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In an era where customer interactions can make or break a business, understanding the pulse of contact centre operations has never been more crucial. That’s why we’ve conducted an extensive survey of 500 UK contact centre leaders, spanning various sectors and organisation sizes, to bring you our 2024 Industry Benchmark Report.

This comprehensive study delves into the heart of contact centre operations, examining key performance indicators, emerging trends, and the challenges faced by industry professionals. From sales strategies to debt collection tactics, customer experience initiatives to agent performance metrics, our report offers a panoramic view of the current landscape. Whether you’re looking to optimise your sales approach, enhance your customer service, or improve your debt collection processes, the insights gleaned from this study will provide valuable benchmarks and actionable intelligence.

Sales Benchmarking

In the realm of contact centre sales, our findings reveal a sector striving for efficiency and effectiveness in an increasingly challenging market.  

Key findings:

• Average daily calls per agent: 65.55
• Mean success per call rate: 6.74%
• Average first-call close rate: 27.81%
• Mean average revenue per call: £197.60

The average number of daily calls per agent stands at an impressive 65.55, with half of the sales teams managing between 31 and 60 calls per agent per day. This high volume of calls underscores the importance of streamlined processes and effective time management in today’s fast-paced sales environment.

What’s particularly encouraging is the mean success per call rate of 6.74%. This figure suggests that most of our respondents are working with qualified leads rather than relying on cold calling, which typically yields much lower success rates. It’s a testament to the growing sophistication of lead generation and qualification processes in the industry.

The average first-call close rate of 27.81% further emphasises this point, with nearly 30% of teams achieving rates between 20% and 29%. This metric not only reflects the quality of leads but also speaks volumes about the skill and preparation of sales agents. It highlights the value of thorough training and the importance of equipping agents with the right tools and information to close deals efficiently.

However, when it comes to revenue generation, there’s a notable disparity among teams. While the mean average revenue per call is £197.60, nearly a quarter of teams are generating between £30 to £59 per call. This variance suggests there’s significant room for improvement in upselling and cross-selling strategies for many contact centres. It also points to the potential benefits of focusing on high-value products or services to boost overall revenue.

Debt Collection Benchmarking

The debt collection sector faces unique challenges, especially in the current economic climate. Our findings provide a nuanced picture of how debt collection teams are performing in this demanding environment.

Key findings:

• Mean Right Party Contact (RPC) rate: 26%
• Average Promise to Pay (PTP) rate: 29%
• Mean percentage of debt collected: 32%
• Average First Call Resolution (FCR) rate: 42.83%

The mean Right Party Contact (RPC) rate of 26% indicates that debt collection teams are making headway in reaching the correct individuals, but there’s still considerable room for improvement. Enhancing this metric could significantly boost overall collection efficiency, potentially through better data management and intelligent dialling strategies.

When it comes to securing commitments, the average Promise to Pay (PTP) rate of 29% shows promise, with over half of the teams achieving rates between 20% and 39%. This suggests that once contact is made, agents are relatively successful in negotiating payment arrangements. However, pushing this rate higher could dramatically improve collection outcomes.

Perhaps the most encouraging statistic is the mean percentage of debt collected, standing at 32%. This figure outperforms the average US rate of 20% to 30%, indicating that UK debt collection teams are relatively effective in their collection efforts. However, it also suggests that there’s potential to recover an even greater proportion of outstanding debts.

The average First Call Resolution (FCR) rate for debt collection at 42.83% is a positive sign, showing that many issues are being resolved efficiently. However, increasing this rate could lead to faster resolutions and improved customer satisfaction, even in challenging circumstances.

Contact Centre Agent and Team Benchmarking

Our findings on agent and team performance reveal a sector in flux, adapting to new working models while grappling with perennial challenges.

Key findings:

• 66.2% of agents work in a hybrid environment
• Average annual agent turnover rate: 30.2%
• 43.8% of contact centres increased agent salaries (average increase: 7.14%)
• 42.0% of contact centres reported increased agent workload (average increase: 10.87%)

The shift towards hybrid working is clear, with 66.2% of agents now working in a hybrid environment and less than a quarter (23.2%) working fully in-office. This transition brings both opportunities and challenges, requiring contact centres to adapt their management and communication strategies to ensure consistency and quality across different working environments.

The average annual agent turnover rate of 30.2% remains a concern, highlighting the ongoing challenge of retention in the industry. This high churn rate can lead to increased training costs, reduced efficiency, and potential impacts on customer experience. Addressing this issue through improved working conditions, career development opportunities, and employee engagement initiatives should be a priority for many contact centres.

On the compensation front, 43.8% of contact centres reported an increase in agent salary compared to last year, with an average increase of 7.14%. This suggests that many organisations are recognising the need to offer competitive salaries to attract and retain talent. However, it’s worth noting that over half of the contact centres surveyed didn’t report a salary increase, which could potentially exacerbate retention issues.

Perhaps most concerningly, 42.0% of contact centres reported an increase in agent workload compared to last year, with an average increase of 10.87%. This significant uptick in workload, if not managed carefully, could lead to burnout, decreased job satisfaction, and ultimately, higher turnover rates.

Customer Service Benchmarking

In an age where customer experience can be a key differentiator, our findings reveal a sector that’s performing well but still has room for improvement.

Key findings:

• Mean call abandonment rate: 4.41%
• Average speed of answer: 17.11 seconds
• Mean Average Handle Time (AHT): 7.82 minutes
• Average First Call Resolution (FCR) rate: 41%

The mean call abandonment rate of 4.41% is relatively low, with over half of teams achieving rates between 2% and 5%. This suggests that most contact centres are managing their call volumes effectively, preventing customer frustration due to long wait times. However, striving to reduce this rate further could significantly enhance customer satisfaction.

When it comes to responsiveness, the average speed of answer stands at 17.11 seconds. While this isn’t a poor performance, it’s worth noting that a quarter of teams are managing to answer calls between 6 and 10 seconds. This faster response time could be a goal for other contact centres to aspire to, as quick answers can dramatically improve customer perceptions.

The mean Average Handle Time (AHT) of 7.82 minutes, with 44% of teams reporting times between 6 and 9 minutes, indicates a balance between efficiency and thoroughness. However, it’s crucial to remember that AHT should always be considered alongside other metrics like customer satisfaction and first call resolution to ensure quality isn’t sacrificed for speed.

Speaking of First Call Resolution (FCR), the average rate for customer service stands at 41%. While this isn’t a poor figure, there’s certainly room for improvement. Boosting FCR rates can lead to increased customer satisfaction, reduced workload, and lower operational costs.

Charting the Course for Contact Centre Success

As we reflect on the findings of our 2024 Industry Benchmark Report, it’s clear that UK contact centres are navigating a complex and evolving landscape with resilience and adaptability. While there are many positives to celebrate – from impressive sales metrics to above-average debt collection rates – there are also clear areas for improvement across all sectors.

There are several challenges facing contact centres in the coming years: balancing efficiency with quality customer experiences, managing the transition to hybrid working models, addressing retention issues, and leveraging new technologies like AI and speech analytics to enhance performance. However, these challenges also present opportunities for forward-thinking contact centres to differentiate themselves and achieve new heights of success.

By focusing on key performance indicators, investing in agent wellbeing and development, and embracing innovative technologies, contact centres can enhance their operations, improve customer satisfaction, and drive business growth. The benchmarks provided in this report offer a valuable starting point for organisations looking to assess their current performance and set ambitious yet achievable goals for the future.

As we move further into 2024 and beyond, the contact centre industry will undoubtedly continue to evolve. Those who stay informed, remain agile, and consistently strive for improvement will be best positioned to thrive in the forever changing contact centre environment. At MaxContact, we’re committed to supporting this journey, providing the tools, insights, and support needed to turn these benchmarks into stepping stones for success.

The full “2024 UK Contact Centre KPI Benchmarking Insights Report” is available for download here. 

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As we close out 2024, it’s time to look ahead at what the coming year might bring for the contact centre industry. The sector has shown remarkable resilience and growth, with industry revenue reaching an estimated £3.2 billion in 2024, representing a compound annual growth rate (CAGR) of 5.1% over the past five years. This sustained growth, despite economic headwinds, demonstrates the vital role contact centres play in modern business operations. While the past year brought its share of challenges, it also showed us the adaptability of the sector.

Here’s our forecast for the key trends that will shape contact centres in 2025.

AI Enters the Value Creation Phase

If 2024 was about deploying AI solutions, 2025 will be the year of proving their worth. With current AI implementations showing efficiency improvements of around 25% (rather than the often-marketed 70-80%), organisations are becoming more pragmatic about their AI investments. The focus will shift dramatically from simply having AI capabilities to demonstrating measurable return on investment.

We expect to see several key developments in the AI space:

• More domain-specific AI models replacing general-purpose solutions
• Decreasing costs as AI technology becomes more efficient
• New applications focusing on hyper-personalisation and proactive customer engagement
• Real-time language translation becoming more accessible and affordable
• Improved analysis of customer interactions for training and quality assurance

However, the human element remains crucial. We anticipate contact centres finding a better balance between AI automation and human interaction, with technology being deployed strategically to give agents more time for complex, emotionally sensitive conversations.

The Evolution of Agent Roles

We’ll begin to see significant shifts in the contact centre agent role throughout 2025, as organisations respond to growing operational complexities. Research shows that typical UK contact centres expect their agents to juggle between five and ten different IT applications during or after customer calls – and that’s on top of standard office applications and web browsers.

This technological overload, combined with increasing customer expectations, is driving a fundamental shift in how we think about the agent role. Research indicates that customers are less satisfied with customer service interactions than ever before, despite the proliferation of new technologies. This paradox highlights the need for a new approach to agent development and deployment. Throughout 2025, we expect to see progressive changes in how agents work and the skills they need.

Key developments will include:

• Enhanced focus on emotional intelligence and complex problem-solving.
• Greater emphasis on using data insights to inform customer interactions
• New training approaches combining technical skills with soft skills
• More sophisticated performance metrics beyond traditional KPIs
• Increased focus on wellbeing and post-difficult-call support

Personalisation Meets Privacy

The drive for personalised customer experiences will continue, but with a crucial twist: finding the balance between customisation and privacy. Studies show that while 76% of consumers say personalised communications are a key factor in considering a brand, and 78% say such content makes them more likely to repurchase, 80% are concerned about how their data is being used. This tension will define how contact centres approach personalisation in 2025.

The key will be implementing what we call “respectful personalisation” – using customer data in ways that enhance service without crossing privacy boundaries. For example, acknowledging a customer’s upcoming holiday booking when they call about travel insurance is helpful; making assumptions about their personal life based on their purchase history is not.

Contact centres will need to:

• Develop clear frameworks for using customer data responsibly
• Implement personalisation that enhances rather than intrudes
• Create transparent policies about AI use in customer interactions
• Balance automation with customer preference for human interaction
• Establish clear opt-in/opt-out processes for data usage

Economic Pressures Drive Innovation

With continued economic challenges expected, 2025 will see contact centres getting creative about efficiency. The impact of the 2025 minimum wage increase to £12.21 per hour, combined with the National Insurance changes, has already pushed many organisations to reassess their operational models.

We anticipate:

• Further exploration of offshore and nearshore options
• Investment in technology that demonstrates clear cost benefits
• More sophisticated workforce management solutions
• Increased focus on first-contact resolution to reduce overall contact volumes
• Creative approaches to training and development that maximise resources

Hybrid Working 2.0

With current data showing that 98% of contact centre leaders expect hybrid working to be standard practice, we’re moving beyond basic remote working capabilities to more sophisticated operational models. After several years of experimentation, and with attrition rates in remote teams running 10% higher than those in hybrid or office-based teams, contact centres are implementing more nuanced approaches to hybrid working.

The focus in 2025 will be on solving the persistent challenges of remote work, particularly around training, culture, and team cohesion, including:

• AI-powered coaching and development platforms for remote agents
• Sophisticated workforce management tools that optimise hybrid team performance
• More nuanced approaches to training and development in hybrid environments
• Enhanced security protocols addressing the specific vulnerabilities of distributed teams
• Improved virtual collaboration tools
• New approaches to maintaining company culture in distributed environments

Data-Driven Decision Making

In 2023, the world generated a staggering 120 zettabytes of data, and this volume continues to grow exponentially. Contact centres are significant contributors to this data explosion, capturing thousands of customer interactions daily across voice, email, chat, and social channels. Yet many organisations are still only scratching the surface of what’s possible with this wealth of information. 2025 will see a dramatic shift in how contact centres approach data analytics.

With more sophisticated analytics tools available, 2025 will see a shift towards more data-informed operations:

• Better integration of cross-channel customer journey data
• More sophisticated prediction of contact volumes and resource needs
• Enhanced ability to identify vulnerable customers
• Improved measurement of customer effort and satisfaction
• Better tracking of resolution rates across channels

Regulatory Compliance and Security

The regulatory landscape continues to evolve rapidly, with new AI-specific regulations expected to join existing frameworks like Consumer Duty in shaping contact centre operations. The increasing frequency of security incidents – with some recent breaches affecting hundreds of millions of customers – has made security a board-level priority for many organisations.

As technology continues to evolve, so too will the regulatory landscape. We expect:

• New AI-specific regulations and compliance requirements
• Enhanced data protection measures, especially for AI applications and hybrid working environments
• Stricter requirements around customer vulnerability identification and support
• More rigorous security protocols for third-party integrations

Looking Ahead

2025 promises to be a year of practical innovation, where contact centres focus on getting real value from their technological investments while adapting to economic pressures. Success will come from finding the right balance between efficiency and effectiveness, automation and human interaction, personalisation and privacy.

The winners will be those who can navigate these competing demands while keeping sight of what matters most: delivering excellent customer service in a way that’s sustainable for both the business and its employees.

Key Areas to Watch:

• The evolution of AI from novelty to necessity
• The changing role of contact centre agents
• The refinement of hybrid working models
• The balance between cost efficiency and service quality
• The development of new industry regulations
• The impact of economic pressures on service delivery

While challenges certainly lie ahead, the contact centre industry has repeatedly shown its ability to adapt and innovate. We expect 2025 to be no different, as organisations continue to evolve their approach to customer service delivery.

Remember, the most successful contact centres will be those that can maintain their agility while staying true to their core mission of providing excellent customer service. The technology and tools may change, but the fundamental importance of human connection in customer interactions remains constant.

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The rise of AI is revolutionising industries across the globe. In healthcare, it’s personalising treatment options. In retail, it’s creating tailored offers. In manufacturing, it’s streamlining supply chains. And in call centres, it’s changing the game entirely.

Tools like ChatGPT have shown how AI can handle complex queries, learn from interactions, and deliver lightning-fast responses. For contact centres, this isn’t just exciting, it’s essential.

High call volumes, repetitive tasks, and increasing customer expectations for fast, accurate resolutions put immense pressure on agents. Balancing these demands while delivering quality and improving performance is no easy task.

AI is the solution. By automating routine tasks, providing actionable insights, and enhancing agent performance, AI helps call centres boost efficiency, improve customer satisfaction, and empower teams to succeed.

In this article, we’ll discuss the impact of AI in contact centres, and the need for organisations to take a wider view of this evolving technology. When departments collaborate to create seamless AI integration, the whole business feels the benefit.

How is AI used in call centres today?

AI chatbots

The most obvious use of AI technology in contact centres is AI-powered chatbots. AI-powered chatbots have reshaped self-service, offering lifelike and personalised support through Natural Language Processing (NLP).

They can:

• Deflect routine queries: By resolving common issues without human intervention, chatbots free up agents for complex tasks.
• Provide tailored responses: Integrating with CRM systems, they personalise conversations based on customer history and preferences.
• Work around the clock: Available 24/7, customers get support anytime they need it.

With 80% of customers wanting better self-service options, AI chatbots meet this demand, reducing inbound call volumes, cutting costs, and enhancing customer experience.

AI speech analytics

AI speech analytics transcribes calls into searchable text files, streamlining QA processes and call reviews. Unlike manual reviews, which often cover a small percentage of interactions, AI can transcribe 100% of calls into searchable text files. Text is much faster to review compared to speech files, which means that QA teams can assess more calls than they would with a traditional manual process. This provides actionable call data and insights on a much wider scale.

Here’s what else AI-powered speech analytics can do for your call centre:

• Sentiment analysis: Understand customer emotions in real-time, flagging issues before they escalate.
• Compliance monitoring: Check agents meet regulatory requirements by tracking mandatory phrases within transcripts.
• Performance insights: Identify knowledge gaps and areas for improvement to enhance team performance.

These insights help contact centres optimise operations, improve agent effectiveness, and make data-driven decisions that have a positive impact.

AI analytics, automation & optimisation

AI automates repetitive tasks, streamlines workflows, and supports agents in delivering exceptional service.

Here are some examples of how AI and automation work together:

• Skill-based routing: Automatically connects customers with the most qualified agents for their needs.
• Real-time data access: Provides call summaries, keyword tracking, and sentiment insights for better team management.
• Workforce optimisation: Simplifies scheduling and forecasting, so resources match fluctuating workloads.

By handling routine tasks, AI allows agents to focus on high-value interactions, improving productivity and customer journeys.

The fear of change

Despite its benefits, AI still faces scepticism. People naturally wonder if it will live up to the hype and question what potential downsides it might bring.

For AI, much of the anxiety centres on data privacy and security. AI tools rely on analysing vast amounts of personal information to uncover trends and patterns. But what happens when an AI system has processed all the available data? How can organisations ensure this data isn’t misused or repurposed in ways that customers didn’t consent to?

This isn’t just science fiction. The debate around data privacy in an AI-driven world is real, leading to the emergence of innovative solutions like machine unlearning-a new field aimed at enabling AI systems to “forget” sensitive information completely. Initiatives like the Machine Unlearning Challenge push the boundaries of this technology, helping businesses comply with strict regulations and safeguard customer trust.

IT and CX collaboration: The key to successful AI implementation

While data protection is a crucial consideration for AI adoption, it’s just one piece of the puzzle. Successful AI implementation requires collaboration between IT and customer experience (CX) teams to address key questions:

• How will the data that drives AI be sourced, stored, and integrated?
• How will data flow seamlessly across disparate systems?
• How can patterns and trends identified by AI be turned into actionable insights?
• What specific outcomes should AI achieve?

An AI tool is only as effective as the infrastructure that supports it. CX teams must clearly define the organisation’s goals for AI-whether it’s enhancing customer satisfaction, improving agent efficiency, or boosting operational performance. IT teams, in turn, need to ensure the systems are robust enough to handle integration, data flow, and scalability.

When these teams work together, AI tools can seamlessly align with contact centre processes, enhancing both operations and customer satisfaction. Feedback loops between CX leaders and IT departments ensure AI solutions are continually refined to address real customer challenges and pain points.

By embracing collaboration and tackling implementation strategically, businesses can harness the transformative power of AI while safeguarding the trust of their customers.

So, what does the future of AI look like in call centres?

The future of AI in call centres promises even greater efficiency and customer satisfaction. AI will power more tailored customer journeys, automating support processes and empowering seamless self-service for a larger share of queries.

However, AI won’t replace human agents. Instead, it will redefine their roles, allowing them to focus on complex and sensitive interactions. Skilled agents will always be essential for delivering empathy and understanding in emotional or high-stakes conversations.

AI’s continued evolution will uncover deeper customer insights, support predictive analytics, and refine training tools. AI will support contact centres to deliver exceptional service and stay agile in a competitive market.

See AI’s transformative power in action with MaxContact’s leading contact centre software. Book a demo today.

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Imagine this: you’re running an outbound call campaign, and 5% of your calls go unanswered. Well, according to our recent benchmark report, this is the reality for 29% of call centres. That’s a lot of wasted time and effort for your agents, not to mention a frustrating experience for potential customers.

This is where Answering Machine Detection (AMD) comes in. Answering Machine Detection can improve efficiency and boost your outbound campaign performance.

The Problem: Unanswered Calls and Voicemail Monotony

Let’s face it, outbound calls can be a challenge. Agents spend a significant amount of time leaving voicemails that may never be heard. And this leads to frustration on both ends.

• It leads to agent inefficiency: Your agents spend time waiting for the customer to answer the phone, only to be met with a voicemail prompt. This not only eats into their productivity but can also be demotivating.
• It leads to customer frustration: Nobody enjoys unanswered calls or overflowing voicemails. AMD helps ensure you reach live prospects, leading to a more positive customer experience.

The Solution: Introducing Answering Machine Detection

AMD is a game-changer for outbound call centres. Answering Machine Detection uses advanced technology to differentiate between live answers and answering machine greetings, allowing you to connect with real people, fast.

How Does Answering Machine Detection Work?

1. AMD analyses incoming audio signals for patterns typical of answering machines, like pre-recorded greetings, long pauses, and background noise.
2. Smart algorithms identify these patterns with high accuracy, allowing AMD to distinguish between live callers and machines.
3. AMD utilises various detection techniques like silence detection and keyword spotting to make its call.

When Should You Use Answering Machine Detection?

Answering Machine Detection can support many different outbound campaign scenarios.

Large Outbound Campaigns

The time and cost savings you can achieve by connecting only with live prospects in large campaigns are sizable. AMD streamlines the process, maximising agent productivity.

High Volume, Low Interaction

For quick, targeted messages in high-volume campaigns, AMD ensures you reach an actual person right away. No more wasting time on unanswered calls.

Standardised Voicemail Drops

If your campaigns involve pre-recorded voicemail messages, AMD helps avoid leaving unnecessary voicemails that get lost.

No matter your campaign type, AMD helps maximise agent talk time and overall campaign success by focusing on live connections.

Why Does Answering Machine Detection Matter?

Answering Machine Detection (AMD) offers significant benefits to contact centres, boosting efficiency and improving customer experience. But let’s not ignore the controversy surrounding its use.

AMD has faced criticism in the past due to its potential for generating ‘silent calls.’ Inadequate systems with high false positive rates can mistakenly identify live callers as answering machines, resulting in calls being disconnected without a message being left. This issue has led to regulatory scrutiny, with Ofcom considering false positive rates when calculating drop rates.

Despite these challenges, AMD remains a valuable tool when used correctly, and the benefits of AMD extend to both your contact centre and your customers:

• Increased Agent Talk Time: Spend less time on voicemails and more time on connecting with live leads.
• Improved Customer Experience: Reduce frustration for your customers by reaching them directly. AMD ensures they receive your message, not just another voicemail.
• Higher Conversion Rates: By connecting with the right people at the right time, you increase the chance of converting leads into customers.
• Cost Savings: AMD saves you money by reducing call time and agent resources spent on voicemails. It’s a win-win!

So, while the risks of misuse are evident, the potential rewards of effective AMD implementation are substantial. And, by choosing a trusted AMD solution with high accuracy rates like ours, the risk of silent calls can easily be mitigated.

Choosing a CCaaS Solution With the Best AMD

The benefits of Answer Machine Detection solutions can’t be ignored. But if you’re considering adding the feature to your outbound capabilities, be mindful that not all CCaaS solutions are created equal when it comes to effective AMD (resulting in the ‘silent calls’ and high false positive rates mentioned above).

So, if you want effective AMD, here’s what to look for:

Speed

When fast and accurate detection is crucial, speed matters. You want an AMD solution that works quickly to maximise efficiency.

Accuracy

Reduce errors to avoid missing valuable connections. Look for Answer Machine Detection with a high accuracy rate.

Campaign Flexibility

Every outbound campaign is different. Your AMD feature should adapt to different campaign needs. Choose one that can handle diverse dialling strategies.

Combining AMD with Data Analytics

Take your Answer Machine Detection utilisation to the next level by combining it with data analytics. Analyse call data to optimise campaign strategies and improve AMD effectiveness. Remember, AMD is a powerful tool, but data insights help you use it to its full potential.

Answering Machine Detection is no longer a luxury, it’s a necessity for successful outbound campaigns. By implementing AMD, you can boost agent productivity, improve customer experience, and ultimately achieve higher conversion rates.

Ready to see how MaxContact’s Answer Machine Detection can transform your outbound campaigns? Book a demo.

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Which is the best dialling mode? There isn’t a simple answer, because it depends on the use case. The right dialling mode is the one that best meets the requirements of a particular campaign or customer demographic.

A dialler is simply a piece of software that automatically places calls to customers, but it can do that at different speeds and in different ways. The best way isn’t set because it changes depending on why and who you are calling. Ideally, your outbound dialleranswe will offer three modes which you can switch between as circumstances dictate.

For an overview of diallers, read our blog: Demystifying diallers – what they are and how they operate

Three dialler modes

The three main dialler modes are predictive, progressive and preview dialling. Ultimately, they all place calls automatically, so your agents don’t have to waste time dialling numbers or waiting for connections.

And they all share various features that help call centres operate efficiently. For example, they all offer call back management services, so customers who don’t answer or who do but can’t talk at that time are administered appropriately. At the same time, good call back management will ensure no customer gets called more frequently than regulations allow.

Good diallers in all modes will also recognise when calls are answered by answer machines and take appropriate action (such as leaving a pre-prepared message), without agents having to become involved in the call – this is called Answer Machine Detection (AMD).

In fact, the three modes share many similarities. But their differences are fundamental, and make each more suited to certain types of call and campaign. We explain the differences and their use cases below.

Predictive dialling

Predictive dialling is perhaps the ‘classic’ outbound call centre dialling mode, helping agents work through large databases of numbers, often as part of a mass market sales campaign.

How does predictive dialling work?

Predictive mode dials multiple numbers at the same time, and then matches answered calls to available agents. You can adjust the rate at which the dialler places calls, but speed and efficiency are of the essence with predictive dialling.

What are the benefits of predictive dialling?

Predictive dialling uses a sophisticated algorithm to estimate the number of calls that are likely to be answered and the number that are likely to ring off or connect to answering machines. It continually adjusts the rate of dialling as the algorithm gathers more information. Because a percentage of calls won’t be answered, it dials multiple numbers at the same time, ensuring agents spend as much time as possible talking to customers. It is the most intensive dialling mode but also the most efficient.

Who uses predictive dialling?

Predictive dialling is the gold standard for straightforward, high volume sales campaigns. It can quickly and efficiently work through large datasets, making sure leads are contacted while they’re still warm. Predictive dialling is about making every call count, and ensuring agents are always doing what they do best – talking to customers and leads.

Progressive dialling

Progressive diallers are auto diallers that only dial a number when an agent is available to take the call.

How does progressive dialling work?

Instead of calling multiple numbers at the same time, the system only calls the next number when the previous one is finished, or the agent indicates they are ready for the next call. Dialling is instant and automatic at that point, reducing wait time between calls.

What are the benefits of progressive dialling?

By slowing the pace down a little, the system still allows for a relatively high number of calls, but also eliminates the risk of customers abandoning calls or waiting a frustratingly long time before being connected to an agent. With progressive dialling, there is always an agent free to talk when a call is answered. That’s not always the case with predictive dialling, when customers may have to wait before being connected to an available agent.

Who uses progressive dialling?

Progressive dialling is often used in more targeted sales campaigns, or those involving higher value goods or services. Smaller, more focused data sets mean cost per call pressures are not so severe, and having an agent available when calls are answered is of paramount importance. After sales service teams may also prefer progressive dialling.

Preview dialling

Preview dialling automates call placing but only after agents have had time to gather and absorb information about the call recipient.

How does preview dialling work?

When an agent indicates availability, information about the next call is sent to the agent for preview. After a set amount of time the number is automatically dialled. The purpose of this delay is to let the agent prepare for the call, using information typically taken from the company CRM system.

What are the benefits of preview dialling?

The benefits of preview dialling are the time agents are allowed to prepare for a call. They can review all previous contacts with a customer and any other information stored on the firm’s CRM system. That stops customers having to repeat information they’ve already given and also leads to more personalised conversations.

Who uses preview dialling?

Preview diallers are particularly helpful when the reason for the call is complex or sensitive. That could be a debt resolution call, or a call responding to a customer complaint. Agents get to rehearse answers and tighten scripts before the call is connected.

Choosing the best dialling mode for your call centre

So which dialling mode is best for your call centre? Ideally, your system will allow you to switch between all three, but here are the questions to ask before choosing the right one at any given time.

Which dialler mode is best for cold calling?

It depends on the data set and what is being sold. For commodities and utilities, predictive dialling that can speed through large data sets efficiently is usually the best option. For higher value or B2B sales, progressive dialling may be preferable.

Which is the fastest dialling mode?

Predictive dialling is the fastest mode, because it calls more numbers than agents and connects agents as soon as they become available.

Which is the best dialler for current customer campaigns?

Progressive dialling is a low risk option that can improve customer experience, help nurture loyalty and effectively help agents upsell additional products and services. Because an agent is always available to have a conversation, the customers you have painstakingly nurtured over a period of time feel valued.

If we deal with more complicated calls or B2B campaigns, which dialling mode would be best?

In these instances you need to slow the pace of calls down and ensure agents are well informed about the reasons for the call or the product or service being sold. We’d recommend preview dialling for these types of calls.

My team deals with high-volume sales campaigns so which dialling mode should we use?

Predictive dialling will allow your team to get through a lot of calls in a short space of time, while keeping cost per call rates at a minimum.

Which dialling mode would help us maximise efficiency? It’s a key aim for our business

That depends on the circumstances. Predictive dialling places the most calls. But call speed efficiency counts for nothing if valued customers require a more personalised service, in which case an efficient call centre might be one that uses progressive or preview dialling. Take this on a case by case basis.

We’re looking for a dialler/dialling mode that will reduce the chance of dropping outbound calls. Which would be the most appropriate option for us?

MaxContact is your friend here. Our sophisticated customer engagement solution will keep dropped calls to an absolute minimum (in fact, close to zero), while helping you remain compliant.  

The verdict

The right dialler mode depends on the reason for the call and who you are calling. Predictive dialling works efficiently through large cold call data sets, progressive dialling reduces the risk of dropped calls and preview dialling allows for more personalised conversations. Each has huge advantages over manual dialling, but call centres must choose the balance of speed, preparedness and personalisation that best suits their needs.

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As we approach the end of 2024, it’s time to look back at our predictions from last year and reflect on how the contact centre industry has evolved. While some trends played out as expected, others took unexpected turns, and new challenges emerged that shaped the industry’s direction.

AI: From Hype to Reality

We predicted that 2024 would be the year AI moved from the “excitement phase” to the “deployment phase.” This proved largely accurate, though perhaps not in the way many expected. The rush to implement AI solutions in early 2024 revealed important lessons about the technology’s current capabilities and limitations.

The reality check came quickly: while AI showed promise, its productivity improvements landed closer to 25% rather than the marketed 70-80%. Auto-summarisation emerged as the unexpected hero, delivering the most tangible value among AI applications. This taught us an important lesson: sometimes the most valuable AI solutions are the ones that enhance existing processes rather than completely revolutionising them.

Security and Compliance: More Critical Than Ever

Our prediction about security and compliance becoming front and centre proved remarkably accurate. The year saw several significant security incidents that highlighted the vulnerability of customer data, including Transport for London’s widespread system disruption and Ticketmaster’s massive data breach affecting over half a billion customers. These high-profile cases served as sobering reminders of the critical importance of robust security measures.

The SaaS-driven nature of modern contact centres amplified these concerns, as a single breach can now impact entire client networks simultaneously. This catalysed a fundamental shift in how the industry approaches data protection, particularly around AI models and their implementation. The full implementation of Consumer Duty in July 2024 added another layer of complexity, requiring financial services contact centres to demonstrate how they’re promoting fair customer outcomes and increased transparency in every interaction.

The conversation evolved beyond basic compliance checkboxes to encompass deeper ethical considerations about data usage, ownership, and customer profiling. This regulatory evolution, combined with heightened security awareness, has prompted many organisations to reassess their data practices, especially as AI technologies become more deeply embedded in customer service operations.

Hybrid Working: Still a Work in Progress

While we predicted that 2024 would be the year contact centres refined their hybrid working models, the reality showed that this journey is far from complete. With over 60% of contact centres now incorporating home working, the industry continues to grapple with challenges around maintaining company culture, effective onboarding, and managing attrition rates.

Sustainability and CSR: Economic Realities Bite

Our prediction that Environmental, Social and Governance (ESG) and Corporate Social Responsibility (CSR) would take centre stage in 2024 proved to be one of our more challenging forecasts. While we anticipated growing pressure on contact centres to demonstrate their commitment to sustainability and social responsibility, economic headwinds forced many organisations to reprioritise their initiatives.

The tough macroeconomic climate saw sustainability taking a back seat for some contact centres to immediate operational concerns, mirroring broader trends across industries. This shift was evident in the scaling back of net-zero commitments and the reprioritisation of resources toward cost management and operational efficiency.

However, this doesn’t mean sustainability has lost its importance. Rather, organisations have had to become more pragmatic in their approach. Hybrid working, initially championed as a way to reduce carbon footprints, has become more valued for its operational benefits and cost savings. This demonstrates how environmental initiatives can align with business necessities when properly implemented.

Looking back, 2024 taught us that while sustainability remains crucial for long-term success, its implementation needs to be balanced against immediate business survival needs. The challenge going forward will be finding ways to maintain environmental and social commitments while navigating economic pressures.

Customer Experience vs Cost Efficiency: A Delicate Balance

Perhaps our most accurate prediction was about the challenge of reducing costs while improving performance and customer experience. This became the defining challenge of 2024, as inflation and economic pressures forced difficult decisions across the industry.

Throughout the year, we’ve also seen a trend where customer experience initiatives have taken a back seat to cost reduction strategies. The industry’s pivot towards digital deflection, while economically motivated, has sometimes come at the cost of customer satisfaction. This tension between efficiency and experience will likely continue to shape industry decisions going forward into 2025.

Looking Forward

As we end 2024, the contact centre industry stands at a crossroads. The promise of AI remains strong, but with more realistic expectations about its capabilities. The challenge of balancing cost efficiencies with customer experience has never been more acute, and the industry continues to adapt to new working models.

The year has taught us that successful innovation isn’t just about implementing new technology – it’s about understanding our limitations, focusing on tangible value, and maintaining sight of what matters most: delivering quality service to customers while supporting our workforce.

The contact centre industry proved resilient and adaptable in 2024, even if the path forward wasn’t always clear. As we look to 2025, this ability to adapt while maintaining core service values will be more important than ever.

Key Learnings from 2024:

• AI implementation requires focused, realistic goals rather than broad transformations.
• Security and compliance must be built into every new initiative from the ground up.
• Hybrid working isn’t just about technology – it’s about culture and connection.
• The balance between cost efficiency and customer experience requires constant attention.
• Industry evolution must consider both technological and human factors.
• Sustainability initiatives need to demonstrate clear business value alongside environmental benefits.
• Economic pressures can reshape priorities, but long-term ESG commitments shouldn’t be abandoned.

As we move into 2025, these lessons will be crucial in shaping the next phase of contact centre evolution. The industry may face continued challenges, but it has shown it has the resilience and creativity to meet them head-on.

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