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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.)

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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.

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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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The workload squeeze on UK contact centres is intensifying. In the latest 2025/6 UK Contact Centre KPI Benchmarking Insights Report, 52.6% of respondents report increased agent workload, up from 42% in 2024, a 10% rise. The report also highlights the people impact of sustained pressure: average annual agent turnover is 31.2%, up from 30.2% last year.

The report, based on a survey of 300 UK contact centre decision makers, highlights a sector balancing high customer expectations with tough economic conditions, and increasingly looking to technology to relieve pressure.

“Customer facing teams are being asked to do more - and the data shows that pressure is rising year-on-year,” said Ben Booth, CEO, MaxContact. “When workload increases, it doesn’t just affect service levels. It affects quality, morale, and the capacity to improve. The most sustainable response is to reclaim time - removing avoidable work and using AI to handle routine interactions and provide team’s with support, so they can focus on the conversations that truly need a human.”

AI moves from experiment to strategy

The research suggests AI is quickly becoming central to contact centre operations and investment. 66% of respondents say their organisations are using or piloting AI, with a further 20% planning implementation in 2025/26.  

Looking ahead, 60% of respondents say AI and automation tools will be a main area of increased investment in 2026, while 55% cite AI and automation implementation as a top technology priority for 2025/26.

Among those already using or piloting AI, the report finds:

• 48% say AI has improved customer experience  

• 30% say AI has driven a significant transformation, with AI becoming central to service delivery  

• 99% are confident AI will improve contact centre effectiveness over the next three years  

“This isn’t AI for AI’s sake,” added Booth. “Businesses are clear on the goal: protect customer experience or drive the desired business outcomes while reclaiming capacity for teams. The winners will be those who build AI into day-to-day service - not just a bolt-on tool.”

Competitive advantage is shifting towards technology, speed and insight

When asked what delivers the most competitive advantage, respondents point to:

• Advanced technology/automation (42%)

• Speed and responsiveness (42%)  

• Better customer data and insights (38%)

At the same time, the report highlights constraints contact centres must navigate as they scale AI. 45% cite data security concerns as a leading challenge holding back AI ambitions.  

Reclaiming time in the contact centre

In response to the findings, MaxContact is urging leaders to focus AI investment on one tangible outcome, reclaiming time.  

That means:

• Shifting high-volume, repetitive interactions to self-serve and automation to reduce operational pressure

• Using insight from conversations to spot objections, knowledge gaps and coaching opportunities - so you improve performance faster, across sales and service

• Supporting agents with better context and guidance so human time goes to high-value, high-impact conversations

The full findings and benchmarks are available in the 2025/6 UK Contact Centre KPI Benchmarking Insights Report.

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Every salesperson has heard them before:

❌ “How did you get my number?”
❌ “No, I’m not interested.”
❌ “I’m already with [competitor].”

Everyone who works in the industry knows that sales objections are inevitable. Particularly if you work in a high-pressure environment like a call centre where agents handle hundreds of calls every day.

It’s easy to view objections as a rejection, but a recent analysis of 800,000+ objections calls carried out by MaxContact from annoymynised platform data revealed that 39% can be overturned if they are handled well.

Objections should be viewed as opportunities. The chance to address concerns, show value, build stronger customer relationships, and move prospects closer to saying yes.

“When I first started in sales, the biggest challenge wasn’t hearing objections, it was knowing how to respond instead of just saying ‘Oh right, OK’ and ending the call.” – Business Development Manager, MaxContact

However, mastering objection handling doesn’t come down to persistence alone; it’s about having the right tools, techniques, and insights to guide conversations, understand prospect needs, and ultimately, improve conversions.

In this article, we’ll explore:

• Proven objection-handling techniques that empower sales teams.
• How AI-driven insights from MaxContact’s Conversation Analytics platform (including our success intelligence feature) can improve objection-handling strategies.

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It builds confidence within your sales team

When salespeople feel equipped to handle objections, they perform better. Our data shows that some objections are highly recoverable, for example:

• 46% of “No Immediate Need” objections were overturned
• 46% of “Lack of Time” objections were also successfully handled

This proves that when a sales team adopts the mentality that objections are hesitations, and signal the end of a conversation, they are more likely to find ways to adapt and refine their sales approach, instead of cutting their losses

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It improves conversion rates

Many objections aren’t a firm no; instead, they’re usually a sign that the prospect is missing key information and needs more clarity.

Our data analysis revealed that while “Not Interested” is one of the most common objections, occurring over 150,000 times. It’s also one of the hardest to overcome, with a 23% success rate.

Agents need to listen to and address these objections by being armed with a deep understanding of the right information to turn conversations around.

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It strengthens team performance

The most successful sales teams share best practices rather than keep them to themselves. They learn from each other’s handling techniques and replicate the best strategies across the team.

With MaxContact’s Success Intelligence feature, which is part of our Conversation Analytics product, sales leaders can identify patterns in objections. Leaders can see:

• Which objections appear most frequently
• Which ones agents struggle with
• Which top performers consistently overturn
• Coaching opportunities based on data, not assumptions

For example, cost-related objections account for 18% of all objections, but teams overturn almost 40% of them when they use strong value framing.

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It creates better customer experiences

Even if a sale doesn’t happen immediately (the majority don’t), a well-handled objection and respectful interaction builds trust, increasing the likelihood of a conversion further down the line.

Trust-based objections (which account for 22% of all objections) are among the hardest to overcome, especially “Lack of Trust,” which has just a 32% success rate.

A professional and respectful interaction can leave a positive impression, which means when things change in the future, they are more likely to consider you and get back in touch

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Objection handling techniques for sales calls

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1. Be prepared with a decent script

Why? A structured script helps your sales team be consistent and shows agents what good looks like. It is also easier to refine your approach and build agent confidence when handling objections.

Top Tip: You should regularly review and update your call scripts to mirror common objections. Refinements should be based on real-world responses and positive past outcomes.

Want ready-to-use objection-handling scripts? Download our Scripting Templates for Dealing with Difficult Customers to train your team with proven responses.

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2. Anticipate and address objections before the call

Proactively addressing potential concerns reduces resistance later in the conversation. Our dataset shows the most common objections are:

1. No Immediate Need - 151k occurrences
2. Not Interested - 150k occurrences
3. Lack of Time - 94k occurrences
4. Too Expensive - 69k occurrences

Top Tip: Do your research before the call and think about what their objections are likely to be. If you proactively address these pain points early in your pitch, you prevent them from derailing conversations later.

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3. Focus on building value

Cost objections make up nearly 70,000 conversations, but almost 45% of “Disputes Amount” objections are overturned when agents clearly demonstrate value. If you can confidently demonstrate how your product or service meets your prospect’s unique needs, it paves the way for a conversation with fewer objections to overcome.

Top Tip: Tailor your sales pitch so it addresses their specific pain points and priorities to make the benefits more relevant and persuasive.

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4. Uncover the real concerns behind the objection

Surface-level objections can often mask deeper customer concerns.

“Scepticism,” for example, occurred 50,364 times, with agents successfully resolving 44% when they probed deeper into customer concerns.

Listening, probing and clarifying explore the real motivations behind a “no.”

Top Tip: Use probing questions to encourage the customer to open up and really listen to what they have to say:

“What are your biggest challenges with your current system?”
“What keeps you up at night about this issue?”
“What does a good day vs. a bad day look like?”

Sales Specialist Insight: “Ask and then be quiet and listen. If you can keep the conversation going, you’ll build rapport, understand their needs, and have a better chance of addressing their true concerns.”

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5. Know when to cut your losses

It’s a skill in itself to realise that not every prospect is worth pursuing. At the end of the day, your time is a valuable resource, and some objections are genuine dead-ends, contractual commitments being one.

Our data analysis uncovered that “Contractual Obligations” appears less often as an objection but has a low recovery rate of just 35%.

Top Tip: Learn to recognise the signs that an objection is a hard “no” rather than a request for reassurance. Feel comfortable to politely bring the conversation to a close when it’s necessary.

Example: What does a ‘hard no’ sound like?

Agent: “I think our solution can really help you with [pain point]. Are you free for a quick call next week?”

Prospect: “Well, we’ve actually just signed a five-year contract with another provider, so we’re locked in with them.”

Agent: "Oh ok, sounds like you’re set for now, but I’d like to stay in touch in case your needs change in the future. Would you be happy for me to check back in with you in a few months to see how everything is going?"

Instead of pushing further, the agent sees that this isn’t a timing objection; it’s a contractual commitment. Instead they:

• Respect the prospect’s situation and don’t waste time.
• Keep the door open for future conversations.
• Avoid the hard-sell approach, which could damage the relationship.

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6. Understand it’s a numbers game

Why? Not every call ends with a sale, but persistence and efficiency are part of what drives success.

How? It’s important that sales agents don’t get hung up on rejections. Call volume and quality interactions are key, so the best thing to do is move on to the next prospect.

Top Tip: Use automated dialler software to improve connection rates and reduce wasted time. Skills-based call routing can also help to match the right agents to potential opportunities to match their knowledge and experience.

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Objection handling cheat sheet

How AI-driven insights take objection handling to the next level

Not every call ends with a sale, but persistence and efficiency are part of what drives success. Across all 803,000 objections, agents overcame 39% overall.

It’s important that sales agents don’t get hung up on rejections. Call volume and quality interactions are key, so the best thing to do is move on to the next prospect.

Top Tip: Use automated dialler software to improve connection rates and reduce wasted time. Skills-based call routing can also help to match the right agents to potential opportunities using their relevant knowledge and experience.

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MaxContact’s Conversation Analytics & Success Intelligence - Turning Insights into Sales Success

Traditionally, sales coaching relies on manual call reviews, which are time-consuming and only capture a small percentage of conversations.

But with Conversation Analytics and Success Intelligence, sales teams can now use post-call insights and AI-powered analytics to enhance objection handling across teams.

Here’s how it is used in call centres.

Speech analytics that goes beyond transcription

• Transcribe and analyse 100% of calls with speech analytics. Instead of analysing small call samples taken at random, you can search and analyse a higher volume of calls, so fewer objections go unnoticed.
• Identify trends in objections and understand the most common customer concerns within your sales process.
• Track sentiment and review call summaries to explore where or when conversations take a negative turn.
• Use AI-powered analytics to enhance coaching with data-backed insights that help agents improve faster.

Success Intelligence - AI that measures & improves objection handling

• Categorise and analyse objections and help agents refine their approach.
• Identify what top performers do differently to overcome objections and use it as a blueprint for coaching agents who struggle.
• Provide actionable insights based on performance trends and data, not just opinions based on limited call samples.

“Success Intelligence highlights your best-performing agents and allows you to compare them with lesser-performing agents to see where improvements can be made. Instead of just reviewing a handful of calls, we now have insights into every objection raised and whether or not it was handled effectively.”

Ready to handle objections in sales the smarter way?

Handling objections is more than just a desirable sales skill; it’s a competitive advantage.

The best sales teams:

✔ Use structured scripts and refined techniques.
✔ Stay adaptive and customer-focused.
✔ Use AI-driven insights to continuously improve strategies.

Want to see these techniques in action?

Book a free demo of MaxContact’s Conversation Analytics to see how AI-powered insights can improve your sales team’s objection handling

Contact centres are working harder than ever – yet outcomes aren't improving. Despite deploying more technology and increased investment, connect rates remain stubbornly lower, attrition stays high and costs per call have reached a five-year high.  

The breakthrough will come from technology that connects seamlessly – where your systems work as one platform, not separate tools.

Here's what contact centre leaders need to know about 2026.

2026's Defining Shift: Making Your Systems Talk to Each Other

Last year was about proving AI works. This year is about making it work together.

Picture this: Your conversation analytics spots that agents are struggling with a specific complaint type. Right now, that insight sits in a report somewhere. In 2026? It automatically triggers updated coaching materials, alerts team leaders, and feeds into next week's training schedule.

That's the shift. Not more tools. Connected tools.

Your CRM knows what your telephony system is doing. Your analytics feed your workforce planning. Your AI capabilities trigger actual actions, not just insights.

The winners in 2026 will connect their systems, not just collect them.

• ‍Key Takeaway: The winners in 2026 will be organisations that connect their capabilities, not just collect point solutions.

AI Adoption: Data First or Fail Fast

With 66% of organisations already using or piloting AI, adoption is no longer the question. Successful implementation is. And here's the problem: 80% cite data quality as their main barrier, while 75% say their data is too siloed to use AI effectively.

Here's what happens next

Some organisations will fix their data first. Others will skip that step and wonder why their AI projects fail. The gap between these two groups will widen fast in 2026.

The organisations getting it right start with a simple question:

Before any AI project: where's the data? Is it current? Can we trust it? Is it joined up?

Then they split projects into two categories:

• Quick wins need minimal data. Automated absence handling? One data source. Call summarisation? Just transcripts. These deliver fast returns and fund bigger projects.

• Big projects need more serious data work. Cross-channel customer insights. Predictive analytics. These require 12-18 months of data consolidation. But once done, they unlock multiple AI use cases at once.

The Reality Check

Most organisations skip the data work. They deploy AI on fragmented information. It disappoints. They blame the AI.

Meanwhile, AI is creating more data. Speech analytics now transcribes every call. Conversation analytics tracks every interaction. The challenge isn't just fixing old data problems – it's making the flood of new data useful for the people who need it.

• ‍Key Takeaway: Start with quick wins on clean data. But commit to the harder work of data consolidation, or your AI projects will keep disappointing.

Contact Strategy: Beyond Set-and-Forget

The numbers are stark: outbound connect rates sit at 42.8%, with only 27% reaching the right person. Traditional set-and-forget strategies aren't working. AI call screening will only make this harder.

Yet voice isn't dying – it's evolving. Most valuable AI starts with voice: conversational AI, sentiment analysis, real-time insights. Even chatbots are moving toward voice interfaces.

What Works in 2026

Three factors define successful contact strategies:

• Speed to lead has returned as top priority. When customers show intent, the window is minutes, not hours. Organisations reaching out within 5-10 minutes see dramatically higher conversion.  

• Intelligent personalisation means dynamic, context-aware outreach. Not just who to contact, but when, how, and with what message based on their specific situation and recent interactions. This requires joining up web behaviour, contact history, and purchase patterns.

• Dynamic multi-channel workflows adapt in real-time. Customer doesn't answer? Trigger an SMS: "We're calling from [company]. Save this number, we'll call back at [preferred time]." They respond with availability and the system adapts. They engage via chat? The system handles it and transfers to human when needed, with full context.

Why SMS Matters

SMS isn't replacing calls. It's making calls work better.

"Save our number, we'll call when suits you" transforms cold calling into expected contact. Response rates go up. Conversations are better because people are ready for them.

But only if your SMS, voice, chat, and email systems actually work together.

• ‍Key Takeaway: Abandon set-and-forget for dynamic, multi-channel workflows that adapt to customer behaviour. Build multi-channel workflows that adapt to how each customer actually wants to engage.

The Data Problem: From Integration to Intelligence

Contact centres are saying siloed data blocks CX improvement. Teams make decisions on incomplete information. Despite AI tools generating insights, frontline managers still can't easily answer: "Which agents are struggling and why?" or "Where are our quality issues?"

Will 2026 fix this? Our prediction: fragmentation won't worsen, but solving it will be slower than hoped. The challenge has shifted from having data to making it meaningful.

The New Challenge

Conversational analytics now transcribes every call and summarises every interaction. That's incredibly valuable.

But a team leader managing 15 agents faces 500 call summaries a day. Reading them all isn't realistic.

What they actually need: which agents need support right now? What's the trending issue today? What should I focus on first?

What This Looks Like When It Works

It's 9:30am Tuesday. Your team leader opens their screen and sees:

"Agent Sarah has handled three difficult complaints this morning. Might need a check-in."

"Billing issue contacts up 40% vs yesterday. Consider adding afternoon resource."

Not a dashboard to interpret. Not a report to analyse. Just: here's what needs your attention right now.

How to Get There

The organisations making progress aren't building more sophisticated dashboards. They're rethinking how information reaches people.

• Alerts instead of reports. Team leaders get notified when agents need support. Ops managers see capacity issues before they escalate. The system brings insights to people, rather than expecting people to hunt for them.

• Conversational access. A team leader can ask: "Why is Sarah's handle time up today?" and get an answer with context. No report building required.

• Embedded in workflows. Insights appear where people already work, not in separate reporting tools they need to remember to check.

‍Key Takeaway: The challenge isn't gathering data or even analysing it. It's getting the right insight to the right person at the moment they can act on it.

Agent Experience: Finally a Priority

The statistics: 52% report increased workload (up 10 points), agents switch between 6-12 windows, attrition remains at 31.2%, and cost per call hits £6.26. As routine tasks automate, agents handle only complex interactions – meaning every contact is difficult.

Why This Matters Now

The business case is finally clear. At £6.26 per call, you can't afford agents spending 30% of their time hunting for information across multiple systems.

Vendors are starting to focus on this. The quick AI wins – digital deflection, call summarisation – are done. Now they're tackling the harder problem: reducing the cognitive load that comes from constantly switching context.

What’s Changing in 2026

As low-value tasks automate, agents handle only high-value interactions. Every conversation involves complexity or emotional sensitivity. The job is harder than ever.

In 2026, expect:

• Unified desktops that bring information from multiple systems into single interfaces, surfacing the right information at the right time based on conversation context.

• Real-time assistance that provides contextual guidance, suggests actions, surfaces knowledge articles, and drafts responses. AI becomes the agent's assistant, not replacement.

• Post-interaction support recognising the emotional toll. Automated break scheduling after difficult calls, sentiment monitoring for struggling agents, proactive manager interventions.

• Better performance frameworks moving beyond handle time to recognise interaction complexity. First-call resolution for complex issues, sentiment improvement, and de-escalation become the measures that matter.

Will 2026 fix the agent experience? Our prediction: improvements begin, but full transformation extends into 2027.

Key Takeaway: Agent experience is finally getting serious attention. The focus is shifting to reducing cognitive load and supporting agents who now handle only the most complex interactions.

The Offshore Reality

Offshoring is accelerating. The economic pressure from 2025 isn't easing – it's getting stronger.

But there's a pattern worth noting. Over the past 15+ years, we've seen the same cycle repeat: contact centres move offshore to cut costs. Quality issues emerge. Operations move back to the UK. Then costs rise again, and the cycle starts over.

Offshoring isn't a permanent solution. It's a response to immediate pressure that often creates different problems down the line.

What this means for UK operations

If you're running a UK contact centre, competing on cost alone won't work. The economics don't add up.

The path forward? Combine AI efficiency with the advantages UK operations naturally have. Quality. Cultural alignment. Regulatory compliance. Understanding of the local market.

AI helps narrow the cost gap. 20-30% efficiency improvements make the economics more defensible. You're still not the cheapest option, but you can justify the premium based on outcomes.

Here's the reality: without AI, UK contact centres at scale struggle to make the numbers work. With AI, you can compete on value rather than just price.

• ‍Key Takeaway: For UK operations, AI isn't a nice-to-have. It's what enables you to compete on outcomes while narrowing the cost gap that offshore alternatives exploit.

Looking Ahead: Strategic Technology Decisions

As we move through 2026, the question isn't whether to invest in technology. It's which technology to invest in.

• Choose solutions that connect with what you already have. The best new tool in the world doesn't help if it sits in isolation. Before buying anything, ask: how does this integrate with our existing systems? Can it talk to our CRM? Our telephony platform? Our analytics tools?

• Prioritise data foundations. Fix the plumbing before adding new taps. If your data is fragmented, every AI tool you add will underperform. Sometimes the smartest investment is consolidating what you have, not buying something new.

• Look for vendors who care about outcomes, not just features. The conversation should be about what you're trying to achieve, not just what the software can do. Implementation support. Integration help. Ongoing optimisation. That matters more than a long feature list.

The bigger picture

The challenges facing contact centres in 2026 are real. Rising costs. High attrition. Fragmented data. Low connect rates.

But here's the opportunity: the right technology decisions – made thoughtfully – can genuinely transform outcomes. Not through revolutionary breakthroughs. Through building an ecosystem where your systems work together. Where new capabilities enhance what you already have. Where data flows naturally between tools, creating workflows that deliver results.

That's what 2026 is really about. Moving from collecting disconnected tools to building platforms that work as one.

What Contact Centres Should Prioritise in 2026

• Strategic technology decisions that prioritise full deployment and optimisation of existing AI capabilities alongside thoughtful expansion of your technology stack.

• Clear ROI demonstration for every new investment, with realistic timelines and measurable outcomes.

• First-contact resolution as a cost-reduction strategy, using AI and better agent support to solve issues completely on first interaction.

• Strategic workforce planning optimising resource allocation through AI-powered forecasting and scheduling.

• Data foundations that enable AI success – investing in consolidation and integration before deploying new capabilities.

• Agent experience improvements focusing on reducing cognitive load through unified interfaces and real-time assistance.

• Integrated workflows connecting systems across your technology stack so capabilities work together, not in isolation.

The contact centre industry has shown remarkable resilience. As we enter 2026, the organisations that thrive will be those that combine innovative technology with strategic implementation – building integrated systems that deliver measurable outcomes.

Ready to build a more integrated contact centre for 2026? Book a demo to see how MaxContact’s integrated platforms can address your challenges.

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Resource Centres are powerful, contextual hubs that surface relevant help content based on the product you’re working in. Whether you’re looking for a quick answer, learning a new feature, or working through a process step-by-step, support is now available exactly where you need it.

Why we built this

When you’re in the middle of a task, the last thing you want to is to stop, switch tools, or wait for a support response just to keep moving forward.

Resource Centres have been built to help you:

• Resolve questions quickly
• Stay focused on the task at hand
• Reduce disruption to your workflow

Instead of raising a support ticket or searching through documentation elsewhere, you can now access answers and guidance directly in the product. Helping you move faster and with greater confidence.

By bringing guides and walkthroughs into MaxContact itself, we can show you the exact steps to take, in real time, removing uncertainty and reducing the chance of error. This is especially valuable when new features are released, allowing you to build an immediate understanding of how they work and how you might want use them in your own setup.

What’s New: Key Features at a Glance

Within the Resource Centres you’ll find:

• ‍Powerful Knowledge Base Search
• Step-by-Step Guided Tours
• AI-Powered Chat Assistant
• Contextual Help, tailored to the product you’re working in

This is just the beginning. Resource Centres will continue to evolve, with additional features and capabilities planned over time.

Feature Breakdown: How Resource Centres Help You!

In-Product Access

Resource Centres are available directly within the MaxContact product, meaning help is always close at hand.

Powerful Knowledge Base Search

If you’re looking for more information on a particular setting, page or feature, you can now search our Knowledge Base directly from within the product. You’ll be taken straight to the most relevant solutions article, significantly reducing the time it takes to find the right answer.

We’re continually improving our Knowledge Base content to ensure articles remain accurate, clear and genuinely useful.

Step-by-Step Guided Tours

Guided Tours walk you through key processes directly within the product, step-by-step. They guide you to exact areas you need, highlight the relevant settings, and explain what each step is used for, so nothing is missed.

These tours are designed to:

• Help you complete tasks confidently
• Reduce confusion around complex processes
• Demonstrate new features as soon as they’re released

This means you can learn and adopt new functionality immediately, without having to search through release notes or documentation.

We’ve also reviewed common support desk queries to ensure the guides we build focus on what matters most to our customers. From everyday tasks to frequently requested processes, like blocking an inbound caller, making them quick and straightforward to complete.

AI-Powered Chat Assistant

The AI chat assistant is trained on our latest solution articles and product information, so you can feel confident in the answers it provides.

Alongside each response, you’ll also be shown the articles and guides that informed the answer, allowing you to explore further and build deeper knowledge when needed.

Contextual Help, Tailored to Each Product

Each Resource Centre is built specifically for the product it sits within.

For example:

• In Management Hub, you’ll see content and guides relevant to configuration and administration
• In Conversation Analytics, help is tailored specifically to analytics features
• In Contact Hub, users can self-train through guided walkthroughs directly in the product

What This Means for Support Going Forward

Our Support team isn’t going anywhere.

Resource Centres are designed to complement human support, not replace it. By enabling faster self-service for common questions and tasks, our Support team can focus more time on complex, high-priority issues, helping deliver meaningful resolutions when you need them most.

We’re excited to launch Resource Centres and look forward to seeing how they help make your day-to-day work simpler and more efficient.

Resource Centres will be gradually rolled out over the coming weeks, launching in Management Hub and Contact Hub, with Conversation Analytics to follow.