Outbound still pays - your customers just need a smarter approach
High-volume cold calling is losing ground. Here's what a high-performing, data-led outbound strategy looks like - and how to sell it to your customers.
High-volume cold calling based on limited data is no longer a cost-effective outbound strategy and in the B2C world can be non-compliant.
With both sales and debt collection, the public has grown wary of unsolicited calls and generic conversations. But that doesn’t mean outbound dialling is over as a revenue engine.
It means it has to be smarter, multi-channel and data-led. Based on real-time information and a refined dialling strategy. Often personalised in tone, timing and approach.
So, if you’re reselling UCaaS today, there’s a strong chance your customers’ outbound results are being held back by the platform they’re on. When revenues stagnate, contact rates fall or conversions get harder to close, the problem usually isn’t effort - it’s strategy, data and tooling. This blog sets out what a high-performing outbound operation looks like, so you can have that conversation with confidence.
The outbound metrics your customers should be measuring
The foundation of any smart outbound strategy is good information. Help your customers understand that without the right data, they can’t tell whether calls are reaching the right people, whether agents are performing, or whether their scripts are working. Measurement isn’t a nice-to-have - it’s where improvement starts.
Outbound KPIs to share with your customers:
• Connect rates: are calls being connected to a real person?
• Contact rate: how often are agents reaching the right decision-maker?
• Data penetration rate: is their data being used effectively - are they making the most of high-value leads?
• Conversion rate: the percentage of contacts that result in a positive outcome
• Calls to success rate: the number of calls needed per successful result
Take conversion rate as a case in point. It tells your customers two things at once: the quality of their contact data, and the effectiveness of their team.
Better data means a higher likelihood of reaching the right person. Skills-based routing - matching the right agent to the right call- increases that further. And stronger training, combined with more refined scripts, means more of those conversations end the way they should.
Qualitative insight matters as much as the numbers
Quantitative KPIs don’t tell the full story.Improving contact rates will generate more conversations - but without the right skills in place to handle them, conversion rates won’t follow.
Encourage your customers to combine the numbers with qualitative insight: what objections are coming up most, what their customers are saying about competitors, and where conversations are breaking down.Helping them bring both lenses together is one of the most valuable things you can do as a partner - and it’s a conversation most resellers never have.
Industry-specific KPIs worth knowing
The metrics above apply broadly, but it’s worth helping your customers zone in on numbers that are specific to their sector.
In debt collection, promise to pay (PTP - the percentage of calls resulting in a commitment to pay) and percentage of debt collected are key indicators. In sales, first-call close rates and average revenue per call say a lot about campaign effectiveness.
MaxContact’s KPI Benchmark Report gives a detailed breakdown of what good looks like across sectors. It’s a useful resource to share with customers who want to know how their numbers stack up.
Benchmarking: what good looks like
Once your customers know what to measure, the next step is helping them understand what the numbers mean.
MaxContact’s own research found that the largest proportion of respondents - 34%, across both sales and debt collection - reported conversion rates of between 10% and 19%. Cold outbound sales calls typically convert at 1–3%; warmer, more targeted calls can reach as high as25%.
Broad benchmark ranges for common outbound KPIs:
• Average handling time: 4–12 minutes
• Contact rate(cold calls): 5–15%
• First call resolution: 10–40%
These are broad ranges and will vary significantly by sector and product complexity. The more important thing for your customers is to track their own numbers consistently over time - and to understand what’s driving movement in either direction.
What your customers can do to improve outbound performance
Once your customers are tracking the right metrics,the focus shifts to moving them. Here are the levers most likely to make a meaningful difference - and the conversations worth having:
• Team training and coaching - conversation analytics can surface objection patterns, benchmark individual and campaign performance, and show exactly where coaching will have the biggest effect.
• Smarter dialling strategy - when are their contacts most likely to answer? Are they prioritising by lead value? Are they using the right dialler mode for the campaign? These are practical questions you can help them think through.
• Omnichannel engagement - how does combining SMS, email and calls affect contact and conversion rates? Could AI agents handle routine calls while human agents focus on more complex or sensitive interactions?
The performance advantage you can offer your customers
Helping your customers understand and act on their outbound performance data is a powerful way to open the door to a bigger conversation. Standard UCaaS platforms can’t offer the range of insight and capability that a specialist customer engagement solution like MaxContact provides - and once customers seethe gap, the case for change makes itself.
Think conversation analytics, AI chatbots, workforce management, intelligent outbound dialling and sophisticated contact strategies - capabilities that standard UCaaS systems simply can’t match, and that enterprise-grade platforms price out of reach for most teams.
MaxContact delivers measurable results - from 200–300% increases in contact rates to doubling sales teams’ conversion rates. Benchmark Insights Report.
That’s because its intelligent, intuitive platform lets teams build smarter outbound strategies and tailor them for every campaign.
Talk to the MaxContact partner team about adding a specialist customer engagement solution to your portfolio. Book a call
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September 29, 2025
5 Must-Have Dialler Features You Need In Your Outbound Call Centre
Whether you’re looking to supercharge sales, streamline debt collection, or elevate customer service, the right outbound dialler can redefine how you connect and communicate. So, continue reading to learn more about automated diallers and discover the potential they hold for your contact centre’s success
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Put simply, outbound dialling is the process of making calls to customers or contacts, typically for sales or marketing purposes.
While outbound dialling can be performed manually on a mobile or business phone, this is not practical when dealing with a high volume of calls. A range of additional features can enhance outbound calling in a contact centre setting through the use of an automated dialler.
What does an outbound dialler do?
An outbound dialler is generally a cloud or software solution that automatically dials phone numbers and makes calls on behalf of your sales, collection or customer service teams. As such, it’s an essential ingredient in any organisation where you need to make outbound calls to clients and prospects throughout the day.
What are the different types of call centre diallers?
The main options are a manual dialler and an auto dialler.
Manual Dialler
A manual dialler is like a traditional phone. A call agent manually dials numbers from a call list, one after another.
Auto Dialler
As the name suggests, an auto dialler automates much of the dialling process. It digitally dials numbers, and can also dial multiple numbers at once, passing answered calls to available agents.
Manual vs Auto Dialler
Why would you choose one over another? Most call centres now opt for auto dialling, because it significantly boosts productivity. Agents spend more time talking to customers and less time dialling unresponsive numbers.
Manual dialling can still be useful, but only for campaigns involving a small number of high value customers who demand a more personal approach.
The different outbound dialler modes
If you’re using an auto-dialler, there are likely three dialler modes that you’ll frequently use, depending on the type of outbound calling you are doing. These are predictive diallers, progressive diallers and preview diallers.
What is it? When most people think of outbound dialling software, they tend to think of predictive dialling. Predictive dialling places calls based on the software’s predictions of agent availability. It dials multiple numbers simultaneously, so that when agents finish one call they can be instantly connected to the next.
What are the benefits? The best predictive diallers minimise abandoned calls (and the amount of time customers spend on hold) and maximise the time your agents spend having conversations. When should I use it? Predictive dialling is the standard for straightforward, high volume sales campaigns (like commodity sales) or debt collection activity.
What is it? Progressive diallers are predictive diallers that slow the pace down by only dialling a number when an agent is available to take the call. Dialling is instant and automatic, so the system still allows for a relatively high number of calls.
What are the benefits? Progressive dialling eliminates the risk of customers abandoning calls or waiting a frustratingly long time before being connected to an agent. Because an agent is always available, the customers you have painstakingly nurtured over a period of time feel valued and importan
When should I use it? It is often used in campaigns that target current customers. It’s a low risk option that can improve customer experience and effectively help agents upsell additional products and services.
What is it? A preview dialler takes the pace down another notch. When an agent indicates availability, information about the next call is sent to the agent for preview.
After a set amount of time – say, one minute – the number is automatically dialled. This delay lets the agent prepare for the call, using information typically taken from the company CRM system – which are often integrated into the dialler.
What are the benefits? Agents can have more in-depth, focused conversations, based on a customer’s real experiences and challenges. It can improve customer experience and increase the number of positive outcomes.
When should I use it? Preview diallers are particularly helpful when the reason for the call is complex or sensitive. For example, following up with web leads or dealing with customer complaint calls.
Outbound diallers can be integrated into many industries. Any company with an outbound contact centre who are cold calling or making high volume phone calls can benefit from outbound dialler software.
Power up your sales teams
Sales campaigns are often high volume and low touch. Predictive dialling is the gold standard for straightforward, high volume outbound campaigns (like commodity sales). It can quickly and efficiently work through large datasets, making sure leads are contacted while they’re still warm.
The best predictive diallers minimise abandoned calls (and the amount of time customers spend on hold) and maximise the time your agents spend having conversations. They can be set to play messages if they meet an answerphone, and will recycle numbers (placing unanswered calls back into the call queue) in a way that ensures your customers or leads are contacted, but never pestered.
The right outbound dialler can make selling straightforward by helping to connect your sales people to the right customers at the right time. Combined with the contact centre-specific features mentioned earlier, it can offer powerful tools for contacting customers, winning business and exceeding customer expectations.
Increase debt collection rates
Your credit and debt resolution teams can use effective targeting to reach priority customers at times that suit them. Maximise collection rates using advanced data segmentation and encourage self-serve with automated communications. Automate payments with self-serve options providing customers choice and improving satisfaction.
Preview diallers are particularly helpful when the reason for the call is complex or sensitive. For example, debt collection calls are more likely to end positively if agents have the time to gather all the information they need beforehand.
Elevate your customer service teams
Customer service teams often use progressive dialling to target current customers with after sales information or courtesy communications. It’s 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.
5 must-have outbound dialler features
Answer Machine Detection (AMD)
Answer Machine Detection (AMD) lets your auto-dialler software identify answering machines before connecting calls to agents. This means agents only spend time on live conversations, saving them valuable time and boosting productivity.
AMD is particularly helpful for high-volume sales campaigns where every minute counts. MaxContact’s AMD boasts a 90% success rate in detecting answering machines, freeing up agents to focus on reaching real people.
Speech analytics
Forget manually reviewing call recordings! Speech analytics uses AI to analyse every conversation, automatically identifying customer sentiment, call quality, and agent performance. This lets you:
Spot frustrated or vulnerable customers who need extra care.
Ensure agents follow compliance guidelines.
Understand what customers are saying about your products and competitors.
Speech analytics gives you valuable insights from all calls, not just a select few. It saves time and helps you improve the overall performance of your contact centre.
A secure payment manager
A secure payment IVR gives customers the payment options they want, while giving teams the time they need to deal with more complex or sensitive cases.
Payment automation helps you speed up debt collection and improve cash flow. When you give customers more convenient ways to pay, they’re more likely to stick to payment schedules.
MaxContact’s payment IVR is fully PCI compliant, protecting customer information at all times. We offer both assisted payments, in which staff safely guide customers through the payment process, and automated payments, which are fully self-serve and available 24/7.
Analytics and reporting
You can only improve contact centre performance when you can measure it. When you’ve done that, you need to present the data in a way that is easy to understand and act on. That’s where analytics and reporting come in.
MaxContact’s pre-configured reporting gives you complete visibility around productivity, issue resolution rates, revenue and customer satisfaction, to name just a few. You can set targets for campaigns, channels, teams and agents and track performance over time.
All teams – sales, service and debt resolution – benefit from better information. Pre-configured reports give you the data you need in the quickest and most hassle-free way.
Easy integration
A powerful dialler is even better when it works hand in hand with your existing systems. Imagine a sales agent having instant access to customer history, preferred contact methods, and past feedback – all within the dialler interface (thanks to CRM integration).
This allows for personalised conversations that address specific needs, leading to happier customers and improved outcomes. Easy integration applies to after-sales and debt resolution teams too. By connecting your dialler with other systems, you can put all relevant information at agents’ fingertips, reducing hold times and boosting overall efficiency.
The benefits of auto-dialler software you can’t ignore
Improve contact centre metrics like AHT
Average Handling Time (AHT) is a calculation based on the time agents spend talking to a customer, the amount of time callers are on hold and the time taken on follow up tasks, divided by the number of calls handled. The lower your AHT, the better. It means you can handle more calls, improve efficiency and reduce costs. A good dialler can improve AHT and a host of other contact centre metrics, by allowing agents to handle more calls, more efficiently.
Excel at sales and debt collection
Whether it’s sales or debt collection, the best results happen when good agents talk to customers. Whether it’s a high volume, low touch sales campaign, or more sensitive debt resolution calls, the right dialler means your agents spend more time in conversation with customers, and less time processing unanswered calls or connecting to answering machines.
Keep your contact centre compliant
A powerful predictive dialling algorithm speeds up and slows down depending on the conditions in your contact centre. If fewer agents are available, the dialling slows down, helping to ensure you stay within compliant boundaries for abandoned and dropped calls. Or you can switch to progressive or preview modes for more personal contacts. The dialler can also ensure that the frequency of calls to a contact never exceeds official limits.
Seamlessly integrate with your CMS
A dialler that integrates with your CMS system is a huge advantage. It means that the systems feed information to each other, so your agents always have the details of previous contacts at their fingertips. That reduces the risk of customers becoming annoyed by having to repeat information they’ve already previously given. It can also provide insights into customer satisfaction rates, preferred times and methods of communication and so on.
These companies boosted performance with auto diallers
We worked with these companies to replace ageing systems with modern cloud-based diallers – and the results are impressive.
Compare My Insurance
Compare My Insurance is one of the largest independent insurance and protection specialists in the UK. But dialler downtime, data issues and missed opportunities were hampering the business.
MaxContact’s dialler solution integrated seamlessly with the company back office systems. It has significantly increased contact rates while providing complete transparency around performance and progress.
APJ Solicitors
APJ Solicitors, a leading financial mis-selling specialist, needed to increase call volumes and boost efficiency, but its basic VOIP phone system was no longer up to the task.
MaxContact’s solution increased call volumes by 110% in the first year, and improved average agent call efficiency by 36%. Productivity has risen five fold over the company’s previous solution.
Improve your call centre performance with MaxContact
MaxContact offers the most sophisticated outbound dialler currently available. This continually improving cloud-based dialling solution gives you the flexibility to run your contact centre your way, letting you choose the right blend of productivity and compliance for your business needs. With over a 1,000 unique features, MaxContact’s outbound dialler helps meet your contact centre challenges in new and powerful ways.
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Running an Effective Outbound Call Centre
Running an effective outbound call centre can boost sales, help retain customers and ensure timely payment collection. They are a vital cog in the day-to-day running of many different types of businesses, especially those that rely heavily on sales, lead generation or market research.
Unfortunately, many outbound contact centres run into the same challenges time and time again, from low call connect rates to poor performance and difficulties measuring or handling data.
Whether you run an in-house or outsourced contact centre, solving some of these issues can boost your bottom line.
An outbound call centre is a common business operation that handles outgoing phone calls to current or prospective customers, whether it be for sales, telemarketing, surveys and research, appointment setting, or customer notifications and payments.
Inbound vs Outbound Call Centre
As the name suggests, the main difference between an inbound and an outbound call centre is the type of call. An inbound call centre deals primarily with incoming phone calls, supporting new and existing customers with queries, complaints, bookings, or sales. Meanwhile, an outbound contact centre focuses on outgoing calls, where agents are proactively reaching out to prospects or clients.
Many contact centres operate on both an inbound and outbound basis, depending on the needs of the business.
Since outbound call centre operations face a unique set of challenges, we will focus primarily on those for the remainder of this article. Nevertheless, contact centres with diverse and complex requirements can also benefit from the CCaaS solutions mentioned below.
What are the Challenges of an Outbound Call Centre?
Whether it be cold calling, debt collection, or simply ringing customers to remind them of their upcoming appointments, actually getting through to the desired recipient is one of the main challenges of an outbound call centre.
Meanwhile, data management and compliance pose a different, although equally important problem. Let’s look at some of the common challenges of outbound call centres in more detail, and see how they can be solved with effective CCaaS solutions.
Challenge #1: Low Call Connect Rates
A low call connect rate has the capacity to defeat the entire object of an outbound call centre. If you can’t get through to your recipients, you’re unlikely to see a return on the investment of the operation, whether you’re trying to make more sales, raise funds or collect vital market data.
Problems
Incorrect or outdated contact information: With the wrong information, not only do agents fail to reach the recipient, but also waste valuable time on erroneous calls.
Uninterested recipients: We’re all guilty of hanging up quickly or even ignoring unsolicited calls, but large volumes of uninterested recipients can seriously impact results.
Busy signals and voicemails: Reaching live individuals can be challenging depending on the time of day and individual communication preferences.
Solutions
Predictive Dialling and AMD
Predictive dialling is a powerful tool to boost the number of successful connections, using advanced algorithms to optimise call attempts. The technology works by analysing historical data to predict when agents are more likely to reach the desired recipient.
Meanwhile, AMD (answering machine detection) screens and bypasses calls that go to voicemail to reduce idle time, with software provided by MaxContact seamlessly integrated with your existing infrastructure.
Contact Prioritisation
CCaaS software can also identify the most important calls and put them at the top of an agent’s list, using custom data fetching on your leads. This helps you connect more quality calls with customers or prospects who are less likely to hang up.
Outbound Skills-Based Routing
This clever functionality supercharges your campaign results by intuitively matching customers with their ideal agents.
Outbound skills-based routing is a relatively new technology that works across progressive, predictive and preview campaigns to connect customers with agents who have the relevant skills to handle the call. Live-call data is used to assign skill ratings to agents.
Challenge #2: Inefficient Agent Performance
While performance is on some level, determined by the individual agent, there are still plenty of things you can do to increase efficiency and motivation.
Problems
High call volume and workload: When there is a high call volume to keep up with, agents can experience stress and burnout, leading to a significant drop in performance.
Lack of proper training: Some call centres lack the resources to provide personalised agent training, meaning they don’t have the necessary skills and knowledge to handle a variety of call types and objections effectively.
Inadequate scripting and resources: Poorly designed scripts or a lack of training and support resources are guaranteed to reduce productivity and ultimately, results.
Solutions
Automated Scripting and CRM Integration
An excellent feature of MaxContact CCaaS is the built-in scripting tools, which help agents handle calls efficiently and consistently with confidence in their script.
Meanwhile, integration with your existing CRM software helps agents easily personalise calls, with all the relevant information at their fingertips.
Call Recording and Data Insights
Using a CCaaS platform to record calls helps supervisors easily identify areas for improvement and provide tailored training to agents, boosting their skills and effectiveness.
Data Dashboards and Performance Management
Most modern CCaaS platforms feature data and performance dashboards which can encourage a more engaging work environment and introduce a dose of healthy competition. They use gamification elements to boost motivation and track progress.
Challenge #3: Difficulty Measuring Success
Collecting information about what works and what doesn’t is one of the only ways to tailor your approach to your unique customer base and operations, improving success exponentially. But collecting and organising that information can be a headache waiting to happen, and is often deprioritised as a result.
Problems
Multiple success metrics: Many campaigns have more than one goal, and monitoring conversion rates, appointment bookings, or survey responses simultaneously can be challenging.
Attribution challenges: It can be difficult to attribute specific outcomes to outbound calls as a range of other marketing efforts and customer touchpoints can also play a role.
Lack of data-driven insights: Without comprehensive, readily available data, it’s difficult to make decisions to optimise call centre performance.
Solutions
Automated Analytics
Using CCaaS software that has automated analytics built-in is a simple way to optimise your campaign strategies. MaxContact provides custom solutions with the capacity to collect and present automated data insights from a range of performance metrics such as call volume, agent utilisation, and call duration.
Multi-Channel Reporting
Taking it one step further, CCaaS can also facilitate data analysis across a range of different communication channels when integrated with your existing software. This provides a holistic view of customer interactions across all touchpoints, helping you gain a broader view of campaign performance.
Challenge #4: Compliance and Security
Breaches of compliance or security can be incredibly costly to an outbound call centre operation. But staying on top of ever-changing regulations can be just as pricey and time-consuming, without one streamlined solution.
Problems
Complying with Do Not Call (DNC) lists: Dialling someone on the DNC list can result in hefty fines and penalties if you’re not careful.
Taking payments quickly and securely: If your outbound call centre deals with payments, calls can be vulnerable to security breaches, damaging your reputation and leading to a significant loss of revenue.
Solutions
Built-in Regulatory Compliance
Having a CCaaS platform with built-in regulatory features is one way to avoid the compliance nightmare altogether.
MaxContact software features innovative DNC list scrubbing to automatically remove all names and contact information that appears on the registry from your database, reducing the likelihood of a fine. It also keeps your system up-to-date with call recording compliance and allows you to locate, edit or remove someone’s information on one simple page.
Secure Payment Handling
Take payments quickly and securely with PCI-DSS (Payment Card Industry Data Security Standard). The MaxContact CCaaS system allows agents to handle payments without viewing or hearing the specific card information of the customer. Instead, they can securely input their details using their keypad.
Data Encryption
Implementing robust security features into your CCaaS system is the best way to proactively protect against a potential breach. Depending on your operational needs, you can add a range of special features such as data encryption, access controls, and regular audits to safeguard sensitive customer information.
Outbound call centre outsourcing is incredibly common, but BPOs often face more challenges than those that operate in-house. These include:
Data Security and Privacy: BPOs that deal with sensitive customer data may face heightened concerns about privacy and compliance. This means they often require even more robust security measures and special technology to stay compliant with data protection regulations.
Geographical limitations: Outbound call centre outsourcing puts distance between the business and its end customer, which sometimes makes it difficult to maintain performance and service quality. Auto quality assurance (QA) can assist in providing continued support to an outsourced team and connect the dots between the client and their customers.
Running an Effective Outbound Call Centre: Final Thoughts
While not without its challenges, running an effective call centre can be a lot easier with the right tools, technology and knowledge on your side.
Get in touch today to start running your outbound contact centre more efficiently, or download our guide for more information.
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Is Your Outbound Sales Team Truly Data-Driven?
Most outbound sales teams would describe themselves as “data-driven”. They track activity, review performance reports and measure success against targets.
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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 efficiencyexplores how performance indicators combine to drive overall effectiveness.)
Key benefits for outbound sales teams include:
Enhanced Agent Training: Identify successful techniques and areas for improvement, allowing for targeted training programmes.
Customer Sentiment Analysis: Detect changes in tone and emotion, helping agents adapt their approach in real-time.
Quality Assurance at Scale: Analyse every call, ensuring comprehensive QA and quick identification of compliance issues.
Identifying Sales Opportunities: Recognise patterns in successful calls to refine sales scripts and strategies.
Competitor Intelligence: Flag mentions of competitors, providing valuable market insights.
Trend Identification: Quickly spot emerging trends in customer behaviour or common objections.
By implementing speech analytics, outbound sales teams can gain data-driven insights that lead to more effective strategies, improved customer experiences, and better business outcomes. Use these insights to identify common objections, spot successful sales techniques, and provide targeted coaching to your team. A recent study by Forrester found that companies using AI-driven speech analytics saw a 10% increase in customer satisfaction scores and a 15% improvement in first-call resolution rates.
With speech analytics, you’re not just collecting more data – you’re gaining the ability to understand and act on the nuances of every customer interaction, transforming your outbound sales operation into a truly data-driven powerhouse.
Sustaining data-driven outbound sales performance
When combined with performance data, conversation analytics closes the loop between insight and action. Conversation analytics doesn’t sit alongside metrics. It explains them and enables more confident decisions and continuous improvement.
Using more tools or tracking additional metrics doesn’t automatically make an outbound sales team data-driven. Data only becomes valuable when it actively guides decisions across the contact strategy, from how calls are dialled, and leads are prioritised, to how agents are routed, coached and optimised.
In genuinely data-driven teams, agents and managers understand what key metrics mean, how they influence outcomes and when intervention is needed. Performance reviews focus on interpreting trends and agreeing on clear next actions, rather than simply reporting on results after the fact.
The most effective outbound sales teams connect data. By linking real-time performance insight with intelligent technology and informed decision-making, they improve results while activity is still in progress, not once opportunities have already passed.
If you want to understand how your outbound sales performance compares to other UK contact centres, benchmarking is the most effective next step.
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If you run a contact centre, the chances are you're managing rising call times, inconsistent quality reviews, repeat contacts that erode margin, and a personalisation gap that's hard to close without the right data infrastructure underneath it.
None of these are new problems. But the distance between where most operations are today and what's now achievable is narrowing fast - and the teams pulling ahead aren't waiting for a full platform overhaul to make it happen.
At MaxContact's recent webinar, hosted by Marketing Director Kayleigh Tait and Principal Product Manager Conor Bowler, we worked through four specific challenges that are costing contact centres time and money right now - and showed, live, how AI is solving each one. Here's what we covered.
Challenge 1: Call length is rising, and post-call admin is a big reason why
Average service call duration in the UK is now 422 seconds - seven minutes per call - according to Contact Babel. That's the highest figure recorded in 20 years of data collection, and it's been climbing steadily since 2004. There's no sign it comes down on its own.
A large part of the reason is fragmentation. 96% of agents are still navigating multiple systems on every single call. Only 4% of UK contact centres operate from a single unified desktop. 40% of agents are juggling more than four applications at once - doing real-time system-surfing while simultaneously trying to solve a customer's problem or make a sale.
Then there's wrap time. 18% of every call is post-call admin: writing up notes, updating records, triggering next steps. That's queue time growing while your agents do data entry.
The commercial impact is significant. For a 50-agent contact centre making 50 calls a day, a 50% reduction in wrap time is worth over £175,000 a year - based on MaxContact's own ROI modelling.
What good looks like:
An agent wrap-up summary that generates automatically within seconds of a call ending, built from a live stereo transcript that's already separated the agent's voice from the customer's. The agent reviews it, makes any edits, and submits. No blank page. No three to five minutes of typing between every call.
MaxContact's Agent Wrap-Up Summary feature — currently in alpha testing and moving to beta in mid-June — does exactly this. Prompts are fully configurable via Prompt Studio, so the output format, structure, and language match your operation's context, whether that's a collections agency, a sales team, or a customer service function.
Challenge 2: Repeat contacts are eroding margin and driving churn
42% of UK consumers have already switched provider because of a poor contact centre experience - not because of a product issue, but because of the experience itself. A further 38% have seriously considered it. MaxContact's consumer research, shared at the After Work with MaxContact event, makes clear this isn't an edge-case risk.
First contact resolution is what Contact Babel calls the "miracle metric." It's consistently cited as one of the top two KPIs most influential on customer satisfaction. Every repeat call is a direct hit on that number - and at roughly £5 per service call, a repeat contact doubles your cost before you've factored in agent time and churn risk.
The AI angle here is often misunderstood. 69% of customers rate AI worse than humans for understanding their issue - but the problem usually isn't the AI itself. It's where it's introduced in the customer journey. AI deployed in an emotionally charged or complex situation will struggle. The bigger failure point is the handover: when a customer escalates from an AI interaction to a human agent and has to repeat everything from scratch. That's where trust breaks.
What good looks like:
Context continuity. When a human agent picks up - regardless of whether the previous interaction was with an AI agent, a chatbot, or a colleague - they start with the full picture. Customer history, intent, what happened last time, what was agreed. Not a blank screen.
That requires clean data flowing across your channels and a single interface for agents to work from. It's a foundational requirement, not an aspirational one.
Challenge 3: QA based on a sample of 1–2 calls per week isn't good enough
The average contact centre reviews one to two calls per agent per week. Contact Babel's most recent guide describes this explicitly as "neither fair nor valid as a performance measurement tool." That's not a MaxContact opinion - it's the industry's own assessment of its standard practice.
The consequence is that coaching decisions, script adjustments, and performance reviews are all made on a handful of conversations selected at random. Objection handling failures, compliance drift, and the moments where an agent is genuinely struggling can remain completely invisible until the problem is already embedded.
What good looks like:
100% call coverage. Scorecards built on every conversation, not a sample. AI that makes that achievable without overwhelming your QA team.
MaxContact's AI call scoring — now generally available to all Conversation Analytics customers — reduces QA review time per call from 30 minutes to 5 minutes. That's approximately four days of analyst capacity returned to the team every month. Capacity that can go into actual coaching, script development, and performance improvement.
Scorecards are fully configurable: yes/no questions, rating scales, observation notes, auto-fail criteria. Business context can be set per scorecard so the AI understands your products, processes, and compliance requirements before it starts scoring. Scheduled auto-QA at scale — allowing always-on scoring as calls come in, or one-off compliance campaigns across historical data — is moving to beta on 6 July, with general availability planned for early August.
Challenge 4: Personalisation requires the right building blocks first
76% of consumers say personalised communications influence their brand choice, according to Salesforce's State of the Connected Customer. Personalisation at conversation level isn't a luxury - it's a commercial lever.
But it doesn't start with AI. It starts with having the right infrastructure in place:
Customer history and intent available before the conversation starts
In-call sentiment detection so agents know when someone is frustrated or at risk
Consistent context across channels - what happened on the last call, the last chat, the last AI interaction
Next-best-action guidance that surfaces what your best agents do in key moments, and replicates it across the team in real time
Once those building blocks are in place, personalisation stops being an aspiration. It becomes the logical next step, because you already have everything you need.
The bigger picture: it's not about solving one problem in isolation
The demo Conor ran at the webinar wasn't designed to show five separate features. It was designed to show how they connect.
A single agent interface. An automated wrap-up that feeds clean data into the next interaction. Real-time transcription with stereo accuracy that improves everything built on top of it. AI scoring across 100% of conversations. Context that follows the customer, not the channel.
The teams that are getting this right aren't deploying AI as a standalone fix for one metric. They're building a connected system where each piece makes the next one work better.
That's the direction of travel. And a lot of it is available right now.
Call Centre Quality Monitoring: Why Sampling Isn't Enough
Quality assurance is one of the most compliance-critical functions in any contact centre, and one of the most under-resourced. For most operations, the gap between what QA teams can review and what regulators now expect to see evidenced has never been wider.
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Most contact centres review a small fraction of their calls. A QA analyst picks a handful, scores them, flags what went wrong, and then moves on. It feels like it ticks the box for quality assurance. But for Ofcom-regulated telecoms operations and FCA-regulated financial services firms, it’s not enough, and the consequences of getting it wrong have never been higher.
This article explains why call sampling creates compliance exposure, what always-on monitoring looks like in practice, and what to look for when evaluating your current approach.
What is call quality monitoring?
Call quality monitoring is the process of reviewing agent-customer interactions to assess whether they meet your quality, compliance, and performance standards.
It typically covers:
What was said and how the agent handled the conversation
Whether compliance scripts and protocols were followed
How vulnerable customers were identified and managed
Whether the outcome was appropriate for the customer
How performance compares against your scoring framework
When call quality monitoring is done consistently, it gives you a documented evidence-base across every call type, agent, and campaign. But when it’s done poorly or too infrequently, it leaves gaps that regulators are increasingly likely to find before you do.
How do most contact centres currently monitor calls?
Sampling is the typical approach many call centres take to monitoring calls. A QA reviewer listens to a set number of calls per agent per month, scores them against a framework, and feeds the results back into coaching. It is time-consuming work, so let’s break down the numbers.
Example:
A single reviewer handles 50 calls a month at 30 minutes per call.
This amounts to 25 hours of review time.
And it is still only a fraction of the total call volume reviewed.
The problem here is not the effort; it's the coverage. On average, contact centres manually evaluate 5% of calls per week, meaning many QA operations are leaving the majority of interactions unreviewed. This means:
You don’t know whether your agents are consistently identifying vulnerable customers.
You don’t know whether compliance scripts are being followed on the calls you did not pick.
You are not building an evidence bse, only a small sample.
Manual call sampling statistics
FCA Consumer Duty: you need evidence across every interaction, not a snapshot
For debt collection, insurance, and other FCA-regulated contact centres, the stakes are different but the problem is the same. Consumer Duty requires firms to demonstrate they are delivering good outcomes for retail customers, not just on the calls they reviewed, but consistently and measurably across their entire operation.
The FCA has shifted decisively from implementation to enforcement. Regulators are no longer asking whether you have a quality monitoring process. They are asking whether you can prove, with documented evidence, that your agents are handling vulnerable customers correctly, following compliant scripts, and not causing foreseeable consumer harm. And that’s for every call, not just the ones you checked.
A sampling approach does not produce that evidence. It produces a snapshot.
For more on what the FCA now expects from contact centres in financial services and debt collection, see our Consumer Duty guide.
The problem with call sampling: A Summary
Sampling typically covers around 5% of calls per week, leaving the 95% of interactions unreviewed and unverifiable
Compliance drift happens slowly. By the time sampling catches a behaviour, it is already established and harder to coach out
Poor agent behaviour on outbound calls can go undetected long enough to trigger carrier blocking or an FCA flag
Vulnerable customers may not be identified correctly on calls you never reviewed
Good performance goes unrecognised as you cannot replicate what you cannot see
A sample tells you what happened on the calls you chose to review. It does not tell you what is happening in your operation
From sampling to monitoring: what's actually required
Moving from sampling to consistent call monitoring is not simply a matter of reviewing more calls. It requires the right infrastructure in place, and historically, that infrastructure was either too expensive, too time-consuming, or both.
At a minimum, always-on monitoring requires:
Call recording across all interactions, not just selected campaigns or call types
Transcription that converts voice to text accurately enough to be reviewed and searched at scale
A platform that connects recording, transcription, scoring, and reporting in one place rather than across multiple disconnected tools
Without all three, monitoring at scale either falls back on human reviewers (which is where the 25-hours-per-50-calls problem comes back in) or produces data too inconsistent to be useful as a compliance evidence base.
MaxContact's Conversation Analytics brings all of this together in a single platform. Call recording, real-time transcription, and reporting sit alongside each other. This gives your QA team a single place to monitor, review, and evidence what is happening across every interaction, without stitching together multiple tools or managing separate systems.
The reason most contact centres have defaulted to sampling is not because they did not want better coverage. It is because the operational cost of achieving it manually was prohibitive. A team large enough to review every call would cost more than most mid-market operations can justify. But that has changed.
How Conversation Analytics makes always-on monitoring feasible
Conversation Analytics is the platform that makes consistent, always-on call monitoring operationally viable for mid-market contact centres.
Rather than relying on a QA team to manually select, listen to, and score calls, Conversation Analytics connects call recording, transcription, scoring, and reporting in a single platform – automating quality assurance. Every interaction is captured, transcribed, and made reviewable, giving your QA team complete visibility across all call types, all agents, and all campaigns without the resourcing overhead of manual review at scale.
The cost comparison is significant. Replicating meaningful call coverage with human reviewers alone would cost an estimated £14,000 per month in analyst time for a mid-sized contact centre. Conversation Analytics delivers that coverage at a fraction of the cost, freeing your QA team to focus on coaching, calibration, and the complex calls that genuinely need a human eye.
How AI call monitoring surfaces insights faster
AI is what makes the insights from always-on call monitoring actionable rather than overwhelming.
Without AI, full call coverage creates a different problem; more data than a QA team can meaningfully review and act on. AI-powered call monitoring solves that by doing the heavy lifting on routine scoring, so your team's attention goes where it matters most.
Benefit
What it means for your operation
Structured scorecards answered automatically
Every scorecard question is answered using transcript evidence; no manual listening, no reviewer subjectivity.
Transcript-linked evidence
Every score links back to the exact exchange that informed it, giving you a defensible audit trail.
Faster review cycles
Review time drops from 30 minutes to 5 minutes per call, recovering around 4 days of analyst time every month.
Consistent scoring across your entire operation
The same criteria, applied the same way, across every agent, call type, and campaign every time.
Human oversight built in
Your QA team reviews outputs, calibrates scoring, and focuses on complex calls. AI handles the routine. Governance stays with your team.
The result is not just faster QA. It is a more reliable, more defensible evidence base built on every call, not a sample of them.
What to look for in your call quality monitoring approach
Is your evidence transcript-linked? Generic summaries are not a defensible evidence base. Scoring decisions need to be traceable back to what was actually said.
Is your scoring consistent? If different reviewers score the same call differently, your evidence has a credibility problem. Consistent scoring logic applied across all interactions removes that subjectivity.
Does your QA sit within your analytics platform? If scoring, feedback, and reporting live in separate tools, you create friction and risk. Everything should be in the same place.
Is human oversight built in? Your QA team should be able to review, challenge, and calibrate outputs. Always-on monitoring supports human-led governance, it does not replace it.
Are you scoring the right calls? Configurable triggers and criteria by call type, queue, campaign, or outcome, mean your monitoring effort goes where the compliance risk is highest.
The question is not whether you can afford to monitor every call
It is whether you can afford not to.
Ofcom and the FCA have both made clear that evidence of compliance needs to be consistent, documented, and demonstrable. A sampling process may satisfy an internal audit. It is unlikely to satisfy a regulator asking for proof of good outcomes across your entire customer base.
Always-on call quality monitoring closes that gap. It gives your QA team better data, gives your compliance function defensible evidence, and gives your operation a consistent view of what is actually happening on the phones across all calls, rather than just the ones you happened to pick.
Download the UK Contact Centre Regulatory Guide 2025–2027 to see how the FCA and Ofcom compliance obligations facing your sector map to your call monitoring approach and what good evidenced practice looks like in both.
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We surveyed 1,000 UK adults who had interacted with a contact centre in the last 18 months. The findings reveal something that goes beyond wait times, channel preferences, and AI adoption. This year, the biggest barrier to customer contact isn't the interaction itself - it's getting consumers to engage in the first place.
The Numbers Don't Lie: Trust Is Now an Operational Problem
Before we get to what consumers want, we have to address what's getting in the way. Our research reveals a structural trust deficit playing out before a single agent picks up the phone.
69% of UK consumers always or often screen calls from unknown numbers
46% have ignored a message from a legitimate company because they assumed it was a scam
Only 22% strongly agree they can tell when unexpected company contact is genuine
77% of those who ignored a legitimate call experienced a real consequence such as a missed appointment, an unresolved problem, a missed payment deadline
This is the Trust Gap: the growing distance between a company's confidence in its own outbound contact and what consumers actually believe when they see an unknown number. It affects every sector with outbound ambitions and it can't be fixed by dialling more.
Call Avoidance Varies Dramatically by Sector
Not all sectors face the same screening wall. Our data shows stark differences in call avoidance rates, and the gap between best and worst performing sectors is significant.
Loans, credit and debt management companies are the most avoided, with 37% of consumers saying they'd be least likely to answer a call from this sector. Insurance follows at 25%, with telecoms, technology, and retail/e-commerce close behind at 22–23%. Banks and building societies fare better at 16% avoidance, and notably, they also hold the highest sector trust score at 96%.
The lesson? Trust and answer rates move together. Sectors that have invested in consumer trust over time are reaping the operational benefits in their outbound performance. Those that haven't are paying the price at the identification gate.
"This data should make every contact centre leader pause," says Ben Booth, CEO of MaxContact. "Consumers broadly trust the sectors they deal with, but that trust doesn't translate into picking up the phone. If consumers can't tell the difference between a legitimate call and a scam, outbound strategies will struggle to deliver."
What Actually Makes Consumers Pick Up
The good news is that the Trust Gap is closable. When we asked consumers what would make them more likely to answer, two things stood out clearly:
82% say they would be more likely to answer if caller ID clearly identified the company name
80.5% say a pre-call text or email would make them more likely to pick up
These aren't aspirational preferences - they're operational levers. The problem isn't the dialler. It's the identification gate. Legitimate contact centres aren't losing the persuasion game. They're often not getting on the pitch.
Contact centres should prioritise:
Branded caller ID and carrier number reputation management - so consumers can recognise your call before they decide whether to answer
Pre-call communication - give consumers a reason to expect your call, especially in high-avoidance sectors
Treating contact frequency as a trust variable -too-frequent contact doesn't just frustrate consumers; in regulated sectors, it carries compliance risk
AI Is Here — But Transparency Is Non-Negotiable
UK consumers have been interacting with AI in contact centres for some time. The problem is, many didn't know it.
87% of consumers believe they've interacted with AI or automation in a recent company contact. Of those, 22% were sure or fairly sure they'd been talking to AI — but weren't aware of it at the time. That's more than one in five consumers who discovered, after the fact, that part of their experience was automated.
Nearly 9 in 10 (88%) consumers say it's important for companies to clearly disclose when AI is being used. Half say it's very important.
"The reputational risk of undisclosed AI is real and avoidable," says Ben Booth. "Consumers aren't opposed to AI - they're opposed to being kept in the dark about it. Deploying AI without disclosure doesn't just frustrate customers; it reinforces the same uncertainty that's causing them to screen your calls."
AI Adoption: Where It Works and Where It Doesn't
Consumer opinion on AI is nuanced. Where AI genuinely adds value, consumers are broadly willing to accept it:
Answering FAQs: 36%
Routing to the right department: 35%
Account updates and billing information: 26%
But the picture reverses sharply when it comes to high-stakes interactions. Over half (54%) say they don't want AI involved in emergency situations. Significant numbers also object to AI involvement in complex account problems (50%), financial discussions (49%) and when negotiating terms (46%).
Crucially, 71% of consumers say they'd be comfortable with AI helping resolve an issue faster — as long as a human agent was available throughout. The acceptance of AI is conditional on a clear, accessible escalation path.
Humans Still Matter Where It Counts
Despite the growth of AI and automation, consumers are clear about when they need a person:
Emergency situations - 41% want a human agent
Complex account queries - 33%
Financial discussions — 29%
Explaining a sensitive or personal matter - 26%
Making a complaint - 23%
These aren't edge cases. An AI that handles a billing query well creates modest goodwill. An AI that mishandles a bereavement disclosure or an emergency can permanently damage a customer relationship.
When things go wrong and complaints happen, consumers care most about: a clear explanation of the outcome (39%), being kept updated throughout (37%), appropriate compensation when the company is at fault (33%), and only having to explain the issue once (31%).
What Builds and Breaks Consumer Trust
Our research shows consistent patterns in what drives contact experience, positively and negatively.
What puts consumers off before they even try:
Long wait times: 36%
Being transferred multiple times: 34%
Difficulty reaching a human: 29%
Having to repeat themselves: 28%
What good looks like:
Quick resolution -36%
Easy access to a human when needed - 35%
Knowledgeable agents - 34%
Clear communication throughout - 32%
On channel trust, email remains the most trusted channel for company contact (51%), followed by phone calls (30%) and letters (27%). For outbound communications that don't need an immediate response, email is still the most credible messenger.
Five Focus Areas for Contact Centre Leaders in 2026
Based on our findings, these are the areas that will have the most impact:
Fix the identification gate: Deploy branded caller ID, carrier number reputation management and pre-call communication. The recoverable opportunity isn't every screened call; it's the willing contacts who are filtering themselves out because they fear scams.
Make AI disclosure the default: Clearly disclose AI use at the start of every AI-assisted interaction. In regulated sectors, it's a compliance requirement. Everywhere else, the reputational risk is reason enough.
Protect the human escalation path : Across every question about AI in this study, the most-cited condition for consumer acceptance was the same: a human must be available and clearly signposted. Design the escalation as carefully as you design the AI.
Treat 'only explain once' as an infrastructure target: CRM integration, context-passing between channels, and warm handoffs are the operational response to the number one complaint driver.
Audit complaint journeys against what consumers actually need : A clear outcome explanation, ongoing updates, appropriate compensation, not having to repeat themselves, and a human presence. These five things determine whether a resolved complaint becomes a trust-builder or a churn trigger.
Want the full picture? The Voice of the UK Consumer 2026 report includes sector-by-sector breakdowns across utilities, telecoms, finance/debt, and insurance — with data on vulnerability handling, AI comfort, complaint experience, and regulatory risk. Download the full report here.
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