What Is An Outbound Call? Call Centre Best Practices
If you’re an outsourced contact centre dealing with high-volume calls, outbound calling campaigns are vital for driving business growth, acquiring new customers, and nurturing existing relationships. However, executing an effective outbound strategy requires careful planning, the right tools, and a deep understanding of best practices.
In this guide, we’ll explore the essential elements for mastering outbound calling in your call centre.
What Are Outbound Calls?
Understanding the different types of outbound calls before turning your attention to strategy is crucial. The various objectives behind outbound calling initiatives are important to consider:
Sales and Lead Generation: The bread and butter of outbound efforts are often sales calls and lead qualification, whether it’s cold calling for new business or upselling/cross-selling to existing customers.
Market Research: Outbound surveys provide invaluable market intelligence, gathering insights into consumer behaviour, product feedback, and industry trends.
Customer Experience: Proactive outreach can enhance the customer experience by addressing issues before they escalate and gauging satisfaction through post-transaction surveys.
While the specific goals may differ depending on use cases, successful outbound strategies share a common foundation: aligning the right tactics to your unique business needs.
What Can a Strong Outbound Calling Strategy Achieve?
A well-planned outbound strategy, coupled with the right technology, can significantly benefit your business:
| Boost brand awareness and lead generation | Proactively reach a wider audience, introduce your brand, and generate a pipeline of qualified leads. ||-------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------|| Strengthen customer relationships and drive retention | Nurture existing relationships with personalised outreach, exclusive promotions, and addressing potential concerns. || Gather valuable market research and sales data | Conduct market research to gain insights into customer preferences and buying habits, ultimately giving you a competitive edge. || Targeted communication for specific campaigns | Execute targeted campaigns for customer satisfaction surveys, new product launches, and more. |
Optimising Call Centre Technology: Inbound vs. Outbound
While the right technology is crucial for both inbound and outbound calls, their needs differ. Inbound centres focus on agent workflow and empowering customers (think IVR and call routing). Outbound centres prioritise lead generation and call efficiency (think predictive dialers and ACD). For centres handling both, a comprehensive, integrated solution is key.
Make Outbound Calling Successful with Powerful Technology
We’ve established that the right contact centre software is make or break when it comes to outbound calling. But which features and capabilities should you prioritise if you’re looking to boost results of your outbound campaigns?
Auto Diallers: Boost agent productivity with an outbound dialler that connects them directly to live prospects, eliminating wasted time on unanswered calls.
Call Recording: Use call recordings to identify coaching opportunities and help agents refine their communication skills and objection handling techniques.
CRM Integration: Painless CRM integration provides agents with a centralised view of customer information, enabling personalised conversations and stronger relationships.
Automatic Call Distribution (ACD): Intelligent call routing means every call is directed to the most qualified agent based on skills, language proficiency, and availability.
Answer Machine Detection (AMD): Avoid wasted time on answering machines by using AMD technology to identify and skip over voicemails.
Dynamic Call Scripting: Empower agents with flexible, interactive call scripts that can adapt to each conversation while maintaining consistency and accurate data capture.
Outbound Skills-Based Routing: Match customers with agents who possess the most relevant expertise, encouraging rapport and efficient resolution.
Data Management: Use data segmentation tools to target the right audience and prioritise contacts most likely to convert, optimising your outreach efforts.
Outbound Calling Best Practices
When it comes to outbound activity, utilising the right technology alone isn’t enough. Successful outbound strategies also rest on implementing proven best practices:
Planning and Preparation
Clearly define campaign objectives and target your call lists to match.
Develop call scripts that act as flexible conversation guides, not rigid scripts.
Ensure compliance with relevant regulations, such as obtaining necessary consent.
Agent Skills and Training
Refine agents’ communication abilities, focusing on active listening, empathy, and objection handling.
For sales campaigns, provide comprehensive product knowledge training.
Measuring Your Outbound Calling Performance
Measuring the success of outbound calling must look beyond the number of calls made. Tracking relevant KPIs helps you to achieve two things. Firstly, it gives you valuable insights that enhance the effectiveness of your campaigns. Secondly, it empowers you to make data-driven decisions for continuous improvement.
Key KPIs to Track for Outbound Calling Success
Here are some of the essential KPIs you should monitor to gain a comprehensive understanding of your outbound calling performance:
Connect Rate: Measure the percentage of your outbound calls that reach live prospects. A high connect rate indicates efficient dialling strategies and minimal wasted time on busy signals or unanswered calls.
Average Handle Time (AHT): Track the average duration of your outbound calls. While a lower AHT might seem ideal, it’s important to consider the context of your campaign goals. For example, a complex sales call might naturally have a higher AHT compared to an appointment scheduling call.
Conversion Rate: This is the golden metric for many outbound calling campaigns. Measure the percentage of calls that achieve your desired outcome, such as a completed sale, appointment booked, or survey completion.
First Call Resolution (FCR): Track the percentage of customer issues resolved during the initial call. A high FCR indicates efficient problem-solving by your agents and minimises the need for frustrating callbacks for customers.
Customer Satisfaction Ratings: Customer feedback is invaluable. Regularly monitor customer satisfaction ratings to gauge their perception of your outbound calling experience. Positive ratings indicate a well-executed strategy, while negative feedback highlights areas for improvement.
Enhance your outbound calls with MaxContact
Successful outbound calling is a continuous process. By acting on the insights gained from tracking KPIs and consistently refining your approach based on data and best practices, you can transform your outbound calling operation so that your activity consistently delivers exceptional results.
MaxContact is a leading provider of outbound call software, combining powerful diallers with reporting, AI, and optimisation tools. Our cloud-based outbound solution can simplify your call centre operations and boost productivity.
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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
So, what’s an outbound dialler?
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.
Contact centres can be high-pressure environments, with plenty of challenges to tackle; managing customer interactions, staying compliant and helping agents perform at their best, to name a few. That’s where speech analytics comes in.
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By recording and transcribing 100% of customer conversations, analysing sentiment, categorising topics and ranking agent performance, speech analytics helps contact centre leaders uncover actionable insights, make smarter decisions and optimise business operations.In this article, we’ll explore 10 practical ways our speech analytics platform can be used to transform the way contact centres work. From improving compliance checks to empowering agents and enhancing sales strategies, there’s a lot to gain from this powerful technology.
1. Speeding up call quality assessments
In traditional quality assessments, quality assurance (QA) teams are often required to listen to hundreds of call recordings to evaluate, understand agent-customer conversations, and assess the quality of the call. This manual process is time-consuming, especially for call centres dealing with high call volumes.
Speech analytics speeds up the QA process by transcribing speech-to-text, with every call transcribed into a full text version. Thanks to text transcriptions, QA teams can read through calls – which takes 50% less time than listening to them. This is because QA teams can skip directly to specific points in the conversation that need attention.
By searching within transcripts for specific phrases or keywords, it is much easier and quicker to find sections where issues have arisen, saving significant time but without sacrificing detail.
2. Keyword tracking for compliance
Staying compliant is crucial for contact centres, particularly in industries with strict regulations such as sales, collections, or finance. Agents often need to say specific phrases or mandatory statements during calls – for example, those required by the Financial Conduct Authority (FCA) or Ofcom guidelines.
MaxContact’s Spokn AI makes compliance easier to monitor and achieve, as it can be set up to track and filter certain keywords across all call transcripts. Compliance teams can set up the software to flag calls where those important phrases are missing or not used correctly.
This means you can quickly spot and fix potential compliance issues without spending hours manually checking calls. It’s a simple way to reduce risks, save time, and make sure your team is consistently ticking all the right boxes.
3. Keyword tracking for vulnerability detection
Contact centres need to identify and provide special care for vulnerable customers, such as those who express concerns related to financial or emotional hardship. This is where the ability to search for phrases or mandatory statements across transcripts once again supports the process.
Using speech analytics and keyword filtering, it is possible to detect sensitive language within conversations, flagging words and phrases that may indicate vulnerability. By automating this process, speech analytics software helps agents and supervisors identify potentially vulnerable customers quickly, allowing them to respond with empathy, follow specific support protocols, or even escalate the conversation to a specialist.
This targeted approach improves customer care and means vulnerable individuals receive the assistance they need.
4. Optimising sales playbooks
For sales and collections teams, the ability to handle customer objections effectively can have a huge impact on call outcomes. This is where speech analytics steps in to give agents an edge. By analysing call topics, customer objections and sentiment trends, tools like speech analytics can help call centre supervisors to uncover what’s working (and what’s not) in customer interactions.
Senior call centre leaders can use these insights to tweak call centre scripts, refine sales tactics and even create “battlecards” to tackle competitor comparisons head-on. These resources and insights are then shared with call agents.
On top of that, speech analytics can indicate how call agents respond to objections by looking at phrase level sentiment, helping pinpoint successful techniques and areas for improvement. With these insights, teams can continuously optimise their playbooks, leading to smoother calls, better outcomes and more conversions.
5. Improving agent performance through sentiment analysis
Helping agents improve starts with understanding where they might be struggling or excelling. Sentiment analysis does this by breaking conversations into phrases and identifying words of positive or negative sentiment post-call. It draws attention to areas where an agent might be lacking empathy, patience, or clarity – all key factors that impact how customers feel during a call.
When speech analytics software uncovers calls with high customer frustration or negative sentiment, call supervisors can step in with tailored coaching. Whether it’s working on tone, handling sensitive situations, or improving listening skills, this focused feedback helps agents refine their approach. The result? Happier customers, stronger relationships and call agents who feel more confident.
6. Identifying what works well to amplify success
Improvement is important, but so is recognising what’s already working. Speech analytics helps teams to see moments of positive sentiment in calls, showing where call agents have handled objections and sensitive interactions effectively, striking the right chord with customers.
By considering the ‘why’ behind these successful interactions, managers can uncover tactics, language, or approaches that deliver great results time and time again. These insights can be shared across the team to raise everyone’s game, and they’re also an important resource for marketing or sales teams.
Whether it’s refining scripts or crafting new campaigns, using proven techniques ensures greater consistency and impact across your contact centre.
7. Driving operational efficiencies
Efficiency is key in contact centres, but it shouldn’t come at the expense of quality. Speech analytics helps strike the perfect balance, with tools like call summaries, topic detection and sentiment analysis. These features allow call centre supervisors to identify common call topics and recurring customer issues.
Armed with this data, managers can design targeted training and streamline processes to ensure agents are ready to tackle frequent queries right away. This leads to fewer call transfers and more first-call resolutions, cutting down handling times while boosting customer satisfaction. The outcome is a more efficient operation that saves time, resources and costs – all without compromising on quality.
8. Gaining insight into team dynamics
Understanding your team’s performance isn’t just about numbers or individual performance – it’s about seeing the bigger picture. With speech analytics, call centre managers have a clearer view of overall team performance and can break down calls by agent, objection type or campaign. This level of detail helps uncover collective team performance as well as each agent’s individual strengths and areas where they may need extra support.
By tracking objection trends, comparing metrics across agents and teams, and analysing how individuals handle challenging situations, call centre leaders can make coaching much more targeted. Instead of a one-size-fits-all approach, these data-driven insights allow team leaders to tailor their feedback, helping every agent play to their strengths while improving in areas where they struggle. This leads to a more skilled, confident and well-rounded team.
9. Empowering agents to self-improve
Speech analytics isn’t just a tool for managers – it’s also a powerful way to help agents grow and improve. With features like call recaps, sentiment insights, and objection tracking, managers can share clear, objective feedback based on real data from their agents’ interactions.
By providing tailored feedback, managers can help agents spot patterns, identify areas for improvement and refine their skills – whether it’s handling objections more effectively, improving tone, or building stronger rapport with customers.
This personalised coaching creates a sense of accountability and motivates agents to continuously grow.
With clear, actionable feedback, agents can deliver better customer experiences and contribute to the team’s success. Plus, happier, more capable agents are less likely to burn out, which helps reduce turnover and maintain a strong team.
10. Conducting market research to inform growth strategies
Spokn AI is a powerful tool for uncovering what your customers really want. By evaluating recurring topics and sentiment trends across conversations, it helps contact centres build a clear picture of customer needs, preferences and pain points.
With advanced topic detection and transcription capabilities, speech analytics empower businesses to spot emerging trends and patterns that might not be immediately obvious. Whether it’s identifying new product demands, spotting service gaps, or understanding shifts in customer sentiment, these insights are invaluable for shaping future strategies.
This customer-first approach gives contact centres a new-level of visibility into customer information. Often, customer information is recorded in siloed notes (particularly in hybrid working environments) making them inaccessible at a top data level. Speech analytics aggregates and analyses conversations, uncovering actionable insights into sentiment, trends and preferences. This enables businesses to adapt to market changes, create targeted campaigns and design products and services that truly meet customer needs.
Speech analytics is powerful software that makes the way for smarter, more efficient and more impactful operations in your contact centre. By analysing 100% of customer interactions, platforms like Spokn AI offer insights that help tackle the unique challenges of a fast-paced call centre floor, from improving compliance and agent performance to refining sales strategies and uncovering customer needs.
The key to success lies in using these insights to take action: refining processes, tailoring coaching and aligning your strategy with the data. Not only does this lead to better outcomes for your team and business – it also creates a stronger, more positive experience for your customers too.
As customer expectations grow and contact centres become more complex, embracing speech analytics tools can give you the clarity, confidence and competitive edge you need to thrive.
By leaning into the capabilities of speech analytics, you’re not just keeping up; you’re staying ahead.
Blog
5 min read
Are You Ready for AI In Your Contact Centre?
Learn what AI readiness really looks like - and download the scorecard to assess yours.
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AI doesn’t fix contact centres. It scales them. If your journeys are joined up, automation can reduce the pressure your team is facing. However, if they’re fragmented, AI amplifies the friction - faster transfers, repetition and customer effort. That’s why the most useful question contact centre leaders can ask themselves isn’t “What can AI do?” - it’s, "Are we actually ready for it?".
Whether you’re running sales and retention in telecoms, payment collections with vulnerability considerations in finance, customer support in utilities, or managing multiple client programmes in a BPO, the readiness question is the same - do we have the foundations to automate without increasing customer effort or operational risk?
“Always-on” support is an operating model, not a staffing one. It's built to remove avoidable demand, protecting your team's time for high-judgement conversations, and making escalation safe when risk or complexity arises.
Always-On Service Starts with Resolution, Not Headcount.
Consumers are increasingly expecting help at any time of day, across voice and digital channels. But increasing headcount to meet 24/7 customer support expectations isn’t sustainable for most contact centres operating on tight margins.
An always-on contact centre doesn’t mean agents working around the clock. It means using AI and automation to absorb predictable demand across inbound and outbound – from service updates and appointment changes to sales follow-ups and renewals, to payment reminders and self-serve arrangements - without needing an agent for every interaction.
The trap many leaders fall into is assuming that automation alone creates always-on. It doesn’t. Always-on is the result of clear journeys, consistent rules, and controlled escalation.
The Real Readiness Problem: Avoidable Demand
Most contact centres don’t struggle because customers contact them. They struggle because customers are contacting them more than once.
A lot of volume is created by operational gaps:
Unresolved issues driving repeat contact
Too many transfers caused by poor routing
Long handle times driven by missing context
Channels operating as seperate service silos
This is the stuff that quietly drains performance. It also explains why some AI programmes stall: they automate interactions on top of broken flows, then wonder why customer effort doesn’t fall, and agent workload doesn’t change.
If you want a pragmatic AI strategy, start by identifying where the operation is generating demand it shouldn’t have to handle.
A Practical Readiness Lens: Demand, Continuity, Control
To make readiness tangible, use this simple lens. If any one of these is weak, automation outcomes will be capped - or worse, you’ll scale the wrong things.
1) Demand: Do You Know What Should Be Automated?
AI delivers value when it absorbs predictable, repeatable demand - the structured interactions that don’t require human judgement. If you can’t clearly separate predictable from complex demand, you’ll either automate the wrong things and frustrate your customers or keep too much with agents and miss the efficiency gains.
A pragmatic starting point is mapping the top drivers and asking: which ones are genuinely structured, and which are only “simple” because we’re not seeing the full context?
2) Continuity: Does Context Move with The Customer?
Customers think in outcomes, not channels. Readiness means your operation can maintain continuity when a conversation starts in chat and moves to voice, or when an outbound reminder triggers an inbound response, or when a customer returns with a follow-up and expects you to remember what happened last time.
If context doesn’t travel, automation becomes a reset button, and resets are where handle time, repeat contact, and frustration grow.
3) Control: Can You Escalate Safely and Measure Outcomes?
Automation should never be a dead end. When complexity rises, or when there’s vulnerability, a complaint, payment risk, or compliance exposure, you need controlled escalation to a human agent with the full context carried across.
If you can’t define escalation rules and success measures beyond containment” you’re not ready to scale. You’re ready to pilot.
Where AI Fits When You’re Ready: Layers, Not Channels
A common mistake is deploying AI as separate tools by channel - a chatbot here, an AI agent there - and expecting it to add up to an always on operation. It simply adds more mini contact centres to the one you already have.
A more practical approach is to treat AI as layers across the operating model:
Decision layer (AI Agents): Interprets intent, resolves structured interactions, and prevents outbound activity from automatically creating inbound pressure through unmanaged follow-up
Asynchronous layer (chatbots and messaging): Allows customers to complete routine tasks without joining a queue, while keeping journeys connected across voice and digital
Visibility Layer (Conversation Analytics): Shows where demand originates, where conversations stall, and what drives repeat contact so you can improve routing, coaching, and automation design based on evidence rather than instinct
When these layers support end-to-end workflows, AI stops being a bolt-on and becomes a genuine performance lever.
A Quick Readiness Check: The Questions Most Teams Skip
If you’re planning AI-enabled automation this quarter, these questions are worth answering before you commit time and budget:
What proportion of our demand is truly predictable and repeatable?
Where do customers repeat themselves, get transferred, or drop out?
What's creating repeat contact and how will we remove it?
What are our escalation triggers for risk, vulnerability or complexity and do we trust them?
How will we measure success beyond containment - effort, quality, outcomes, stability?
Do inbound and outbound journeys reinforce each other, or create extra pressure?
If those answers aren’t clear yet, that’s not a blocker, it's your roadmap.
Pressure-Test Your Readiness With The Scorecard
If you want a structured way to benchmark readiness across the foundations that matter - demand, continuity, escalation, and operational fit - our scorecard is designed for exactly that. Use it to create alignment internally, prioritise improvements, and shape an automation roadmap that holds up under real-world volume, not just pilot conditions. Download the Always-On Contact Centre Readiness Scorecard here.
Blog
5 min read
Automate smarter: how to identify what to automate in your contact centre
Not sure where to start with contact centre automation? Discover a proven framework for identifying the right interactions to automate — and when.
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The pressure to introduce AI in contact centres has never been greater. But automating the wrong interactions doesn’t just waste investment - it actively frustrates customers and creates more work for your team. Here’s how to get it right from the start.
The real challenge isn’t how to automate - it’s what
Most business leaders today aren’t asking whether to use AI in their contact centre. They’re asking where to start. And that’s exactly the right question to be asking.
We recently hosted a webinar exploring this challenge with Kayleigh Tait, Marketing Director at MaxContact, and Conor Bowler, Principal Product Manager. Together, they walked through the research, the common pitfalls, and a practical framework that helps contact centres make confident, data-driven automation decisions.
Here’s what they covered.
What UK consumers actually think about AI
MaxContact commissioned an independent survey of over 1,000 UK consumers who had interacted with a contact centre in the last 18 months. The findings from the Voice of the UK Consumer Report are revealing.
45% of UK consumers say they’re comfortable interacting with an AI-powered chatbot or virtual assistant. But 36% say they’re uncomfortable.
Only 36% say AI has improved their experience. Almost the same number - 32% - say it has made things worse.
65% of 25–34 year-olds are comfortable with AI, compared to just 27% of over-55s.
70% want a human when explaining their specific situation. 67% for emergencies. 61% when making a complaint.
55% of consumers have abandoned calls because of excessive wait times. 26% because they had to repeat information.
The takeaway? Automation isn’t automatically improving customer experience. It depends entirely on how and when it’s used - and critically, whether the strategy has been built around the customer or around internal efficiency targets.
The modern inbound customer journey
Most businesses treat every interaction the same, routing everything to queues. But inbound demand isn’t evenly distributed. It follows a pattern.
At the start of the journey, volumes are high and queries are simple: balance requests, payment dates, appointment changes, status updates. This is where AI and automation deliver the greatest impact - resolving queries quickly, reducing cost to serve, and freeing agent capacity without compromising experience.
As complexity increases, the role of automation shifts. Intelligent routing, context preservation from AI to human handover, and real-time agent support all help agents handle harder conversations faster and with more confidence.
At the resolution and advocacy stages, humans lead - supported by AI insights, not replaced by them. The goal is that automation removes repetitive workload at the top of the funnel, so people can focus on the interactions where judgment, empathy, and experience really matter.
How Conversation Analytics uncovers automation opportunities
Before you decide what to automate, you need to understand what’s actually happening in your contact centre. Conor Bowler demonstrated exactly how MaxContact’s Conversation Analytics makes this possible - at scale.
In the demo, Conor surfaced 28,000 calls from a single month, immediately identifying intent clusters: appointment booking accounted for 10% of interactions, technical challenges for 4%. Together, that’s 14% of call volume with clear automation potential - identified in minutes.
Using MaxContact’s AI assistant within the platform, teams can drill into individual calls, ask whether elements of those interactions could be automated, and use those insights to design workflows in MaxContact’s Workflow Studio. Those workflows can then be deployed directly to chatbots, voice agents, or email channels - with built-in escalation paths when automation reaches its limits.
For contact centres without Conversation Analytics today, this process is still possible — but relies on manual call sampling, disposition codes, and CRM data. It’s achievable, but slower and harder to repeat consistently over time.
The MaxContact Automation Framework
Based on research findings and direct experience working with contact centres of all sizes, MaxContact has developed a four-step framework for identifying automation opportunities.
Step 1: Start with real interaction data
Automation decisions should be driven by evidence, not assumption. Too often, automation projects are led top-down - driven by boardroom pressure or a use case that sounds innovative rather than one grounded in data. Starting with call recordings, chat transcripts, CRM data, disposition codes, and repeat contact patterns gives you the factual foundation to make better decisions.
Look for patterns: what are the most common reasons for contact? What consistently takes under three to four minutes to handle? What drives re-contact within 24 to 72 hours? Technology makes this repeatable - so you’re not starting from scratch every quarter.
Step 2: Cluster by intent
Rather than analysing by channel (voice vs email vs chat), cluster interactions by customer intent. Instead of ‘20,000 calls’, ask: how many were payment date queries? Balance requests? Appointment changes? Customers don’t think in channels — they think about the problem they want to solve.
Conversation Analytics surfaces these clusters automatically, saving hours of manual analysis and revealing patterns that might otherwise go unnoticed.
Step 3: Rank by volume and effort
Not every repetitive query should be automated. Ranking by two lenses — volume (how often does this occur?) and effort (how much friction does this create?) - helps you prioritise strategically.
High volume + low effort: immediate automation potential.
High volume + high effort: may require journey redesign before automation.
Low volume + high effort: remain human for now.
Low volume + low effort: monitor and consider as a pilot.
Step 4: Validate with your team
Before you automate anything, validate the decision with the people who handle those conversations every day. Ask: Is this emotionally sensitive? Is it a brand touchpoint that customers value? Does it spike seasonally? Does what looks like a simple query often become a complex one underneath?
A payment query might look straightforward - but if it frequently leads to a conversation about payment difficulty, that’s not a candidate for full end-to-end automation. This step prevents automation decisions that look good on paper but frustrate customers in practice.
How do you know your automation is working?
Automation is working when three things improve simultaneously: business outcomes (cost to serve, conversion, retention), customer experience (faster resolution, less repetition), and operational performance (agents spending less time on repetitive tasks and more on complex conversations). If automation only improves one area, it’s likely not deployed in the right place.
Monitor containment rates, drop-off points, and escalation paths on a weekly basis for early warning signs. Review and optimise on a quarterly basis - or more frequently in fast-moving markets with changing regulation or customer expectations.
Book a complimentary automation consultancy session with our Customer Success team and we’ll run you through the MaxContact Automation Framework for your organisation: https://www.maxcontact.com/book-a-demo
Blog
5 min read
How to Measure the ROI of AI Automation in Your Contact Centre
Regardless of the industry they operate in, AI automation is a commercial necessity for contact centres, rather than a tool to experiment with.
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According to our latest Benchmark Report, 66% of contact centres are currently using or piloting AI with the aim of reducing operational costs and driving productivity.
But measuring ROI from AI automation isn’t straightforward.
A contact centre specialising in debt collection may measure ROI through reduced cost per contact, improved payment completion rates, or increased compliance consistency. Meanwhile, an outsourced contact centre that handles high-volume inbound enquiries may focus on deflection rates, average handling time or agent utilisation.
Channel mix can also influence impact. Voice-reliant operations see ROI through reduced call queue pressure and lower cost per call, while digital-first environments may prioritise customer containment and response speed.
Measuring AI ROI properly means understanding what success looks like in your specific environment, rather than relying on generic savings estimates.
Start with a baseline: what does a human-handled interaction really cost?
Before you can begin to measure the return from AI automation, you need a clear picture of what interactions cost when they’re handled by people.
For most UK contact centres, the average cost of a human-handled voice call sits between £5.50 and £6.50 per interaction. This is often used as a headline figure, but it doesn’t tell the whole story.
The total cost is driven by other factors, including:
Agent salaries and on-costs
Training and onboarding, which are made more expensive by high attrition rates
Quality assurance and compliance overhead, including call monitoring and reporting
Out-of-hours staffing, which significantly increases the cost for 24/7 coverage
Inefficiencies caused by repeat calls, transfers and long handle times
Even when handled efficiently, live calls demand dedicated agent time, whereas digital interactions can be managed asynchronously and at a greater scale.
A voice-heavy operation will feel cost pressure very differently from a digital-first one, and ROI calculations need to reflect that reality.
By contrast, AI-handled interactions typically cost a fraction of a human-handled call, often coming in at under £0.50 per interaction, depending on channel, complexity and volume. That gap is where ROI potential starts to emerge, but only if you understand what you’re replacing or augmenting in the first place.
Put simply, you can’t measure ROI without first understanding what each interaction costs you now. Without a baseline, your savings might look impressive on paper but will prove impossible to validate in practice.
The core ROI generators of AI automation
Not every AI capability is designed to solve the same problem, and not every contact centre will prioritise the same outcomes.
The key to measuring ROI accurately is understanding where value is being created in your operation.
AI Agents: reducing cost per interaction and extending capacity
AI Agents deliver ROI by reducing the cost of handling routine interactions and extending service availability without increasing headcount.
Instead of relying solely on human agents to manage every enquiry, AI Agents can handle high-volume, repetitive interactions end-to-end. This includes tasks such as customer authentication, balance enquiries, payment queries and status updates. Each interaction handled by an AI Agent reduces the cost of a human-handled call.
From an ROI perspective, contact centres typically measure:
Cost per AI-handled interaction (often under £0.50)
The percentage of total interactions fully handled by AI
Reductions in out-of-hours staffing costs
Reduced call queue pressure during peak periods
When AI Agents are used to automate between 40-60% of repetitive interactions, the cost impact is significant. Organisations frequently see monthly savings running into tens of thousands of pounds, driven purely by lower cost per interaction and improved utilisation of human agents.
For Indebted (a contact centre in the debt collection industry), automating repetitive interactions with an AI Agent led to a 30% increase in contact centre productivity and a 12% uplift in resolution rates.
AI Chatbots: deflection, containment and digital ROI
While AI Agents reduce the cost of handling interactions, AI Chatbots drive ROI by preventing interactions from becoming calls in the first place.
AI Chatbots aren’t a separate intelligence layer. They’re a digital channel through which AI Agents operate, using the same logic, workflows and compliance rules. The difference is where the interaction happens.
From an ROI standpoint, AI Chatbots are measured through:
Deflection rates (queries resolved without reaching an agent)
Reduction in inbound call volume
Digital containment rates
Cost difference between chatbot interactions and human-led webchat or calls
Impact on Average Handle Time (AHT) by removing routine demand
When routine queries are resolved digitally, contact centres reduce inbound pressure, shorten queues and protect agent capacity. Customers benefit from instant responses, while the organisation avoids the higher cost of voice-based interactions altogether.
AI-powered conversation analytics: ROI beyond cost reduction
Not all AI-driven ROI comes from removing interactions. Some of the most valuable gains come from making existing interactions more effective.
AI-powered conversation analytics deliver ROI by improving visibility, performance and compliance across every conversation. Teams gain insights across 100% of interactions instead of manual samples.
From an ROI perspective, contact centres typically measure:
Reduced manual QA effort and review time
Faster onboarding and agent coaching
Improved compliance monitoring and risk identification
Earlier identification of call drivers and friction points
Improvements in agent effectiveness over time
Conversation analytics don’t directly reduce demand. Instead, they help contact centres understand why interactions are happening, where time is being lost, and how performance can be improved at scale.
ROI looks different depending on your contact centre model
The value AI automation delivers depends on how your contact centre operates, what pressures you’re under, and what success looks like to you.
Below are three common models, and how ROI typically shows up in each.
Debt collection & financial services
In debt collection and financial services, ROI is closely tied to cost control, compliance and availability.
Key ROI drivers typically include:
Lower cost per contact
Consistent, auditable compliance
Always-on availability without expensive out-of-hours staffing
AI Agents are particularly effective here because they can handle structured, repeatable interactions reliably, including:
Customer authentication
Payment flows
Balance and status updates
By automating these journeys, organisations reduce inbound demand on human agents while ensuring interactions are handled consistently and compliantly.
As seen with Indebted, automating high-volume, predictable enquiries helped reduce the cost per interaction while maintaining service availability across extended hours.
Outsourced contact centres and BPOs
For outsourced contact centres, ROI is less about absolute cost reduction and more about margin protection and scalability.
Typical ROI focus areas include:
Improving agent utilisation
Protecting margins under fixed-price or SLA-based contracts
Maintaining service levels during demand spikes
AI plays a key role by absorbing predictable demand during peak periods, reducing the need to rapidly scale your headcount. This helps BPOs meet SLAs without over-recruiting or burning out agents during busy periods.
There’s also a longer-term ROI impact through reduced pressure on frontline teams, which can help lower churn and stabilise delivery costs.
Public sector, health and support services
In public sector and support-led environments, ROI is often measured in capacity, continuity and service quality, not just financial savings.
Key ROI considerations include:
Extending service availability with limited budgets
Reducing pressure on frontline staff
Protecting agent wellbeing in emotionally demanding roles
ROI in Real Terms: Quitline Victoria
Using AI Agents to support outbound engagement, Quitline Victoria achieved a 62% answer rate, 18% completion rate and 10% re-engagement rate, extending service reach without increasing pressure on frontline counsellors.
In this context, ROI is realised through better allocation of human effort, improved service continuity and a more sustainable operating model, rather than simple cost removal.
A practical framework for calculating AI automation ROI
Step
What to assess
What to quantify
1. Baseline costs
Understand what interactions cost today
Salary, training, attrition, and out-of-hours premiums.
2. Identify automatable interactions
Pinpoint where AI can add value
% of queries that are “transactional” (Status, Pay, Reset).
3. Estimate containment & deflection
Assess how much demand AI can absorb
The volume of demand AI can fully resolve (usually 40–60%).
4. Compare cost per interaction
Quantify direct cost savings
Monthly volume × (Human Cost − AI Cost).
5. Factor in secondary benefits
Capture longer-term ROI
Reductions in agent churn and manual QA overhead.
Common ROI mistakes to avoid
When measuring the ROI of AI automation, it’s easy to focus on the headline numbers and miss what actually drives long-term value. These are some of the most common pitfalls contact centres run into.
Measuring AI in isolation AI rarely delivers ROI on its own. Its impact comes from how well it’s embedded into existing journeys, channels and workflows. Measuring AI separately from call routing, workforce management, or analytics often underplays its true value.
Expecting 100% automation AI isn’t designed to handle every interaction. The biggest gains come from automating the right interactions. The interactions that are predictable, repeatable and time-sensitive. Complex or sensitive conversations should always be assigned to human agents.
Focusing only on call deflection Reducing inbound volume matters, but it’s not the whole picture. ROI also comes from shorter handle times, better first-contact resolution, smoother handovers and improved agent productivity.
Ignoring quality, compliance and experience Lower cost interactions mean very little if service quality drops or compliance risk increases. ROI should always be measured alongside consistency and customer outcomes, especially if you’re operating in a regulated environment.
Treating ROI as a short-term metric AI ROI compounds over time. As models learn, workflows improve, and teams adapt, the value of it grows. Measuring success only in the first few weeks can hide the longer-term gains in capacity, scalability and higher resilience.
ROI is about balance, not replacement
The strongest ROI from AI automation comes from supporting people rather than replacing them.
Used as part of a human-AI hybrid model, AI Agents, AI Chatbots and analytics help contact centres reduce cost per interaction and extend capacity to deliver a more consistent service, without increasing headcount or burning out teams.
ROI isn’t something you measure once and move on from. The most successful contact centres refine automation over time as demand, channels and expectations change.
If you want to understand what ROI could look like in your contact centre, start by exploring how AI can support your existing operation.
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