workload across call teams to prevent burnout.

How to calculate Agent Utilisation Rate
Agent Utilisation Rate (%)=Total Working Time/Time Spent on Productive Activities×100

Agent Utilisation Rate is becoming increasingly important for contact centres, with over half reporting that agent workloads have increased. This puts significant pressure on productivity and wellbeing.

Schedule Adherence Rate

What is it? Schedule Adherence Rate measures how closely agents stick to their schedules.
Why does it matter? It helps to make sure there is sufficient call agent coverage during peak times.

How to calculate Schedule Adherence Rate
Schedule Adherence Rate (%)=Total Scheduled Time/Time Spent Adhering to Schedule×100

Average Hold Time (AHT)

What is it? Average Hold Time measures the mean amount of time customers are placed on hold.
Why does it matter? Long average hold times highlight potential issues that need to be resolved, as they negatively impact customer satisfaction.

How to calculate Average Hold Time (AHT)
Average Hold Time (AHT)=Total Number of Calls/Total Hold Time Across All Calls

First-Call Close Rate

What is it? First-Call Close Rate shows the percentage of calls resolved on the first attempt.
Why does it matter? A high first-call close rate enhances customer satisfaction while reducing follow-up calls and agent workload.

How to calculate First-Call Close Rate (FCCR)
FCCR (%)=Total Number of Calls Handled/Number of Calls Closed on First Attempt×100

3. Call initiation metrics

Metrics that show how quickly and efficiently customer and agent calls are connected.

Average Speed of Answer (ASA)

What is it? ASA is the average time it takes for call agents to answer inbound calls.
Why does it matter? Longer wait times lead to frustrated customers and higher call abandonment.

How to calculate Average Speed of Answer (ASA)
ASA = Total Time Waiting in Queue/Total Calls Answered

The UK average speed of answer sits at around 17 seconds. However, many contact centres consistently answer calls within 10 seconds, which shows what’s actually achievable with effective resourcing.

Call Transfer Rate

What is it? Call transfer rate measures the percentage of calls transferred to another agent or department.
Why does it matter? High call transfer rates suggest poor call routing or gaps in agent training.

How to calculate Call Transfer Rate (CTR)
CTR (%)=Total Calls Handled/Number of Calls Transferred×100

Right Party Contact (RPC)

What is it? RPC measures the percentage of outbound calls that successfully connect with the right person.
Why does it matter? Low RPCs can lead to higher operational costs and reduced customer satisfaction. Low RPCs have the potential to be a compliance issue for sales and debt collection call centres.

How to calculate Right Party Contact (RPC)
RPC (%)=Total Number of Contact Attempts/Number of Right Party Contacts×100

UK outbound teams report an average right party contact rate in the low-to-mid 40% range, underlining the importance of data quality and dialling strategy.

Call Abandonment Rate

What is it? Call abandonment rate is the percentage of customer calls that hang up before speaking to an agent.
Why does it matter? High call abandonment signals customer dissatisfaction with wait times.

How to calculate Call Abandonment Rate
Abandonment Rate = (Abandoned Calls/Total Incoming Calls) ×100

The average inbound call abandonment rate currently sits at just over 4%, suggesting most contact centres are managing queues effectively, but with limited margin for error during peak periods.

4. Call centre operations metrics

Metrics that provide insights into the overall efficiency of call centre operations, enabling call centres to optimise processes.

Service Level Agreement (SLA) Compliance

What is it? SLAs measure the percentage of calls answered within a predefined timeframe and quality standard. This is pre-agreed between the call centre and its clients.
Why does it matter? Measuring calls in line with SLAs shows adherence to service-level performance goals.

How to calculate Service Level Agreement compliance
SLA Compliance = (Calls Answered Within SLA Time/Total Incoming Calls) ×100

Cost Per Call (CPC)

What is it? CPC is the average cost incurred per call handled.
Why does it matter? Evaluating CPC helps call centres optimise budget allocation.

How to calculate Cost Per Call (CPC)
CPC = Total Call Centre Costs/Total Calls Handled

For outsourced operations, consistently hitting KPIs such as SLAs, cost per call, and quality scores can be more complex due to working across multiple clients or campaigns concurrently. Our article on call centre outsourcing: how can BPOs meet their KPIs explores how providers can tackle these specific challenges.

Tracking the right metrics is essential for gauging effectiveness, but the follow-up question is always “how do we improve?” For many contact centres, AI and automation are becoming a central part of improving performance.

How AI and automation help contact centres improve metrics

According to the 2025/6 Benchmarking Report:

• 66% of contact centres are already using or piloting AI
• A further 20% planning implementation.

Adoption of AI and automation is becoming widespread, and is reflective of the growing role that technology plays in improving efficiency, quality and customer experience.

A clear use case of AI-powered tools was to reduce metrics such as average handle time to provide a better customer experience.

• 47% of contact centres report improved customer experience following AI adoption
• While 30% say AI has driven a significant transformation in service delivery

These gains directly support improvements in metrics such as first contact resolution, customer satisfaction and customer effort score.

Confidence in these AI and automation tools is high. 99% of contact centre leaders expect AI to improve effectiveness over the next three years, which means that technology advancements will play an increasingly central role in sustaining performance as agent workloads continue to rise.

Want to see how your contact centre compares?

Download the 2025/26 UK Contact Centre KPI Benchmarking Report to explore industry averages, performance gaps and emerging trends across customer experience, productivity and operations.

But reporting on results isn’t the same as being data-driven. In outbound sales, data only creates value when it is used to actively influence decisions; ideally, while activity is still happening rather than when it is reviewed days later.

A genuinely data-driven outbound sales team will use live performance data to shape how calls are placed, which leads are prioritised, how agents are routed and where coaching is applied. Data, technology and execution work together as a single system.

In this article, we explore what “data-driven” should really mean for outbound sales teams operating in a contact centre environment. We look at the outbound sales metrics that matter most, how technology turns those metrics into real-time decisions, and share the latest data from our Benchmark Report to help you determine whether your performance is average or genuinely competitive.

Use data to decide which leads deserve agent time

Outbound sales teams should focus on maximising productive talk time as the foundation. But the next question becomes, who should agents be spending that time speaking to?

The average first-call close rate across outbound sales teams is 25%, with 31% of teams achieving rates between 20% and 29%. This shows that conversion performance is driven less by how many calls are made and more by how effectively effort is focused.

Understanding which metrics genuinely influence outcomes is critical here. Our complete guide to call centre reporting metrics breaks down the KPIs that matter most, and how they should be interpreted in context rather than in isolation.

Sales teams should concentrate on prospects that are most likely to convert. Which means the first-in, first-out approach to lead prioritisation is an ineffective strategy.

This is where intelligent lead prioritisation tools powered by AI have a huge operational impact. By pulling data from multiple sources, such as recent engagement, historical call outcomes, conversion performance, and potential deal value, intelligent lead prioritisation ranks leads dynamically. As prospect data signals change, prioritisation updates are applied automatically, which means agents consistently spend their available talk time on the opportunities most likely to deliver results.

Use data to match the right agent to the right lead

Data-insights need not stop at determining high-value and high-intent leads. It can also influence who handles them.

While the mean average revenue per call across outbound sales teams is just under £230, over 45% of teams generate less than £59 per call. This gap highlights how widely outcomes can vary depending on agent capability.

When data is used to create value, agent assignment isn’t random or purely availability-based. Instead, performance data is used to match leads with the agents most likely to convert them. For example:

• Higher-value or more complex opportunities can be routed to experienced agents with deeper product knowledge or a proven track record of closing similar deals.
• Price-sensitive or early-stage leads may be better suited to agents who perform strongly at qualification and objection handling.
• Sector-specific prospects can be matched with agents who have previous success in that industry or campaign type.

Skill-based routing makes this possible by using historical performance data such as conversion rates by product, deal size, objection type, or lead source. As new performance signals are captured, routing rules can be refined so decisions improve continuously.

Use real-time performance data to intervene early

Outbound sales performance can change quickly. So, relying on end-of-day or weekly reports limits how effectively teams can respond. Retrospective reporting removes the opportunity to correct issues such as poor lead targeting or gaps in agent performance.

Access to real-time performance data gives sales managers the visibility they need to intervene without burning through contact. Live dashboards show early signals, such as declining connect rates, falling conversion performance, or uneven agent productivity.

Instead of waiting for performance reviews, managers can guide execution as it happens. This might involve reallocating resources, adjusting call scripts, changing lead allocation, or providing targeted coaching.

Contact centres that use real-time insight to guide daily decision-making are better positioned to protect conversion rates and maximise the impact of agent time.

For outsourced or multi-client environments, this ability to intervene early is particularly important. Our article on how BPOs can meet their KPIs explores the additional performance and reporting challenges faced by outsourced contact centres.

Use Conversation Analytics to understand why performance varies

Surface-level metrics such as contact rate, conversion rate and first-call close rate explain what is happening in outbound sales. But the why behind performance differentiation is dependent on agents, campaigns, or lead types, and teams need insight from the conversation itself.

Our Conversation Analytics analyses 100% of outbound calls, transforming unstructured call audio into actionable insight that would be impossible to capture through manual review or random sampling.

With the ability to analyse conversations at scale, sales leaders can review and identify the underlying drivers of performance. This insight helps explain why certain agents convert more effectively, why objections stall progress, or why specific lead types underperform despite similar call volumes.

In practice, Conversation Analytics supports data-driven outbound sales teams by enabling:

• More targeted coaching: Identify the techniques used in successful calls and pinpoint where individual agents need support
• Better script and messaging optimisation: Surface patterns in high-performing conversations and common objections
• Improved quality and compliance oversight: Analyse every call rather than small samples
• Earlier identification of emerging issues: Spot shifts in sentiment, objections, or competitor mentions

If you’re looking for a broader view of how these metrics work together, our guide on how to measure call centre efficiency explores how performance indicators combine to drive overall effectiveness.)

Key benefits for outbound sales teams include:

• Enhanced Agent Training: Identify successful techniques and areas for improvement, allowing for targeted training programmes.
• Customer Sentiment Analysis: Detect changes in tone and emotion, helping agents adapt their approach in real-time.
• Quality Assurance at Scale: Analyse every call, ensuring comprehensive QA and quick identification of compliance issues.
• Identifying Sales Opportunities: Recognise patterns in successful calls to refine sales scripts and strategies.
• Competitor Intelligence: Flag mentions of competitors, providing valuable market insights.
• Trend Identification: Quickly spot emerging trends in customer behaviour or common objections.

By implementing speech analytics, outbound sales teams can gain data-driven insights that lead to more effective strategies, improved customer experiences, and better business outcomes. Use these insights to identify common objections, spot successful sales techniques, and provide targeted coaching to your team. A recent study by Forrester found that companies using AI-driven speech analytics saw a 10% increase in customer satisfaction scores and a 15% improvement in first-call resolution rates.

With speech analytics, you’re not just collecting more data – you’re gaining the ability to understand and act on the nuances of every customer interaction, transforming your outbound sales operation into a truly data-driven powerhouse.

Sustaining data-driven outbound sales performance

When combined with performance data, conversation analytics closes the loop between insight and action. Conversation analytics doesn’t sit alongside metrics. It explains them and enables more confident decisions and continuous improvement.

Using more tools or tracking additional metrics doesn’t automatically make an outbound sales team data-driven. Data only becomes valuable when it actively guides decisions across the contact strategy, from how calls are dialled, and leads are prioritised, to how agents are routed, coached and optimised.

In genuinely data-driven teams, agents and managers understand what key metrics mean, how they influence outcomes and when intervention is needed. Performance reviews focus on interpreting trends and agreeing on clear next actions, rather than simply reporting on results after the fact.

The most effective outbound sales teams connect data. By linking real-time performance insight with intelligent technology and informed decision-making, they improve results while activity is still in progress, not once opportunities have already passed.

If you want to understand how your outbound sales performance compares to other UK contact centres, benchmarking is the most effective next step.

Download the 2025-26 UK Contact Centre KPI Benchmarking Report to explore industry averages, performance gaps and the characteristics of high-performing outbound teams.

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