Explore fresh, expert perspectives on customer engagement and innovation

Today, an always-on, 24/7 approach to inbound and outbound customer journeys is what contact centres must deliver, allowing customers to access information, ask questions or respond to communications whenever it suits them.

And automated customer support isn’t confined to phone calls. Customers want channel choice: the ability to engage and switch across SMS, email, live chat and chatbots, without friction or disruption.

When those expectations aren’t met, the impact is immediate. 42% of customers have switched providers following a poor experience handled in the contact centre, making availability and responsiveness a commercial priority rather than a “nice to have”.

This pressure lands in an already challenging environment for contact centre leaders:

• Cost per call is at a five-year high, averaging between £5.50-£6.50
• First-call sales close rates are down year-on-year, with a 25% reduction in 2025
• The volume of customer interactions continues to grow across multiple touchpoints
• Many leaders report higher agent workloads than the previous year

At the same time, simply increasing headcount is rarely a viable option. As it brings significant financial and operational implications.

As a result, contact centres are balancing on a tightrope: deliver high-quality, always-on customer experiences without increasing costs or overwhelming agents.

It’s a tall order. Traditional contact centre models struggle most. Whereas those that treat AI and automation as a necessity, not an experiment, are far better positioned to succeed.

Why traditional contact centres can’t support a 24/7 approach

Contact centres that rely heavily on manual processes are far more likely to miss the mark on consistent, high-quality customer experiences. Not through lack of effort, but instead through lack of capability.

Without automation or AI-enabled workflows, manual contact centres lack the visibility needed to shape effective contact strategies. Disconnected channels and siloed data across multiple systems make it difficult to understand what’s driving demand, where workflows break down, and where agent intervention adds the most value.

As a result, agents often spend a disproportionate amount of time handling repetitive, low-value enquiries instead of focusing on complex or high-impact conversations. This creates inefficiency and, over time, contributes to lower morale and higher fatigue.

Traditional 24/7 models attempt to solve availability problems with people alone. But scaling this way gets expensive fast. In a typical mid-market contact centre, automating just 50-55% of repetitive interactions with AI Agents can reduce monthly handling costs by £80k-£100k (for midsized contact centres), depending on volume and channel mix.

Without connected, automated systems in place, scaling availability scales cost and pressure, but leaves customer experience to chance.

Orchestrating a multi-channel customer journey

Customer support shouldn’t be confined to a single channel. In omnichannel contact centres, customers regularly move between different channels, including SMS, email, chat and chatbots - sometimes within the same interaction.

A customer might receive an SMS, reply with a question, switch to chat for clarification, and later call expecting the conversation to continue seamlessly. Managing this consistently is difficult in manual contact centres, where channels and context are often treated as separate streams.

AI Agents and AI Chatbots make this easier by connecting voice and digital channels into a single, coordinated experience, handling conversations, retaining context and supporting smooth handovers to human agents when needed.

This orchestration is what makes always-on, 24/7 support achievable at scale, and sets the foundation for supporting inbound and outbound journeys more effectively.

What “always-on 24/7” really means for inbound and outbound support

Inbound and outbound interactions are different. And so is the way that customers expect to access 24/7 customer support.

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When inbound and outbound journeys are properly orchestrated and integrate AI customer service solutions:

• Customers can ask questions after receiving outbound messages, without waiting for office hours
• Routine follow-ups are handled digitally, so they don’t automatically become inbound calls
• Conversations continue seamlessly across voice and digital channels, regardless of time zone
• Human agents are reserved for moments where judgement, empathy or complexity matter most

This is what distinguishes always-on availability from simple 24/7 coverage. So, how do contact centre leaders make it a reality?

This is where AI-powered contact centre software becomes essential. Not as a replacement for human agents, but as the execution layer that makes always-on 24/7 customer support possible.

The role of AI Agents in continuous customer support

MaxContact’s AI Agents play a central role in delivering an always-on, 24/7 approach to inbound and outbound customer support, particularly in voice-led contact centres where consistency, compliance and context matter.

Rather than acting as basic automation, AI Agents handle natural, human-like conversations across voice and digital channels. They understand intent, ask clarifying questions and complete tasks end-to-end, from authentication and verification through to troubleshooting, routing and account actions, all without customers waiting in a queue to speak to an agent.

This makes AI Agents especially effective outside core operating hours, when customers still expect fast, accurate responses but human availability is limited. Every interaction is handled consistently and compliantly, with the same rules, prompts and safeguards applied every time.

AI Agents are designed to operate as part of a human-AI hybrid model, not as a replacement for human agents. When a case needs to be escalated due to complexity, risk, sentiment or customer preference, it is, with full conversational context passed on, so customers never have to repeat themselves.

Used this way, AI Agents extend contact centre capacity. They absorb repetitive and time-sensitive demand, pre-qualify and verify customers, and ensure agents are connected to the right conversations at the right time.

The result is faster responses, reduced queue pressure and consistent 24/7 support, without increasing headcount. In cost terms, organisations typically see AI-handled interactions delivered at under £0.50 per contact, compared to £6+ when handled by a human agent.

The role AI Chatbots play in always-on customer support

AI Chatbots aren’t a separate capability from AI Agents. They’re one of the digital channels through which AI Agents operate.

MaxContact’s AI Agents provide the intelligence that understands intent, manages logic and then controls workflows. AI Chatbots maximise that capability across digital touchpoints. This means that the same AI-powered conversations and workflows run consistently across chat, messaging and other digital channels.

In practice, this means customers can get instant answers and can complete simple tasks, such as scheduling a call, or respond to outbound communications through the AI Chatbot, without needing to call or wait in a queue.

Behind the scenes, the AI Agent handles intent, applies rules, and manages the conversation in exactly the same way it would in a voice-led interaction.

This is what makes AI Chatbots so effective in an always-on model. They extend AI Agent capability into digital channels, so contact centres can resolve routine and time-sensitive queries instantly, at any time of day. All whilst maintaining quality and compliance.

How to use AI Chatbots in everyday contact centre situations

In always-on customer journeys, AI Chatbots are particularly effective for handling predictable, high-volume interactions such as:

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Reducing pressure without reducing service

The goal of always-on, 24/7 customer support isn’t to replace human agents or cut corners on service. It’s to remove unnecessary pressure on people, costs and operations while delivering high quality customer experience.

By handling repetitive, predictable and time-sensitive interactions, AI Agents and AI Chatbots absorb demand that would otherwise sit in voice queues or overwhelm frontline teams. Customers still get fast, accurate support, but agents aren’t tied up answering the same questions or repeating the same checks.

This shift allows human agents to focus on high-value conversations. The conversations that need judgement, empathy, reassurance or problem-solving. These moments are where human input makes the biggest difference to outcomes.

Crucially, service levels aren’t reduced. They’re improved. Customers get quicker responses, fewer handoffs and more consistent experiences, while agents work in a more sustainable, focused environment.

Always-on customer support needs the right operational foundations

AI Agents work as a standalone capability. They handle conversations and automate tasks without needing a full contact centre platform.

So, for organisations that don’t operate within a traditional contact centre, AI Agents still deliver immediate value by providing always-on customer support. They handle routine and time-sensitive interactions, and also ensure that customers get fast and consistent responses outside core operating hours.

On the other hand, for organisations that do operate with a contact centre platform in place, AI Agents and AI Chatbots can be easily integrated with core CCaaS capabilities such as:

• intelligent diallers
• real-time call routing
• call queue management
• and contact centre analytics
  

In a contact centre environment, AI Agents extend and enhance existing workflows, and help contact centres manage demand more intelligently by prioritising interactions, and continuously optimising performance across both inbound and outbound journeys.

With the ability to operate independently, or as part of a wider CCaaS set up, AI Agents give a wide variety of businesses the flexibility to scale availability and responsiveness without increasing headcount or incurring ongoing costs. Turning 24/7 customer support into a sustainable capability rather than an operational headache.

Deliver always-on support without always-on staffing

Customers now expect an always-on, 24/7 approach to inbound and outbound customer journeys. Meeting that expectation is reliant on operational foundations that encourage automated workflows, rather than expanding teams and ongoing costs.

By combining AI Agents, AI Chatbots and contact centre capabilities within a single, connected CCaaS platform, contact centres can deliver continuous, high-quality support that scales efficiently and sustainably.

In this model, 24/7 customer support isn’t a strain, it’s a strength that protects customer experience, teams and costs at the same time.

Deliver always-on customer support without increasing headcount.

Explore AI contact centre solution

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As an industry, we’re past debating whether or not AI should be utilised in contact centre workflows. Now, the biggest question is how to do so successfully. How can AI and automation deliver the greatest operational benefits without impacting customer experience?

To be successful, operations teams need to understand:

• How different forms of automation work day to day
• Which problems and scenarios do AI solutions solve
• How AI and automation fit into existing contact centre workflows
• How to implement AI while mitigating risk, complexity and poor customer experiences

Why contact centre leaders are rethinking automation

For many contact centres, the focus on AI and automation is a result of sustained operational pressure rather than chasing technology trends.

Over the last few years, customers’ expectations have changed, with most demanding 24/7 customer support options. As demand has continued to rise, so has agent workload, with over half of contact centre leaders admitting that workloads are a challenge. Add in higher call costs, and it’s clear that something needs to change operationally to take the strain.

AI and automation are capable of protecting service quality and reducing operational costs.

However, it will only work if automation is applied thoughtfully and strategically. And it’s critical that operations teams balance AI utilisation and human judgement. Without a clear grasp of the role AI solutions should play within customer journeys, it creates as many problems as it solves.

With that in mind, let’s look at how voicebots (AI Agents) and AI Chatbots work within the customer journey, both in isolation and as one.  

What’s the difference between a voicebot and a chatbot?

AI voice agents and AI chatbots are both specialised tools designed to address different friction points in the customer journey.

Both understand intent and deliver natural, human-like conversations that can handle enquiries end-to-end.

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One of the biggest concerns that contact centre leaders have around integrating AI solutions is that interactions feel robotic. Thoughts turn to clunky "press 1" IVR scripts, or chatbots that get stuck in "I don't understand" loops.

However, AI-powered solutions are built differently.

• AI Agents and AI Chatbots hold natural, context-aware conversations, whether it be realistic voice synthesis for phone calls or text for chat.
• Rather than relying on specific keywords or phrases, they are built to understand intent and semantics. They ask clarifying questions and complete tasks such as authentication and troubleshooting in real time.
• Industry-trained, AI constantly learns and adapts to the business, improving with every interaction. Responses aren't repetitive or "canned."
• Both voice and chat solutions are built for easy live agent escalation. If a conversation detects frustration or complexity, a handover is triggered. The full background and context are passed to a human agent.

Understanding automation maturity: Where should you start?

Not all contact centres need the same level of automation. The best approach depends on your operational maturity, technical infrastructure, and business priorities.

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How both solutions work in practice: 3 common use cases

The power of modern AI automation is that the same use case can be delivered via voice or chat, or orchestrated across both channels based on customer preference and context.

Use case 1: Payment issues

Challenge: Missed or failed payments need immediate action and often result in agent escalation.

Solution: AI Agents can proactively call customers to verify identity, explain the issue, and guide them through payment options, repayment plans, or promise-to-pay agreements. AI Chatbots handle the same workflow asynchronously for customers who prefer digital channels.

Outcome: End-to-end resolution without agent involvement, with automatic escalation if vulnerability is detected.

Industry example: Utilities companies use this for both scheduled payment reminders and failed direct debit notifications.

Use case 2: Account updates & routine queries

Challenge: Customers calling for opening hours, balance information, policy details, or basic account changes.

Solution: AI handles these interactions instantly across voice or chat, verifying identity, retrieving information, and updating backend systems as needed.

Outcome: Zero queue time for customers and a massive reduction in avoidable contact.

Industry example: Retail operations use this for delivery updates and returns processing; insurance uses it for policy reference capture.

Use case 3: FAQ deflection

Challenge: Repetitive "how do I..." questions consume agent time despite having simple answers.

Solution: AI Chatbots and Voice Agents answer instantly without escalation, allowing customers to self-serve 24/7.

Outcome: Significant inbound deflection, allowing agents to focus on complex issues.

Industry example: Telecom providers use this for connectivity troubleshooting and plan information.

Why most contact centres need both voice and chat automation

Your customers don't use one channel. They might start with a query on your website chat, then follow up with a phone call, before completing the task via an SMS link. But if your automation tools don't work together, your customers will find it more difficult to resolve their query.

The most effective contact centres use both AI Agents and AI Chatbots as part of a coordinated approach. This means:

• Customers get consistent service whether they call, chat, or message
• Context flows between channels, so customers don't have to repeat themselves
• You can start with one channel and add others as your needs grow
• Agents receive the full conversation history when they need to step in

That kind of flexibility only works when both solutions are designed to work together from the start.

What to consider when choosing AI automation

If you're exploring AI Voice Agents or AI Chatbots for your contact centre, here are a few questions to guide your thinking:

Where are you feeling the most pressure?

Look at your highest-volume, most repetitive interactions. Start there for quick wins.

What channels do your customers prefer?

If most contact comes through phone calls, then voice automation makes sense. If digital channels dominate, then start with chat. If it's mixed, you'll likely need both.

How mature is your operation?

If your contact centre operations aren't considered mature, then focus on basic tasks like FAQs and appointment confirmations. For more established or complex operations, consider intermediate or advanced workflows, like payment processing or retention flows.

Can your solution grow with you?

Make sure whatever you choose can scale to handle more complex use cases and additional channels in the future. That way, you won’t have to start again from scratch.

Explore how MaxContact’s AI solutions can transform your contact centre operations. Strike the right balance between reducing agent workload without increasing costs, and crucially, without compromising customer experience.

Explore AI Solutions

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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