Explore fresh, expert perspectives on customer engagement and innovation

Debt collection is undoubtedly challenging; it’s crucial for contact centre leaders to continuously assess and optimise their team’s performance. Our recent survey of 100 UK debt collection professionals provides valuable benchmarking data to help you evaluate your team’s effectiveness and identify areas for improvement. In this blog, we’ll dive into the key metrics and offer practical strategies to enhance your debt collection processes.

Right Party Contact (RPC)  

Rate Our survey revealed that the mean RPC rate in the industry is 26%, with 38% of teams achieving an RPC rate between 20-29%. Improving your RPC rate is essential for maximising the efficiency of your collection efforts and reducing wasted resources.

To boost your RPC rate, start by ensuring the accuracy of your contact data. Regularly update and verify debtor information, and consider partnering with data providers to enrich your database. Implement a multi-channel contact strategy, leveraging a mix of phone calls, emails, SMS, and other communication methods to increase the likelihood of reaching the right party.

Analyse your contact attempts to identify the most effective times and days to reach debtors, and adjust your calling schedules accordingly. Train your agents to quickly identify and navigate through gatekeepers, such as family members or colleagues, to reach the right party efficiently.

Promise to Pay (PTP) Rate  

The survey found that the mean PTP rate is 29%, with 53% of teams securing promises to pay from 20-39% of their contacts. Obtaining a commitment to pay is a critical step in the debt collection process, as it sets the foundation for successful recovery.

To improve your PTP rate, equip your agents with strong negotiation and objection-handling skills. Provide training on active listening, empathy, and persuasion techniques to help agents build rapport and trust with debtors. Develop a range of payment options and solutions that cater to different debtor circumstances, such as flexible repayment plans, discounts for early settlement, or temporary payment holidays.

Empower your agents to make decisions within predefined parameters, allowing them to tailor solutions to individual debtor needs. Implement performance monitoring and feedback processes to identify and address any skill gaps or performance issues among your team members.

Percentage of Debt Collected  

The mean percentage of debt collected across surveyed teams is 32%, with 49% of teams recovering between 20-39% of their assigned debt. Optimising your debt recovery rate is critical for maintaining a healthy cash flow and minimising write-offs.

To boost your debt collection percentage, start by segmenting your debtors based on factors such as debt age, amount owed, and previous payment behaviour. Develop targeted collection strategies for each segment, prioritising high-value and high-propensity accounts.

Implement a robust collections management system that allows you to automate tasks, track performance metrics, and generate actionable insights. Use data analytics to identify trends, predict debtor behaviour, and optimise your collection processes.

If you’re collecting debt in-house, consider outsourcing hard-to-collect debts to specialised agencies, freeing up your team to focus on more recent and manageable accounts. Regularly review and adjust your collection strategies based on performance data and changing debtor dynamics.

First Call Resolution (FCR)  

The survey revealed that the mean FCR rate in the industry is 42.83%, with 33% of teams achieving an FCR rate between 30-49%. Resolving debt collection cases on the first call can significantly reduce costs, improve debtor satisfaction, and accelerate recovery.

To enhance your FCR rate, invest in comprehensive agent training that covers your organisation’s policies, procedures, and available repayment options. Equip your agents with the knowledge and tools they need to effectively address debtor queries, concerns, and objections in a single interaction.

Empower your agents to make decisions and offer solutions within predefined boundaries, minimising the need for escalations or callbacks. Implement a knowledge management system that provides agents with easy access to relevant information and guidance.

Analyse your FCR performance by case type, debt segment, and agent to identify improvement opportunities. Conduct regular call quality monitoring and provide targeted coaching to help agents refine their skills and techniques.

Data-Driven Decisions in your Contact Centre

By leveraging these industry benchmarks and implementing proven strategies, debt collection contact centre leaders can drive significant improvements in their team’s performance. Use these insights to set realistic targets, prioritise initiatives, and make data-driven decisions to optimise your collection processes.

Remember, successful debt collection requires a delicate balance of empathy, firmness, and regulatory compliance. By continuously monitoring your performance, staying attuned to industry best practices, and adapting to evolving debtor needs, you can position your team for sustained success in recovering outstanding debts while maintaining positive relationships with your customers.

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The public sector contact centre industry faces unique challenges in delivering high-quality customer service to the general public while managing tight budgets and dated technology. Here, we highlight several key themes and pain points impacting customer experience in 2024 across local governments in the UK.

Key Challenge #1: Slow Adoption of Digital Channels

One striking finding is the public sector’s low adoption of digital service channels compared to other industries. A recent report states:

“The public sector has some of the lowest take-up of digital channels of any sector, and telephony accounted for more than 80% of inbound interactions in 2018. However, 2020 onwards has seen a major increase in the use of telephony self-service, but this may be due to a drop in live telephony performance in the sector.”

While the central government has pushed for “digital-first” public services, progress has been slow. Public sector contact centres still rely heavily on phone interactions. Depending on the nature of the interaction, transitioning more people to digital self-service, when done well, can reduce costs while still providing easy access to services.

To boost digital adoption, public sector organisations should:

• Ensure digital services are well-designed, easy to use, and accessible to everyone, including the elderly and underserved populations. Define the digital channels’ purpose and then build relevant, helpful content for your contact centre team and the customer-facing assets. Providing excellent support for digital channels will help build trust and confidence.
• Heavily promote digital options and educate people on how to use them.
• Provide easy access to phone service for complex issues or people who require it—don’t try to reduce demand by hiding this option. It only leads to dissatisfaction when people need it the most.

Key Challenge #2: Outdated Technology

Public sector contact centres tend to lag in implementing newer technologies like AI, analytics, and automation.

“The public sector is generally slow to implement new technology, and the relatively small size of many operations also means that it is behind the technology curve, particularly for newer technology such as AI, analytics and email management, as well as outbound-focused technology such as automated outbound diallers.”

Legacy systems can negatively impact public sector contact centre teams’ customer experience and operational efficiency. Modernising the contact centre technology stack is crucial for handling interactions across channels seamlessly and extracting valuable insights from data across the public sector.

Some strategies to address outdated technology:

• Explore cloud contact centre platforms to reduce reliance on legacy infrastructure – which have feature limitations and lack integration options
• Consider point solutions, like outbound dialler technology – they help organisations to increase efficiency without the need to invest in long and complex digital transformation projects.
• Implement AI and automation in phases, starting with simpler use cases like AI-driven chatbots, web chat, and quality-of-life features that make communicating with customers more efficient.

Key Challenge #3: Worsening Speed to Answer

The general public’s expectations for fast service continue to rise, but public sector contact centres struggle to keep up. The report highlights a concerning trend:

“Public sector contact centres have usually seen a higher-than-average speed to answer, which has hugely risen since 2019 and is a concern. Some central government contact centres are under severe pressure to improve their performance, while local government operations will tend to have performance under better control, although their budgets are getting tighter, and they are forced to do more with less.”

Long wait times lead to frustration and more work for agents handling escalated complaints. Improving speed to answer requires a multi-pronged approach.

Tactics to try:

• Implement skills-based routing to match consumers’ requests with the best-equipped agent faster
• Expand self-service options for common requests to reduce live handle time; using tools like speech analytics helps operational leaders understand call drivers more accurately and shifts in conversation trends
• Explore callback technology to give people alternatives to waiting on hold
• Leverage workforce management tools to optimise scheduling and improve forecasting

Key Challenge #4: High Absence and Attrition

Agent engagement appears to be an emerging issue in public sector contact centres. Studies reveal:

“From 2017 until 2021, public sector agent absence rates were below the contact centre industry average. However, the high absence rate in 2022 and 2023 – in line with the jump in attrition and declining performance – is potentially cause for concern.”

Agents are the heart of the contact centre and directly impact customer satisfaction. High absenteeism and turnover disrupt operations and lead to inconsistent service levels as new agents are onboarded.

Some ways to combat absence and attrition:

• Invest in agent training and coaching to build confidence and competence
• Implement gamification to make work more engaging and rewarding
• Gather agent feedback regularly and take tangible actions to address pain points
• Provide clear career paths and opportunities for advancement

Key Challenge #5: Increasing Complexity and Cost to Serve

As people expect personalised, omnichannel service, interactions are becoming more complex for public sector contact centres to handle efficiently at scale. At the same time, budgets remain tight.
“Pent-up demand for phone service will continue to oppose the severe budget-cutting targets that exist at both central and local government levels, which are likely to cancel each other out to a great extent, leading to longer wait times and a greater likelihood of outsourcing, as little budget is available for growing the contact centre figures,” explains the report.

Organisations must find ways to do more with less, leveraging technology, data, and process improvements to reduce handle times and improve first-contact resolution.

Consider these strategies:

• Map customer journeys to identify and eliminate points of friction and unnecessary transfers
• Unify customer data across channels for a full view of interactions and context
• Analyse interaction data to surface opportunities for process improvement
• Implement knowledge management and AI tools to surface relevant information to agents quickly

How MaxContact has helped Dudley Council streamline their rental income collection process and improve community service:

In conclusion, while public sector contact centres face daunting challenges, a strategic approach incorporating new technology, enhanced self-service, and a continued focus on agent experience can help overcome these hurdles. By making steady improvements across channels, technology, and operations, organisations can elevate the quality and efficiency of customer service while effectively managing costs.

With the right strategy and investments, public sector contact centres can deliver the convenient, personalised interactions customers increasingly expect, reinforcing trust in public institutions. While not an overnight transformation, public sector leaders who commit to ongoing contact centre advancement can achieve meaningful progress in 2024 and beyond.

Find out more about how MaxContact can transform your public sector contact centre.

Source: Research public sector stats and quotes – “UK Contact Centre Verticals: Public Sector” (ContactBabel)

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If you work in a contact centre that operates in the debt resolution industry, you’ll know that achieving a high right-party contact (RPC) rate is key to success. After all, how can you collect payments efficiently if you’re not speaking with the right recipient in the first place?

Despite this, our recent benchmark report shows that many contact centres struggle to achieve optimal RPC rates. In fact, 23% of contact centres have a RPC rate below 20%, while the industry average sits at just 26%.

So, what can contact centre managers do to improve their RPC rates and, ultimately, increase the percentage of debt collected?

In this blog post, we’ll explore effective strategies that can help your call team connect with the right people consistently.

Challenges to Achieving High Right-Party Contact Rates

Contact centres in the debt collection industry need to carefully consider and address several common challenges to improve right-party contact rates (RPCs).

Challenge 1: Poor Data Quality & Incorrect Information

Poor data quality is a common culprit of low right-party contact rates (RPCs). When contact information is incorrect, incomplete, or outdated, it becomes difficult to reach the intended recipient, leading to wasted time and resources.

Here are some examples of data quality oversights and their consequences:

Oversight: Inaccurate or incomplete information due to data entry errors, system integration problems, or customer-provided data.

Consequence: Difficulty reaching the intended recipient, wasted time and resources and reduced customer satisfaction.

Oversight: Duplicate records for the same customer, once again caused by data entry errors or inconsistent data sources.

Consequence: Confusion and inefficiency in call routing, resulting in unnecessary attempts to contact the same person.

Oversight: Outdated contact information due to changes in addresses, phone numbers, or email addresses.

Consequence: Failed attempts to reach customers, decreased efficiency and potential lost revenue.

Challenge 2: Inefficient Call Routing

Call routing is an invaluable tool- but only when used correctly. Inefficient call routing is another culprit of low RPCs. Here are some examples of the oversights contact centres often make with call routing and the impact on KPIs.

Oversight: Call routing rules are not implemented properly or updated.

Consequence: Calls are directed to the wrong agents or departments. Unnecessary transfers and delays lead to frustrated customers and negatively impact agent efficiency.

Oversight: Outdated call routing systems are not updated in real-time with information about agent availability, call volumes and customer preferences.

Consequence: If a system is unaware of a sudden increase in call volume or an agent’s unavailability, it will continue to route calls to that agent, resulting in inefficient routing and longer wait times.  

Oversight: Agents aren’t trained to identify and route calls correctly.

Consequence: Untrained agents may misinterpret caller information, direct calls to the wrong departments, or transfer calls to agents ill-equipped to handle the customer’s query.

The Impact of Low Right-Party Contact Rates

Low right-party contact rates lead to increased costs, reduced customer satisfaction and potential compliance issues.

Let’s explore each one in more detail to understand the impact.

Increased Costs

• Inefficient call routing leads to agents spending time on unproductive calls, wasting resources and delaying debt recovery.
• Dealing with frustrated customers and repetitive tasks contributes to high agent turnover rates, increasing hiring and training costs.

Reduced Customer Satisfaction

• Difficulty reaching debtors can lead to missed payments and lower debt collected percentages.
• Negative customer experiences can tarnish a debt resolution company’s reputation, making it harder to collect debts in the future.
• Frustrated debtors may take legal action against debt resolution companies, leading to increased legal costs and potential reputational damage.

Potential Compliance Issues

• The Financial Conduct Authority (FCA) has guidelines to treat customers fairly and reasonably. If contact centres fail to reach the right party, it can be seen as a breach of this requirement, leading to regulatory action, including fines or penalties.

Strategies for Improving Right-Party Contact Rates

How to Manage Data Accuracy and Quality

So we know the accuracy and quality of contact data impact right-party contact rates, but what strategies can call centres action to improve data?  

StrategyOverviewStrategy 1: Implement a Data Cleansing and Validation ProcessIt’s important to regularly review and clean contact data to remove typos, inconsistencies and outdated information. Use data validation tools to ensure data is formatted correctly and adheres to specific standards.Strategy 2: Enrich Contact DataSupplement existing data with additional information, such as demographic details, preferences and recent interactions. This can help you tailor your outreach efforts and increase the likelihood of reaching the right person at the right time.Strategy 3: Integrate with CRM SystemsConnect your contact centre software with your CRM system to access comprehensive customer information and ensure data consistency. This can help you avoid duplicate records and provide agents with a complete view of each customer’s interactions.Strategy 4: Leverage Third-Party Data SourcesSupplement your existing data with information from third-party providers to improve targeting and accuracy. Consider using demographic data, credit bureau information, or social media data to enhance your understanding of customers.Strategy 5: Establish Data Governance PoliciesDevelop clear policies and procedures for data management and quality. This includes regular data audits, data cleansing, and data retention guidelines. To ensure this is carried out effectively, all employees must be aware of and adhere to these policies.Strategy 6: Combine Accurate Data with Automated DiallingAutomated dialler systems can reduce human error and improve call efficiency. However, accurate data is essential for these auto-diallers to function effectively and minimise wasted calls.Strategy 7: Monitor Data Quality MetricsUse analytics tools like MaxContact’s reporting capabilities to track RPC rates, data accuracy and other relevant metrics. This will help you identify areas for improvement and make data-driven decisions to enhance your contact centre’s performance.

How to Optimise Call Timing

Call timing plays a key part in improving right-party contact rates and debt recovery. Here are some effective strategies to enhance call timing.

StrategyOverviewStrategy 1: Introduce Predictive DiallingPredictive dialling can automatically dial numbers based on predicted availability and considers factors such as past call history and customer behaviour. This reduces the time agents spend on unanswered calls and improves overall efficiency.Strategy 2: Analyse Historical DataUse MaxContact’s analytics features to examine historical data and identify optimal calling times for debtor segments. Consider factors such as the day of the week, time of day and specific customer preferences when scheduling calls.Strategy 3: Implement Skills-Based Call RoutingSkills-based call routing directs calls to agents with the appropriate skills and expertise to handle specific debt collection scenarios, such as dealing with difficult debtors or negotiating payment plans. Customers are connected with the best-qualified agents, improving their overall experience and increasing the likelihood of successful debt recovery.Strategy 4: Use Intelligent Retry StrategiesImplement a system of intelligent retries to increase the chance of reaching debtors when calls go unanswered. Vary the time between call attempts based on factors such as the debtor’s history, the urgency of the debt and previous attempts. Consider omnichannel communication, such as email or text messages, to reach debtors who may not answer phone calls.

How to Boost Call Agent Skills in Debt Collection

Agent training and development can improve right-party contact rates and enhance overall performance. Here are some ways you can deliver impactful training:

StrategyOverviewStrategy 1: Give Comprehensive TrainingTrain agents on customer data, contact strategies and communication skills, all tailored to debt collection. Utilise features such as call scripting and training on objection handling to equip agents with the tools they need to interact with customers effectively.Strategy 2: Analyse Call PerformanceUse speech analytics to analyse call transcripts and identify areas for improvement in agent performance. This can help you pinpoint areas where agents may need additional training or coaching.Strategy 3: Prioritise Regular Feedback and CoachingOffer regular feedback and coaching to agents based on their performance analysis. Address identified areas for improvement with tailored coaching, helping agents develop their skills and increase their confidence (and boost your retention rates).Strategy 4: Track Additional KPIsMonitor additional KPIs such as average handle time (AHT), average call rate (ACR), and customer satisfaction (CSAT) alongside RPC to gain a more comprehensive view of agent performance. These metrics can help you identify areas for improvement and measure the impact of your training and development efforts.

By implementing these strategies to improve data quality, call routing and call agent skills, debt resolution contact centres can significantly improve their right-party contact rates and achieve better outcomes.

Incorporating advanced outbound contact centre software is essential for achieving these goals. Features such as auto-diallers, speech analytics and reporting analytics can provide valuable insights and automation capabilities and help measure performance.

By investing in the right technology and implementing effective strategies, you can overcome the challenges highlighted in our benchmark report and achieve higher RPC rates. Increase revenue, improve customer satisfaction and reduce operational costs, ultimately boosting the overall performance of debt resolution.

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Key Takeaways

In our recent webinar, we explored how intelligent conversation analytics is transforming contact centres operations. MaxContact’s Leah Tillyer and Conor Bowler demonstrated how our Success Intelligence solution empowers teams to enhance performance, provide personalised coaching, and drive better business outcomes.

The QA Challenge

Traditional quality assurance approaches are failing contact centres. Our research reveals that most operations:

• Review only 2-3% of calls through random sampling
• Struggle with clunky legacy speech analytics platforms
• Wait 48+ hours for insight synchronisation
• Miss valuable opportunities hidden in 97% of unanalysed conversations

Performance Benchmarks That Matter

Our independent benchmark survey of 500+ contact centre leaders revealed:

• Teams making more strategic calls (avg. 65 per agent daily) achieve greater success
• First call close rates average 28%, indicating training effectiveness
• Average conversion rates for campaigns hover around 7%
• Each successful call generates approximately £200 in revenue per agent

The Future of Sales Success: Smarter Listening

Success Intelligence delivers:

• Complete visibility across all customer interactions, not just a small sample
• Objective sentiment analysis to track customer emotions and identify coaching opportunities
• Powerful objection tracking to understand patterns and measure handling effectiveness
• Data-driven coaching insights to help agents improve faster without blanket training

Download the Slides

Webinar Transcript

[00:00:04] Leah Tillyer: Hello and welcome. I’m just going to let people join as

[00:00:14] Leah Tillyer: we just go through some housekeeping elements.

[00:00:20] Leah Tillyer: so, whilst people are joining, the session is being recorded, and it will be shared afterwards. So if you do need to drop at any point, don’t worry. It will be there as a playback.

[00:00:33] Leah Tillyer: We encourage questions throughout the session. So we run the sessions, live every single month.

[00:00:41] Leah Tillyer: and we encourage questions just so other people can learn might be something they were thinking about and wanted to know, too. And

[00:00:51] Leah Tillyer: yeah, if if you think it’s useful, and it will be useful for somebody else, too, please do feel free to share as well.

[00:01:01] Leah Tillyer: so I can see numbers are creeping up now, and I’ll just do some introductions.

[00:01:11] Leah Tillyer: So Hi, everyone, I’m Leah, I’m product marketing manager here at Max contact. And my role is all about understanding our customers. So just understanding what they need, challenges that are faced and how our solutions can help them to succeed. I work really closely with Conor and the product team and with the sales team and customer success and look at how we bring new features to market

[00:01:39] Leah Tillyer: hopefully ensure clear and compelling messaging, and help businesses to get the most value from Max contact and our technologies.

[00:01:47] Leah Tillyer: and Conor is on the call with me. So he is principal product manager at Max contact. He brings over 16 years of product leadership experience across a diverse technology range, including contact centre software, financial services and AI solutions as well.

[00:02:07] Leah Tillyer: His career began in engineering and development. He progressed through roles in professional services, pre-sales and channel management, a lot of variety, and I’m sure a lot of empathy across those different roles, and notably Connor launched A. b 2 b product that attracted over 15,000 clients. It secured patents for AI innovations

[00:02:29] Leah Tillyer: and it revitalised product from decline to growth, which is no easy job. So at Max contact. He leads a spoken product focusing on enhancing contact center analytics to provide businesses with actionable insights for improved decision making.

[00:02:48] Leah Tillyer: And so that’s a little bit about us.

[00:02:51] Leah Tillyer: and we have some existing customers on the call, which is good to see and a few new faces as well. So a little bit about MaxContact for anybody that doesn’t know us. So we’re the best Cloud Contact Centre software for delivering conversation outcomes and customer insights to generate more revenue compliantly, and our customers are across the sales collections and customer service space.

[00:03:20] Leah Tillyer: And they work with Max contact to build better and more intelligent contact strategies that deliver results. So

[00:03:29] Leah Tillyer: for our customers. Since working with us, they’ve seen talk, time, sales, conversion rates and debt collection rates double since working with us.

[00:03:40] Leah Tillyer: and at the beginning of 2024 we launched, spoken.

[00:03:45] Leah Tillyer: So we have over 4 million hours of transcribed calls and summarized calls, topics tagged, and sentiment tracked, and it’s quickly trending upwards as well, which is very exciting.

[00:03:59] Leah Tillyer: And at the beginning of this year we launched success, intelligence, and that is what we’re here to talk about today. So success, intelligence is conversational analytics for better sales, performance and customer experience. It provides visibility on missed buying signals, common objections, and, most importantly, objection, handling effectiveness as well.

[00:04:25] Leah Tillyer: but before we go into that we’re going to talk a little bit about what we see across contact centres, and why and how they’re missing valuable insights. And so we use speech analytics. The. This is how we gather our insights as a business. So we’ll play a little bit of QA Bingo and just see how many of these resonate with you.

[00:04:51] Leah Tillyer: In terms of how customers usually operate when we speak to them. They’re either already using a speech analytics software and that they’ve maybe had for a few years, or they’re doing things manually. So

[00:05:06] Leah Tillyer: if they’re manually listening to calls, they usually have an excel spreadsheet. Typically in front of them. They are having to look out for compliance elements. So was a direct debit mandate read out on a call. They’re looking for

[00:05:27] Leah Tillyer: legalities that might need to be said, and then on the flip side of that, they’re also looking at performance metrics as well. So

[00:05:34] Leah Tillyer: 2 very different things to look out for, and looking at how empathetic an agent was on the call. Did they actively listen for things that were being said, and 2 very different things to be listening out for. And I know when we’ve spoken to clients about this in the past, it’s often question time when they’ve got the headphones on. People are coming over. They’re asking questions. They’re having to stop, start the process.

[00:06:00] Leah Tillyer: And so it’s really time consuming.

[00:06:03] Leah Tillyer: And they’re not always capturing the things that they need to.

[00:06:07] Leah Tillyer: And then we have on top of that random call sampling. So they’re going through picking out random calls with no

[00:06:19] Leah Tillyer: no kind of strategy behind it, just hoping to to pick a couple of variations, to give some good feedback and make sure compliance. Elements are being carried out, and then the call sampling is often limited as well. So some clients that we speak to will do a couple of calls per agent per month, and others

[00:06:41] Leah Tillyer: a couple of calls per agent per quarter. They just don’t have the man hours or the resource that they need. And it’s a really time consuming task. They’re taking extensive notes throughout. So I’m sure that resonates with a few people. And then on the flip side of that where where contact centers or teams have a speech analytics software already.

[00:07:06] Leah Tillyer: it’s not a new technology. It’s been around for between 10 and 15 years now. So if they’ve had it for a while. It’s often clunky and cumbersome. It can be inaccurate because it relies on

[00:07:19] Leah Tillyer: the manual input of data and the manual tagging of data. The technology behind speech. Analytics now has come a long way with the introduction of AI. But if you’re using a legacy platform or product, it can be a time consuming process. They’re often really complicated and complex to set up. And

[00:07:43] Leah Tillyer: with that comes a lot of

[00:07:46] Leah Tillyer: time consuming maintenance to keep it up to date and relevant as well.

[00:07:50] Leah Tillyer: and sync delays are a big issue. We speak to customers where their previous platforms would sync twice a week, and and of course, in terms of the information that they need to get back. People want that within the within 24 h, or as near to real time as possible. And then this siloed data across the contact center. It’s usually a separate system. It doesn’t integrate with their call software. And

[00:08:19] Leah Tillyer: so because of those reasons.

[00:08:21] Leah Tillyer: contact centres, sales and customer service and debt collection teams are missing out on really valuable insights. They’re not seeing the whole picture across the contact centre. They’re seeing a really small part of it, and the process behind it is

[00:08:39] Leah Tillyer: It’s clunky. It takes time. It’s not something that’s prioritized as a business.

[00:08:47] Leah Tillyer: We last year as a as a company, carried out an independent benchmark survey of over 500 Contact Center leaders in the sales and collections and customer service space and we were looking at metrics

[00:09:04] Leah Tillyer: to track across those areas and how they drive successful outcomes for businesses. So looking at sales performance today? And how do you compare? How does your sales team compare? And how do you start to deliver and drive results?

[00:09:22] Leah Tillyer: And some of the things that we were seeing across different contact centres was, I’m sure we’re already aware of this. But sales is a numbers game. So the report showed that teams made up that made more calls tended to achieve greater success. So the average number of calls from this report was around 65 per agent, which is

[00:09:46] Leah Tillyer: a really big number of calls to hit. And it’s where your automated dialling technology comes in. And obviously, the more calls you’re making and the more strategic you are with those calls as well with with

[00:09:59] Leah Tillyer: skills, matching, and things like that. The higher the success rate is. And then we looked at

[00:10:05] Leah Tillyer: 1st call close rate as well. So the higher that your 1st call close rate, it typically shows how well your team are trained and qualified to convert. So a low call, close rate. It might indicate a lack of empathy on a call or a poor understanding of the product or the service that they’re selling or not understanding or able to convey their value. Proposition.

[00:10:29] Leah Tillyer: So average 1st call close rate was around 28% across the contact centres that we surveyed.

[00:10:40] Leah Tillyer: and then just looking at conversion rates as well. And across those so average conversion rates for campaigns is around 7%. And that’s

[00:10:52] Leah Tillyer: that’s within the I guess, above average range with around 26% of contact centres falling into that good range of between 4 and 5%.

[00:11:04] Leah Tillyer: So just some nice benchmark stats to be looking at there around performance of your sales team within the contact centre, and what they’re coming up against.

[00:11:15] Leah Tillyer: And we also looked at some roi stats as well. So how much revenue is generated per agent per successful call, and and this was looking at nearly 200 pounds per agent per successful call. So really giving you an understanding of the Roi per campaign or team or user.

[00:11:40] Leah Tillyer: I think it’s important to have a view of how other contact centres are performing. But also looking at how you benchmark against yourself in these metrics. And as you start to look at introducing dial in technology or using dial in technology and improving it. With different tactical approaches, with the campaigns. Introducing things like speech analytics. How you then improve. Your own benchmarks

[00:12:10] Leah Tillyer: and tracking is, I think.

[00:12:15] Leah Tillyer: and understanding performance is half of the picture. But I think the future of sales success. It really lies in smarter listening. And so that’s something that we’re going to talk about a little bit more now, with Connor. So I’m going to

[00:12:39] Leah Tillyer: Pass over to Connor to share his screen.

[00:12:44] Leah Tillyer: we’re going to go off camera for this now, just so you can concentrate on what is being shared.

[00:12:56] Conor Bowler: All right. So, as Leah said, the future of sales, success is smarter listening.

[00:13:01] Conor Bowler: So it’s all about turning every conversation you have into competitive edge

[00:13:06] Conor Bowler: customer experience. Obviously about the 3 S’s success, sentiment, and satisfaction

[00:13:11] Conor Bowler: with your traditional CCaaS analytics. You’re only going to get the 1st 3 of these with spoken. You’ve got all 3 the full picture.

[00:13:20] Conor Bowler: So we’re focused on success intelligence today to track agent performance and providing coaching insights. So you’re seeing their true behaviors, habits, and trends.

[00:13:29] Conor Bowler:  But let’s start with improving visibility into AI insights to call sentiment for agents. So you want to get a consistent objective view of customer emotions across every single call.

[00:13:40] Conor Bowler:  Not just a few. You Qa. Manually.

[00:13:43] Conor Bowler:  What happens to cinnamon when you make some changes to a script are running some training

[00:13:49] Conor Bowler:  onboarding a new agent.

[00:13:52] Conor Bowler: So at Spokn AI you have a whole set of charts to do this.

[00:13:55] Conor Bowler:  Let me show you so. If I take a look at last month. Yeah, I can see that there’s been some small shifts. So we’ve gone from 73% to 74% positive sentiment.

[00:14:06] Conor Bowler:  But equally, we’ve gone from 8% negative sentiment to 9%, a small hop up

[00:14:12] Conor Bowler:  and let’s like, kind of look down and drill into it and see if we can kind of understand.

[00:14:18] Conor Bowler: So if I kind of come down the bottom here, we have lots of different charts

[00:14:23] Conor Bowler:  and tables to help you kind of understand why that’s happening. If we keep this conversation focused on like agent performance and coaching.

[00:14:31] Conor Bowler:  then, instead of looking at campaigns, I might look at users.

[00:14:35] Conor Bowler:  so is there a lack of empathy or emotional intelligence for some of my agents? Can I coach them on building a better rapport.

[00:14:44] Conor Bowler:  maybe, Andre here. He’s pretty high

[00:14:47] Conor Bowler: as I scroll down through them.

[00:14:50] Conor Bowler: You can see that there are others in that same kind of boat. So we have Eric here. And Estelle.

[00:14:56] Conor Bowler:  Okay, I also have all of the different topics that are discussed on the call

[00:15:01] Conor Bowler:  and the kind of level of sentiment towards each of these. If the sample size that I’m looking at is too large, then I can drill down even further.

[00:15:11] Conor Bowler: All right. So let me go back up here. My sample size currently is 7,630. We’ll look at how we filter.

[00:15:20] Conor Bowler: We have like really broad and kind of powerful filters. So I can filter down by perhaps an individual campaign. If that’s what I’m interested in

[00:15:29] Conor Bowler: by list or data supplier to see if it’s a data quality issue that’s leading to this kind of like negative sentiment.

[00:15:35] Conor Bowler:  I can have a look at the Peak sentiment or the end sentiment on the calls. So what’s happening at the most intense parts of the calls. And what’s happening at the end of the calls, which are the ones that kind of truly affect those 3 s’s of like customer experience.

[00:15:51] Conor Bowler:  But in this case let’s filter down by topic.

[00:15:57] Conor Bowler: So all was discussed on the call.

[00:16:00] Conor Bowler: So if I hit in disputes here, and I apply that filter

[00:16:07] Conor Bowler: unsurprisingly, you’ll see the negative sentiment hop right up there.

[00:16:12] Conor Bowler: Okay, now that I’ve got my calls. So I have like 332. Now, instead of my 7,000 and odd, some kind of a manageable number.

[00:16:22] Conor Bowler: I can go in to look at them so I can click on this playback page. Here I can see all the different interactions that supported. I can look through the summaries of those calls.

[00:16:33] Conor Bowler: and there are kind of overall view of sentiment, the transcripts, the sentiments in there, too, kind of any objections that came up in the call, the history of the call. Everything. Okay, I can even kind of drop down into the recording itself and understand where the different pieces of sentiment were and where the objections were in the different parts of the call, so I can go straight to those. I can play it at like double speed and everything to make sure that we’re getting it like

[00:17:01] Conor Bowler: done quickly.

[00:17:03] Conor Bowler:  So you want all of this because well, customer experience is emotional, isn’t it? It’s about how how customers feel during those interactions

[00:17:12] Conor Bowler: to give you that sentiment and satisfaction that you’re combining with your Ccas analytics to give you success.

[00:17:18] Conor Bowler: retention, and loyalty are obviously tied to emotion. So negative sentiment, especially when you don’t notice it leads to churn poor reviews, damage, brand trust.

[00:17:29] Conor Bowler: and agents need this kind of feedback. So without visibility, agents don’t know when they’re succeeding emotionally or falling short.

[00:17:37] Conor Bowler: Okay, now, let’s navigate here to our Success Intelligence Page, and look at some of these additional tools

[00:17:48] Conor Bowler: that allow you to kind of track the performance and provide coaching insights.

[00:17:55] Conor Bowler: So here we have kind of call etiquette statistics.

[00:18:00] Conor Bowler: So we can look at longest monologue or longest silence to figure out if the talk to listen. Ratio

[00:18:07] Conor Bowler: isn’t right across a campaign, a team or a user.

[00:18:10] Conor Bowler: Okay, we’re looking at users right now as that’s where we’re focused.

[00:18:16] Conor Bowler: I have these stats for all of the individual users. They are combined with their conversion rates. There’s a number of successes that they’re having the successes per hour, all of that. So you can kind of begin to judge them holistically.

[00:18:30] Conor Bowler: Okay, equally, I can have a look at their objections.

[00:18:36] Conor Bowler: So we’re going to look at their objections so that they can turn more, maybe Laters into yes, nows like consistently.

[00:18:45] Conor Bowler: So here we can see the different objection categories that are trending.

[00:18:49] Conor Bowler: How is the coaching that we’re going to deliver, affecting what is here affecting the trending of the objections?

[00:18:57] Conor Bowler: So we have all of the objections into categories. They’re in need, time, trust, and cost.

[00:19:04] Conor Bowler: But equally we can drill down by individual reasons. So maybe I am, and kind of tick them on and off. So maybe I just want to see the trend and not interested

[00:19:18] Conor Bowler: here. We go over that period of time.

[00:19:21] Conor Bowler: and we’re really kind of measuring. What matters. So by tracking that objection, frequency, the resolution success rates alongside, the sentiment shifts. We looked at earlier.

[00:19:31] Conor Bowler: We tie that frontline kind of conversations directly into business outcomes.

Conor Bowler: So we can analyze those objection patterns, and what we’ll do with them is refine our messaging our offers scripts so that fewer objections come up. In the 1st place.

[00:19:52] Conor Bowler: beneath it there’s a table of all the objections. And again, it’s kind of

[00:19:56] Conor Bowler: categorised by into the various different categories of need, trust, cost, etc.

[00:20:02] Conor Bowler:  But also kind of has it alongside conversion rate, some success statistics. And then you have the effectiveness, and that’s the key one here. The effectiveness is, how how many times that agent handled that objection successfully or not.

[00:20:22] Conor Bowler: So if we drill through.

[00:20:27] Conor Bowler:  So I can see that trending in a kind of breakdown of handling effectiveness.

[00:20:33] Conor Bowler: So here’s my kind of basic information. I’m not interested. Here’s the trending of it in it, the different weeks, but also down the bottom. Here are my different agents, and how effectively they’re handling that not interested objection.

[00:20:49] Conor Bowler:  Okay.

[00:20:51] Conor Bowler: not only that, but I can go up here, and I can like click in, and it’ll just highlight my top and bottom performance in this kind of area.

[00:21:03] Conor Bowler:  And I can drill through to see those various interactions.

[00:21:08] Conor Bowler: Okay, there’s only like 4 or 5 or 9 here. So I’m going to go back.

[00:21:14] Conor Bowler: And maybe what I want to do is drill through all of those different things.

[00:21:20] Conor Bowler: So I’m going to go to my filters again. I’m going to add my objection of not interested.

[00:21:32] Conor Bowler: Apply those filters and have a look at the calls.

[00:21:38] Conor Bowler: Okay, so here are all calls where the objection not interested has come up.

[00:21:46] Conor Bowler: and I can go through those like my sentiment calls individually.

[00:21:50] Conor Bowler: and look through those kind of summaries, transcripts, histories to kind of figure out what’s going on. But equally I might do something a little smarter.

[00:22:00] Conor Bowler: and I find it really interesting to understand the calls that are not interested, but whereby there was some buying signals on them. So let me add a filter here, and we have all of these kind of search and transcript filters.

[00:22:14] Conor Bowler: so I could add some kind of buying criteria that I’m looking for. So if it maybe contains

[00:22:23] Conor Bowler: how much is it that’s kind of a buying signal. If the customer is talking about payment plans, another buying signal, and really, we want to. If any of these come up. So instead of the Ands, I’m going to turn this to an or how soon could I get it? Is it in stock right now? Can I pick it up today? All buying signals?

[00:22:44] Conor Bowler: I’ll just talk to my partner.

[00:22:48] Conor Bowler: It’s another good one, or I just need to check my budget and be helpful. If I could sell.

[00:22:56] Conor Bowler: I can add individual groups within these

[00:22:59] Conor Bowler: and continue to add those groups and make them more complex or less complex. Okay, so there’s

[00:23:05] Conor Bowler: it’s really kind of within your hands as to what you want to look at.

[00:23:09] Conor Bowler: I apply these filters.

[00:23:12] Conor Bowler: There we go. We have gone down from kind of our top things to just 40 items that so calls that have not interested objections that are

[00:23:24] Conor Bowler: that have buying signals within them.

[00:23:27] Conor Bowler: And I could even go and kind of say, well, it doesn’t really matter until unless it’s like not a successful call. So I can add that as a filter as well.

[00:23:38] Conor Bowler: Okay.

[00:23:42] Conor Bowler:  not only that, but we make all of this information. So all of the call summaries, the transcripts, the sentiment, the objection handling, we make it available directly to individual agents within the contact hub, agent platform.

[00:23:56] Conor Bowler: And that’s so. The agents themselves can be more efficient, and they can look at themselves how to self-improve.

[00:24:03] Conor Bowler:  But essentially all of these tools, mean, spoken helps coaching become more personalized and precise. So helping ages to improve faster without blanket training sessions, we can stop top, spot, even spot, top and bottom performance performers, track improvement over time and set goals with data. So not just instincts anymore

[00:24:25] Conor Bowler: providing this kind of feedback and allowing those agents to self serve on some of that feedback boosts employee engagement and reduces turnover.

[00:24:36] Conor Bowler: as a whole Spokn AI doesn’t just help you to listen to your customers. It helps you to understand them at scale, so it brings those hidden insights to the surface. It empowers your agents to perform at their best, and it gives your leadership the visibility needed to make faster and smarter decisions.

[00:24:54] Conor Bowler: All right, let’s go back to the main webinar.

[00:25:02] Leah Tillyer: Thank you, Conor, for running through that it was good to see in action, and just put some of

[00:25:11] Leah Tillyer: Some of those use cases to life around QA, and how it could be done differently, and how the coverage can be across everything, and then the insights that that can reveal. If anybody has any questions, now is the time to ask

[00:25:33] Leah Tillyer: Okay, we’ve got a question. How are you exploring? The debt collection use case. So we have clients across sales, debt collection and customer service. So that’s something we’ve not spoken about yet.

[00:25:48] Conor Bowler: Yeah, so I think the objections are really different, aren’t they? Cause they’re different use cases. So there are. The categories are much less kind of need and trust.

[00:25:59] Conor Bowler: But they’re more kind of can’t pay, won’t pay, and the variety of like different things underneath that we’re partnering with the Debt Collection Contact Center at the moment to build those out.

[00:26:10] Connor Bowler: And if I if I if anyone on the call like, wants to volunteer and and partner with us that’d be great as well.

[00:26:16] Connor Bowler: And we expect to have those done in the next few weeks.

[00:26:20] Leah Tillyer: Yeah, amazing. And you you showed the filters there as well. And the buying signals.

[00:26:27] Leah Tillyer: can you save the filters? What? What?

[00:26:30] Leah Tillyer: Yes, like? How complex can you get with them?

[00:26:34] Conor Bowler: Yeah, so those kind of transcript filters like you can write up to 250 or so different things, you know.

[00:26:41] Conor Bowler: and he can.

[00:26:42] Conor Bowler: and mix them with different logical operators, and or, as you can say, whether they have to be like bang on, whether they don’t contain things as an out of compliance whether they’re similar to or like

[00:26:57] Conor Bowler: And yeah, so like, if you’re writing those 250 different things you don’t wanna like, do it over and over again. So definitely, yeah, you can save those filters, click on it and then come back every day and and have a look at your miss buying signals for yesterday, or your competitor mentions for yesterday or your script. Adherence issues for yesterday, or you’re out of compliance. Calls for yesterday.

[00:27:18] Conor Bowler: Yeah.

[00:27:19] Leah Tillyer: Yeah.

[00:27:19] Leah Tillyer: Amazing

[00:27:21] Conor Bowler: Yeah.

[00:27:21] Leah Tillyer: Thank you. We have. We’ve got a couple more questions that have come in. So the 1st one can the analytics for spoken AI be downloaded into an excel spreadsheet

[00:27:34] Conor Bowler: Yeah, okay. So they

[00:27:39] Conor Bowler: there’s a like a download button on the top, right

[27:39] Conor Bowler: there’s a like a download button on the top, right? They can be like pulled out into PDFs.

[27:47] Conor Bowler: We’re looking to kind of like. Do some kind of chatbot integration as well.

[27:54] Conor Bowler: right now. No, they they can’t be pulled out into an Excel spreadsheet. You can pull them out into the PDF. And then take them from there into the Excel. But

[28:02] Conor Bowler: it’s a good. It’s a good shout and yeah, something we should definitely look at

[28:07] Leah Tillyer: Yeah, absolutely. Thank you. And then the next question is, how are the objection? Categories determined as a fundraising agency? We will have slightly different objections to normal contact centres.

[28:21] Conor Bowler: I think that’s similar to to the kind of 1st question around, you know, like there’s various different sales objections. And then there’s

[28:30] Conor Bowler: you know, the debt management type of stuff has different objections again.

[28:33] Conor Bowler: And yeah, if we’d love to work with you as a as a kind of charity or fundraising agency in order to be able to determine what those are and get that kind of training set.

[28:46] Conor Bowler: So

[28:47] Conor Bowler: we essentially like, take a lot of your calls. Initially, we like run through them. We find kind of open questions from there. We kind of put them through small language models, and we like, consolidate them to understand what the objections should look like. We feed them into spoken, and then they get pulled out as objections from there on

[29:07] Leah Tillyer: Yeah, I mean.

[29:08] Conor Bowler: So definitely, we can do that as well

[29:10] Leah Tillyer: Yeah, it was an anonymous question. So whoever reached out, if you we do, we run design partner programs. That’s something we do with all of our customers, and if there’s something we’re exploring, or there’s something new that we’re taking to market, we often work with a client on that, and what that looks like and start to build that out with real life, scenarios and data and information. So yeah, and please do get in touch off the back of the webinar. We’d love to see if we can work with you on that one.

[29:41] Leah Tillyer: I’m gonna say, final call for questions. There’s no more that popped up, but this is usually when they do pop up. I guess, whilst we’re waiting to see if any more come in just to to recap on some of the things that we have covered. So we’ve just understood a little bit more around. How? How contact centers, how sales collections and customer service are currently doing QA, and

[30:07] Leah Tillyer: how that can be evolved to give more insights to the contact center. We looked at some benchmark stats across sales, and how other businesses are doing it, and how they’re performing. And of course we’ve explored spoken, and the newest feature within that which is success, intelligence. If there are any existing spoken clients on the call

[30:31] Leah Tillyer: you should all have access to success. Intelligence now within the existing spoken package, and for any customers looking to explore, spoken as well, and for

[30:43] Leah Tillyer: for a limited amount of time we’re including spoken

[30:46] Leah Tillyer: within the base package as well. So it’s a good time to have the conversation.

[30:51] Leah Tillyer: And so there’s no more questions that have popped up. But yeah, thank you, everybody for your time. Thank you for Connor for running us through that, and we will share the recording afterwards as well

[31:05] Conor Bowler: Cheers! Folks take care!

[31:06] Leah Tillyer: Lovely bye, bye.

[31:07] Conor Bowler: Bye, bye.

Your Questions Answered

Adapting to Different Industries

Q: How are you exploring the debt collection use case?

Connor Bowler, Principal Product Manager: “The objections in debt collection are really different from standard sales objections. Rather than categories like ‘need’ and ‘trust,’ they’re more focused on ‘can’t pay’ versus ‘won’t pay,’ with various subcategories beneath those. We’re currently partnering with a debt collection contact centre to build out these specialised objection categories, and we expect to have those completed in the next few weeks. We’d welcome any volunteers from the call who’d like to partner with us on this initiative.”

Q: How are the objection categories determined for a fundraising agency? We will have slightly different objections to normal contact centres.

Connor Bowler: “This is similar to the first question about different sales objections versus debt management objections. We’d love to work with you as a charity or fundraising agency to determine what those specific objection categories should be and develop the appropriate training set. Our process involves taking a sample of your calls, running through them to identify common patterns, using small language models to consolidate these patterns, and then feeding them into Spoken to automatically detect these objections going forward.”

Leah Tillyer, Product Marketing Manager: “We run design partner programmes with all of our customers. When we’re exploring something new or taking it to market, we often work directly with a client to build it out with real-life scenarios, data, and information. We’d love to connect after the webinar to explore working together on this.”

Technical Capabilities

Q: Can the analytics for Spoken AI be downloaded into an Excel spreadsheet?

Connor Bowler: “There’s a download button in the top right that allows you to pull reports out as PDFs. Currently, you can’t export directly to Excel, but you can take the PDF and convert it to Excel. It’s a good suggestion and something we should definitely look at implementing. We’re also looking to integrate some chatbot functionality in the future.”

Q: Can you save the filters? How complex can you get with them?

Connor Bowler: “Yes, you can save filters, which is especially useful since our transcript filters allow you to include up to 250 different search terms. You can mix these with different logical operators like ‘and’ or ‘or,’ specify whether matches need to be exact, exclude certain phrases for compliance checks, or look for similar patterns. Once saved, you can click on a filter and reuse it day after day to check for missed buying signals, competitor mentions, script adherence issues, or compliance concerns from yesterday’s calls.”

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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.

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Key Takeaways

In this insightful session, Kayleigh Tait (Head of Marketing) and Ben O’Reilly (Training Specialist) share how to create an intelligent contract strategy by leveraging consumer behaviours to build trust and drive better results.

Our latest research explores how UK consumers feel about AI in customer interactions and what businesses need to know to enhance their contact strategies.

1. Customer Expectations Are Higher Than Ever

• 80% of customers expect businesses to anticipate their needs and provide personalised interactions.
• Businesses that fail to understand consumer preferences risk losing engagement and loyalty.

2. The AI Acceptance Gap

• Younger consumers are more comfortable with AI – 65% of 25–33-year-olds are happy to engage with AI-powered interactions.
• In contrast, only 27% of over-55s feel comfortable with AI, and 52% of them actively prefer human interaction.

3. Human Connection Still Matters

• Despite AI advancements, 60% of customers prefer speaking to a human agent for complex queries or emergencies.
• AI should enhance—not replace—the human element in customer interactions.

4. Speed to Lead Directly Impacts Conversions

• Businesses that respond within five minutes can achieve up to 70% conversion rates.
• Delays of 24 hours or more see conversion rates plummet to just 2%.

5. Smart Data Usage Improves Efficiency

• Intelligent contact routing ensures the right customers are connected with the right agents, leading to better engagement and resolution rates.

Download the Slides

Webinar Transcript

00:03:43.000 –> 00:04:05.000: So we wanted to really dig into how AI has impacted those conversations what the the uk consumers are feeling around some of the newer technology that’s out there on the market. So we’ve got a bit of a snapshot of some of the key things that have come up from the research, which we’ll share a sneak peek now.

00:04:05.000 –> 00:04:21.000: And then we do have a full report as well that’s coming out shortly. So here are a few things that we thought would be interesting For you guys to know. So the first one was around I suppose understanding the modern communication preferences

00:04:21.000 –> 00:04:28.000: 80% of customers expect clients to know their needs and expectations.

00:04:28.000 –> 00:04:42.000: Which I think is probably something we all feel day in, day out when we’re communicating with businesses But a really interesting one was around the AI acceptance gap.

00:04:42.000 –> 00:05:02.000: So I don’t know if this would be common knowledge, but maybe a bit of a presumption that The younger cohort of the UK market are the people that we researched with have a higher acceptance of AI in general and are more comfortable with interacting with AI.

00:05:02.000 –> 00:05:16.000: And that’s compared to, it was 65% of 25 to 33 year olds are more comfortable with AI interactions compared to 27% of over 55s.

00:05:16.000 –> 00:05:29.000: Which was interesting. But with 52% of over 55 year olds actually being actively uncomfortable with AI interactions.

00:05:29.000 –> 00:05:51.000: Moving on to the human element. So I suppose this goes hand in hand with ai So despite technology advances and AI being the buzzword and the buzz piece of technology over the last 18 months human the human element is really critical so semi

00:05:51.000 –> 00:05:58.000: 60% of customers do prefer human agents when explaining specific situations.

00:05:58.000 –> 00:06:07.000: Or they have complex queries. And when there’s an emergency there is a real preference to that human contact as well.

00:06:07.000 –> 00:06:26.000: And it’s the same when anything involving finance or I suppose really sensitive subjects, 47% of people do prefer that human agent contact rather than self-serving through digital channels.

00:06:26.000 –> 00:06:44.000: The next slide is around proactive outbound communication. When does it makes sense from a UK consumer’s perspective that you might reach out to me as a business around the different types of things that you might want to.

00:06:44.000 –> 00:07:10.000: When are they more accepting of that? So people are more accepting of outbound communication when it’s in relation to payment and billing matters, account updates And email is a strong strongly preferred channel as well as the initial contact method and then follow-ups via direct phone calls, SMS, WhatsApp.

00:07:10.000 –> 00:07:24.000: We have taught at great length on other webinars around the impact that Omnichannel has on Whether that’s success rates for sales and debt collection.

00:07:24.000 –> 00:07:39.000: Or the actual customer service experience as well. So I think for us, the key things here were really that actually a one size all approach doesn’t work. It does need to be personalised.

00:07:39.000 –> 00:07:51.000: And it is crucial to ensure that you’re matching your your contact strategy with the consumer’s preferences and knowing your customers is really the start of that.

00:07:51.000 –> 00:08:01.000: 76% of customers expect personalisation and brands to really excel at personalisation.

00:08:01.000 –> 00:08:16.000: I think that’s all well and good saying that but actually as organisations and people in charge of contact strategies, how do you make that happen? And that’s something that we’re going to talk about now with Ben.

00:08:16.000 –> 00:08:29.000: It is much harder to execute and scale across hundreds of thousands of clients and make that personal But we can show you some ways that other organisations are doing that.

00:08:29.000 –> 00:08:47.000: We’re going to have… then show us around some of the key features in the Max Contact platform that will help you do that and also share some of the customer stories as well and the use cases for these specific features as well.

00:08:47.000 –> 00:09:06.000: So we’re going to start, Benny’s going to share his screen. Thanks, Ben. So we’ll start by talking about something that we call in our platform outbound skills-based routing and this really is ensuring that the right person for the job is reaching out to the right client.

00:09:06.000 –> 00:09:10.000: So we’ve got a client and a customer story around this.

00:09:10.000 –> 00:09:22.000: Around how someone really made their Outbound campaigns much easier to manage Before they moved to Max Contact, they were using click to dial in Salesforce.

00:09:22.000 –> 00:09:28.000: They were averaging around four hours of talk time per day.

00:09:28.000 –> 00:09:41.000: They didn’t um by talk time in this context That included all answer machines, all no answers So it wasn’t a reflection on true talk time.

00:09:41.000 –> 00:09:45.000: So they struggled with reporting as an element of that as well.

00:09:45.000 –> 00:10:06.000: Now, after the move to Max Contact, they’re averaging four hours of actual talk time active conversations with their prospects each day. So that is excluding the answer machines and no answers So some really great results from moving from a manual dialing

00:10:06.000 –> 00:10:24.000: Approach to more automated and removing some of the ineffective work where answer machine detection is coming in And maybe predictive diving But they’re also being much more effective with how they’re using their data internally.

00:10:24.000 –> 00:10:31.000: Ben, are you all right to give us a little bit more insight as to how they’re approaching the leads and that data.

00:10:31.000 –> 00:10:37.000: Yeah, absolutely. So yeah, hopefully you can see my screen and I’m assuming you can hear me as well. Kaylee will tell me if you can.

00:10:37.000 –> 00:10:38.000: We can, yes.

00:10:38.000 –> 00:10:47.000: So yeah, so after they moved over to Max, they were using individual lists and campaigns per users to begin with.

00:10:47.000 –> 00:10:55.000: So if you can imagine, you know, each one of the campaigns on screen here was for an individual agent and within that there was an individual list, an individual pot of data.

00:10:55.000 –> 00:11:05.000: Problems with that come when people are off sick you now have to start moving around your lists, moving around your campaign. So it can be quite a manual processes.

00:11:05.000 –> 00:11:18.000: Which can take a lot more time. They also have an internal process of prioritising leads based off three kind of categories. So they have hot leads, high priority and normal leads.

00:11:18.000 –> 00:11:29.000: So what they now do with Macs is they apply skills via skill-based routing so as they import their data in.

00:11:29.000 –> 00:11:40.000: What you can do as part of that import is map your data and when you have a category of skill groups or skills on your CSV file, you can map that into our lead table.

00:11:40.000 –> 00:11:57.000: On the system and the system will obviously pick up those skill groups now they link into the skills that you can set up on the system. So you can create skill groups And you can create skills within those skill groups. So what they now do is they apply their skills to their data.

00:11:57.000 –> 00:12:16.000: Upload that data map it all in And then that allows the data to be controlled as to who it’s going to go to so their process only specific agents deal with hot leads. They don’t want some of their agents dealing with those hot leads. They want the best agents effectively, the best performing agents.

00:12:16.000 –> 00:12:22.000: Another thing they do as well is they utilise API imports as well.

00:12:22.000 –> 00:12:33.000: Again, same process as that manual one where it maps the data across and puts the relevant information in there when it comes to the skills.

00:12:33.000 –> 00:12:58.000: What you can also do on the system with your users, and obviously you may have the best users and some that are not quite as good at other things is you can also allocate specific skills and allocate a specific skill proficiency. So you can see here as a quick example, this particular user has got a proficiency of 10 out of 10 for customer service, 7 for dispute management and five for debt collection. So you can also control it at that level as well.

00:12:58.000 –> 00:13:07.000: This user can handle all those types of lead But they’re more likely to get more of the customer service ones because they’re more proficient with them.

00:13:07.000 –> 00:13:18.000: What they also do as well is they use fetch weights on their lists so within this campaign here that you can see up at the top I’ve got two lists in there.

00:13:18.000 –> 00:13:33.000: And on the right hand side, we can control the fetch weight. So how much data we’re dialing from each one of those lists. So the higher the the number effectively, the more data that you’re going to dial. It’s also worth pointing out as well that within a script.

00:13:33.000 –> 00:13:44.000: Sorry, within a list, you can also apply individual scripts. So those two lists within that campaign could have different scripts around different products or services as well.

00:13:44.000 –> 00:13:50.000: Great. What was the impact of that approach then, Ben, for the client in question?

00:13:50.000 –> 00:14:06.000: Yeah, so now now, as I said before, they were separate campaigns, separate lists for separate users. Now they all log into the same campaign and agents are matched to specific leads based on their skills And again, matching with their categories of hot leads, high priority and normal

00:14:06.000 –> 00:14:17.000: And the best agents are always matched to those hot leads. But they can still, if they choose to, on occasion they do, they can still deal with other calls as well, obviously.

00:14:17.000 –> 00:14:24.000: Before they did this, they’d run out of data quite quickly and now it’s spread out a bit more over the day.

00:14:24.000 –> 00:14:29.000: The campaign’s conversion rate before using skill-based routing on the Max Contact platform was around 4%.

00:14:29.000 –> 00:14:37.000: And afterwards the conversion rate doubled to 8% compared to the previous period So yeah, big, big improvement there.

00:14:37.000 –> 00:14:51.000: Yeah, so I suppose the sales conversion rate before was pretty was good. It was in the good category three to five percent is considered a good conversion rate on a B2C sales call.

00:14:51.000 –> 00:15:07.000: They’ve moved up that category. Into 5% to 8%, which is considered an excellent conversion rate so that’s really good to hear and some great roi off implementing really powerful feature.

00:15:07.000 –> 00:15:17.000: So let’s move on to the next area, Ben. So this is our data prioritisation.

00:15:17.000 –> 00:15:39.000: Tool. It really helps organisation leverage real-time data for effective outreach We’ve got another customer who used this specifically to help with their local market penetration so It was a relatively new brand. They were established in 2021.

00:15:39.000 –> 00:16:03.000: And are in a really, really competitive market. They transitioned from An approach where they were using manually dialing via spreadsheets, picking up the phone And lead volume was a priority for the customer as a challenger brand, you have to make sure that you’re going out there and fighting for every sale and lead.

00:16:03.000 –> 00:16:15.000: That you can possibly get. Leads are generated by the website, third party sites And lead generation campaigns across different social channels as well.

00:16:15.000 –> 00:16:26.000: So Ben, can you tell us how they took that local geographic approach to their campaigns and what impact that had. That’d be really good to see.

00:16:26.000 –> 00:16:47.000: Yeah, so if we look at that they collected all the data, obviously, and they import their data into the system they actually do a lot of api imports so an API mapping screen here just to just to call out there. You can import your data map all your fields. You can also map things like skills

00:16:47.000 –> 00:16:52.000: And the skill groups as well that we’ve just previously spoken about as well.

00:16:52.000 –> 00:17:09.000: And what they use is custom data fetching to look at two things. They looked at postcodes and they looked at the area as a whole. So as we say They were prioritising calling data from Manchester area first because they’re looking to build that presence in that area.

00:17:09.000 –> 00:17:25.000: Before going a bit wider field. So the two ways they’ve done that is they use custom data fetching to build a couple of queries. Now, the first one they actually used was a simple Manchester query. So in here, the rule is effectively the city equals Manchester

00:17:25.000 –> 00:17:39.000: So the system will look through all the data, find all the leads that match that, and then it will pull out those leads and prioritise them. I’ll show you that in a second on another screen. But the other way they did it as well is they went in and they built some

00:17:39.000 –> 00:17:44.000: More specific rules around specific postcode areas as well. So for example.

00:17:44.000 –> 00:18:06.000: Here, you know, I can put in these rules where I’ve got three different postcodes that I can apply it to. So just jumping back real quickly um to what that looks like in terms of the campaign on a campaign we can see this particular list here has eligible leads of 15,000 and then filtered leads of just under

00:18:06.000 –> 00:18:17.000: 7,000. So using that custom data fetching, it allows you to filter out that data based on those rules in there. And that’s what they were doing with the postcodes and the Manchester area.

00:18:17.000 –> 00:18:27.000: Yeah. And what are the other ways that customers are using the data prioritise beyond geography.

00:18:27.000 –> 00:18:35.000: Essentially any data that you map, you can use. So for example, number of attempts when you’re calling someone.

00:18:35.000 –> 00:18:46.000: Read out someone that have had X number of attempts already try retry your old data first debt value fetch the highest value contacts first to get the largest amount of debt in sooner.

00:18:46.000 –> 00:19:01.000: Car insurance, so competitive displacement campaigns target contracts who are with certain insurances, if they’ve had bad press, things like that, dates, customer signs up on a certain date and you want to schedule a check-in call after X amount of days

00:19:01.000 –> 00:19:10.000: Contract expiry dates And date of births as well, things like that. So yeah, literally any data you want to map in, you can potentially use in those filters.

00:19:10.000 –> 00:19:17.000: Yeah. Amazing. And I think this is the key to the personalisation side of things.

00:19:17.000 –> 00:19:36.000: Isn’t it really i’m sure there’s so much data and insight in businesses understanding what is your process for capturing it, whether it’s in your department or another area of the business if it’s sitting in a CRM or even a spreadsheet

00:19:36.000 –> 00:19:43.000: It really makes sense to then start to use it within your campaigns and just be more intelligent with your targeting.

00:19:43.000 –> 00:19:47.000: Of messaging and the time of your time team as well.

00:19:47.000 –> 00:20:09.000: Good. Thanks, Ben. So let’s move on to the actual getting a view of customer history and understanding Customer intent, past interactions And how you can actually get that data enriched. So when you are speaking to clients, you can start to build that profile as well of

00:20:09.000 –> 00:20:29.000: What does the client um look like from a competitor perspective are they using a certain utility provider or I’ve got a certain contract date seeing how a customer understanding a customer is really important and it’s the crucial part of the campaigns

00:20:29.000 –> 00:20:41.000: And makes great great campaign success so How can clients stay on top of this in the moment with their teams?

00:20:41.000 –> 00:20:46.000: Yeah, so obviously customer by customer, you’re learning about them, adding details to the right lists.

00:20:46.000 –> 00:21:07.000: Within the system you know you may you may deal with customers who you’ve got campaigns for multiple products services so you know dealing with them and making sure the data and information is up to date on those lists. You can keep up to date in a few ways. So on screen now, I’ve just placed a call to myself. Apologies for the ringing in the background while Kaylee was still speaking there.

00:21:07.000 –> 00:21:36.000: But Simon, I apologise. But yeah, what we can see on here is I’m on a call with a contact and um First thing you can do within Contact Hub is you can update the preferences communication information on the right hand side over here. So I can go in and I can add a new phone number, a new email address. I can copy those and take those out and use them elsewhere and I can update their address detail. And that’s regardless of whether you’re using a script or not and whether you’ve got that information within the script.

00:21:36.000 –> 00:21:44.000: You’ve also got the ability to update that same information if you’ve got it in your script. So for example, we’ve got address detail and information in there as well.

00:21:44.000 –> 00:21:55.000: And a little bit further down here. Again, going back to what we talked about before with filtering data based on essentially any data you map into the system, you can also bring that through into your scripts.

00:21:55.000 –> 00:22:15.000: And then you can update that information on each call, your agents can go in and can make changes to that data and update you know current supplier, who’s your supplier at the minute, for example, with this one. But again, it can literally be any data on their contract expiry dates, debt amounts, so on and so forth, dates of birth and what have you.

00:22:15.000 –> 00:22:27.000: The other area that you can do within here is keeping notes so getting your agents to add notes to the calls about the customer, what’s gone on previously, what’s happened on this particular call.

00:22:27.000 –> 00:22:40.000: Adding those notes to the active call so that they are recorded for future And then finally, agents have access to a history tab which has the entire customer journey on there.

00:22:40.000 –> 00:22:52.000: So I can go through and I can see a call that happened today where the agents left a note, say the customer informed of was a change of address. And as I go through, I can see notes around callbacks, transfers.

00:22:52.000 –> 00:23:09.000: Notes on the call if there are multiple. You can also click on these and you can see more detail if there are that more than viewable. And there’s also some other stuff around Spokane AI, which is a product we have in terms of things like transcripts and speech analytics, which can be pulled through into this page as well.

00:23:09.000 –> 00:23:20.000: But as you can see, I can scroll through this customer’s entire history to see everything that’s gone on with them on the system.

00:23:20.000 –> 00:23:27.000: Cool. Thanks, Ben. Next, we’re going to talk about the need for speed.

00:23:27.000 –> 00:23:47.000: Let’s get that one in there. So all about how reaching out to your leads and contacting people, what is the impact of speed essentially So we’re going to talk through how you can do that. But first, there’s a couple of

00:23:47.000 –> 00:23:53.000: Research pieces really that help us really show how important speed is.

00:23:53.000 –> 00:24:05.000: So there’s some research from mit over They analysed over 15,000 leads and over 100,000 call attempts over three years.

00:24:05.000 –> 00:24:12.000: This study revealed that the odds of contacting a lead decreased by 10 times in the first hour.

00:24:12.000 –> 00:24:17.000: So if you are not moving quickly with anything that is coming inbound.

00:24:17.000 –> 00:24:29.000: Then you are really damaging your conversion rates of campaigns So the odds of qualifying a lead are 21 times higher when contacted within five minutes.

00:24:29.000 –> 00:24:54.000: Compared to 30 minutes as well. There’s more support for the need for speed. So there’s another study from Convertica Who revealed that a significant decrease in lead conversion rates with increasing response times So specifically, within five minutes, the conversion rate is around 70%.

00:24:54.000 –> 00:25:08.000: People are in the moment, they’re ready to have a conversation if they’ve filled in a form on your website or perhaps on a comparison site, they’re in that frame of mind, they’re ready to talk about it.

00:25:08.000 –> 00:25:15.000: The conversion rate drops to 50% within 30 minutes and 20% within an hour.

00:25:15.000 –> 00:25:21.000: And it drastically falls when it’s over 24 hours to around 5%.

00:25:21.000 –> 00:25:31.000: So customers… And not just you, we all spend a lot of money and time on generating high value leads.

00:25:31.000 –> 00:25:43.000: For our businesses. How do you make sure that you are outside of that 2% conversion rate stat how do you make sure that you are performing as best you can.

00:25:43.000 –> 00:25:48.000: Sylvia to you, Ben.

00:25:48.000 –> 00:26:08.000: Sorry, I muted myself there. Apologies. Yeah, I just wanted to talk about HubSpot integration. So one of our customers uses HubSpot integration to create an automated lead management workflow that eliminates the manual processes And speeds up the response times.

00:26:08.000 –> 00:26:27.000: So when prospects submit inquiries through the website integration automatically creates high priority records in Matt’s contact enables agents to contact leads within seconds of the submission The syncing of the data, call activities and outcomes means that they’re instantly added to both systems.

00:26:27.000 –> 00:26:32.000: Also call recordings are automatically stored and linked with HubSpot for quality monitoring as well.

00:26:32.000 –> 00:26:40.000: Agent wise, they can get screen pops with instant access to complete customer records, allowing them to maintain context during conversations.

00:26:40.000 –> 00:26:57.000: Without having to switch between multiple systems, which can obviously sometimes cause a few issues or delay things. The integration also enables automated workflow triggers based off HubSpot lifecycle stages So it ensures leads are followed up and processed according to their status.

00:26:57.000 –> 00:27:16.000: And this this approach a streamlined approach has really helped the customer to improve the contact rate and conversion metrics by ensuring that leads are contacted during peak interest periods Whilst it also maintains the records of all interactions across both of the platforms as well.

00:27:16.000 –> 00:27:32.000: Yeah, so integration is really key, well, a key driver for that speed here. So whether it’s HubSpot or another it’s ensuring that you have the right connection between where your data is being held, where it’s coming in.

00:27:32.000 –> 00:27:41.000: How you respond to it and then we can obviously have the campaigns and the right responses to that inbound contact.

00:27:41.000 –> 00:27:47.000: Good. And apologies. I was a bit slow to share that slide then, but here it is.

00:27:47.000 –> 00:28:00.000: So I think next we’ll chat about how do you understand whether what you’re doing is working So what works for one client might not work for all of them.

00:28:00.000 –> 00:28:07.000: How do you understand those patterns in behaviour and refine your contact strategy.

00:28:07.000 –> 00:28:14.000: Everyone’s customer base and contact strategy differs. What’s important for you to understand is what works for you.

00:28:14.000 –> 00:28:18.000: What are the best ways people can do that, Ben?

00:28:18.000 –> 00:28:27.000: Yeah, so there’s a couple of ways. Reporting wise first of all, max contacts get over 40 out of the box reports to measure success.

00:28:27.000 –> 00:28:33.000: You can also build your own custom reports within the platform and you can also speak to us about having other reports built in as well.

00:28:33.000 –> 00:28:43.000: And then with the introduction to speech analytics. You’ve got access to more data than you’ve had before for the contact center. So it allows you to see trends, draw comparisons.

00:28:43.000 –> 00:28:48.000: And sort of deep dive into what’s going on behind the numbers that you can see in the reports.

00:28:48.000 –> 00:28:55.000: And it also allows you to anticipate future consumer needs as well. So yeah, that’s our sort of spoken AI platform.

00:28:55.000 –> 00:29:01.000: With speech analytics in there as well.

00:29:01.000 –> 00:29:26.000: Good. And we do have… This is, as a spoken ai is it interesting to you we have got previous webinars that cover exactly what this is and the value that it brings to the contact centre And I believe our next webinar next month is going into a deep dive of some of the newer features and things that we’ve introduced.

00:29:26.000 –> 00:29:39.000: Good. Before we get to our Q&A then, just a quick overview from me on our research piece so This is where we got some of the stats earlier on from.

00:29:39.000 –> 00:29:56.000: So if you do want this research report in your inbox. There’s a QR code there that you can scan with your phones now that will take you to a form which you just need to fill in and we will send it to you. It’s due for release in the next

00:29:56.000 –> 00:30:26.000: Three to four weeks It’s the deep dive on what the 1000 UK consumers believe about their recent call centre So yeah, I think it’s got some really good insights in there as to how things have changed what different demographics of audiences want from a contact centre as well. So it’s a really useful report that I’d encourage you to go and download and help inform your contact strategies.

00:30:30.000 –> 00:30:47.000: And then before we go to our Q&A, just a few key takeaways from me. So thanks, Ben, for the insights and the demos So here are some of the key takeaways. So number one is understanding your consumer preferences is essential.

00:30:47.000 –> 00:31:09.000: So we know different people have different communication preferences They also have different preferences of products as well so there’s no point plugging a certain product to To me, I’ve got a dog at home, I don’t want to hear about cat food or cat insurance.

00:31:09.000 –> 00:31:14.000: I don’t know if they do specific cat insurance, actually. I don’t know if that’s a thing but anyway.

00:31:14.000 –> 00:31:29.000: You get the point. And knowing when to use AI versus human interactions and having people involved in your communication process is crucial for customer satisfaction.

00:31:29.000 –> 00:31:41.000: Second one, speed to lead is critical for conversions Respond within five minutes and you’ll achieve or can achieve up to 70% conversion rate on those conversations.

00:31:41.000 –> 00:31:52.000: After 24 hours, it drops dramatically to around 2%. Thirdly, data prioritisation enhances outreach efficiency.

00:31:52.000 –> 00:31:59.000: So strategic routine of contacts to the right agents significantly improves results.

00:31:59.000 –> 00:32:05.000: And customisng fetch rates based on priority can double conversion rates as well.

00:32:05.000 –> 00:32:27.000: Ai and speech analytics do unlock deeper insights so whether I think reports are great for seeing that day-to-day side of things that I suppose real time update as to what’s happening within a campaign or within a team speech analytics really helps to understand

00:32:27.000 –> 00:32:34.000: The high level trends and gives you more visibility into those customer interactions.

00:32:34.000 –> 00:32:44.000: And really helps spot those trends at a higher level across your entire teams or campaigns and really track that over time as well.

00:32:44.000 –> 00:33:02.000: And then finally, the centralised campaign management really increases efficiency as well so unified campaign management simplifies operations and skills-based routing ensures that the right people are handling the right contacts or leads for your business.

00:33:02.000 –> 00:33:09.000: So that’s the key takeaways. I believe we have got a few.

00:33:09.000 –> 00:33:14.000: Questions, just bear with me. I’ll stop sharing my screen so I can see Ben.

00:33:14.000 –> 00:33:19.000: As well? And we’ll get to these questions now.

00:33:19.000 –> 00:33:25.000: Lost my Zoom panel. Here we are.

00:33:25.000 –> 00:33:34.000: Okay, so… If you have 10 agents on a campaign but only half Five, have a customer service skill.

00:33:34.000 –> 00:33:39.000: But are not available. What?

00:33:39.000 –> 00:33:44.000: I’m not available. Will the call move to the other five that do not have that skill?

00:33:44.000 –> 00:33:48.000: Sorry, fluffed that question up there, Ben.

00:33:48.000 –> 00:33:53.000: Yeah, yeah, 100%. Yeah. So yeah, we don’t want calls not to be made.

00:33:53.000 –> 00:34:12.000: Obviously so we can we can set it up so that, yeah, those calls will still go to other agents who don’t necessarily have that skill. So you can look at the originally assigned agent and you can look at the same skill but different proficiency levels. And then, yeah, any agent available. So yeah, 100% that

00:34:12.000 –> 00:34:15.000: That will do that.

00:34:15.000 –> 00:34:20.000: Okay, good. Thanks, Ben.

00:34:20.000 –> 00:34:35.000: So can SQL queries be used to initiate a WhatsApp interview I think that’s and say our WhatsApp interaction For example, after a certain number of days after signing up with a supplier.

00:34:35.000 –> 00:34:42.000: Can you send a check in? Via WhatsApp, maybe via SMS.

00:34:42.000 –> 00:34:43.000: What are your thoughts on that, Ben?

00:34:43.000 –> 00:34:48.000: Yeah, I was going to say, I know that we’ve done that before with SMS.

00:34:48.000 –> 00:35:00.000: That’s something that we can definitely do. Whatsapp, I’m not 100% sure is my honest answer on whether or not we can do that, but it’s certainly something that we’ve done before, as I say, with SMS.

00:35:00.000 –> 00:35:18.000: I would imagine from the technical side of things, I’m doing a lot of imagining because I’m not as technical as some of the company. That’s something that we could as well but yeah um certainly we’ve done that with SMS before, 100% on that side of it. So yeah, WhatsApp, I would imagine it’s possible.

00:35:18.000 –> 00:35:41.000: Yeah, and I believe WhatsApp has I suppose more that opt in and opt out compliance regulations requirements as well with WhatsApp. So we’ve got more information on WhatsApp and we’ll come back to We’ll perhaps link to that in the follow-up email actually because it was an anonymous

00:35:41.000 –> 00:35:55.000: Person who asked that one. So we’ve got, how do you gather a customer list integration

00:35:55.000 –> 00:35:59.000: So, uh. In what respect so uh

00:35:59.000 –> 00:36:10.000: Yeah. So maybe it’s maybe Yeah, if you could provide a little bit more context for that one, Carl, that would be useful.

00:36:10.000 –> 00:36:11.000: Essentially, around… Well, sorry.

00:36:11.000 –> 00:36:21.000: Maybe it’s, yeah, what are the different what are the different ways we can get data integrated into the platform maybe could be along that line

00:36:21.000 –> 00:36:39.000: Yeah, yeah. Yeah, so you’ve got things like obviously your API import. So you can take data from web leads, for example, someone goes on your website, fills in a web form that then automatically comes through into the system is imported in. You can do sftp uploads as well

00:36:39.000 –> 00:36:51.000: So, you know, there’s a few different ways that you can get that data in, as well as obviously your integration with things like HubSpot and other CRMs and and systems available as well.

00:36:51.000 –> 00:36:52.000: Yep. I think it did, Carl.

00:36:52.000 –> 00:36:57.000: Not if that answered the question 100 but yeah

00:36:57.000 –> 00:37:12.000: Expanded on it. So yeah, I think via we’ve got integrations obviously that you can connect to We’ve also got the integration marketplace as well.

00:37:12.000 –> 00:37:21.000: Which has got really useful. Useful integrations in there. So depends where the data is coming from. It’s probably the answer. But if it’s a web API, then yeah.

00:37:21.000 –> 00:37:33.000: Good. Next question is Can we trigger alternative contact actions based on call outcomes or dispositions?

00:37:33.000 –> 00:37:44.000: I.e. An SMS or a WhatsApp is sent to a customer upon a non-contact via the dialer or an IVM.

00:37:44.000 –> 00:37:58.000: Yes. 100%. Yeah, we do that now for some clients. Depending on the outcomes of calls it automatically triggers those messages to go out to people. So yes, we can do that.

00:37:58.000 –> 00:38:09.000: Yeah, that you can automatically trigger it. And then can you also add the options to initiate it if it someone wants to make that choice or not as well.

00:38:09.000 –> 00:38:11.000: Automated. Yeah.

00:38:11.000 –> 00:38:32.000: Yeah, so in terms of SMS conversation, yeah, we’ve got SMS within the on the channel side of things and whatsapp so you can have those conversations off of the customer coming back to you replying into your SMS or your WhatsApp if you’ve got those channels enabled on there as well, then obviously they can chat to your agents via that method if needs be.

00:38:32.000 –> 00:38:43.000: Good. Thanks, Ben. How does that prioritisation engine work and how customisable is it?

00:38:43.000 –> 00:38:44.000: Is the question.

00:38:44.000 –> 00:39:02.000: Yeah, Barry. Yeah, it allows you to create custom rules for prioritising contacts based on your different data points. So again, going back to what we talked about earlier things like postcodes and what have you. Lead source, engagement history urgency you know any any of those things

00:39:02.000 –> 00:39:11.000: You can assign, as we said earlier you know hot leads to your top performing agents, prioritise high value debts, et cetera, et cetera.

00:39:11.000 –> 00:39:24.000: Yeah, there’s lots of ways and it’s totally bespoke how you want to do it. You know, it’s based on your data, whatever you’re mapping we can use those filters, those options with skill-based routing as well on there also.

00:39:24.000 –> 00:39:47.000: Yeah, I think in a previous life, I worked at a telecoms organisation And we always targeted our audience based on their demographic profile. We’re quite a high end provider and weren’t the cheapest on the market so we wanted to make sure that all our effort from a

00:39:47.000 –> 00:40:05.000: A marketing and sales perspective is put in the right place. So we used to use Mosaic profiles. So if you’ve got things like that that perhaps sit within marketing and sales teams and you know how an organisation is going to market you can really

00:40:05.000 –> 00:40:21.000: Utilise that in the contact center or whether that’s an extension of the sales team It’s really useful ways of using data.

00:40:21.000 –> 00:40:27.000: Good. I think that’s it for our questions now.

00:40:27.000 –> 00:40:38.000: Unless there’s any more, they usually flood in when I say that so Thank you very much everyone for sticking around and for all your questions as well. It was great.

00:40:38.000 –> 00:40:54.000: Hopefully you did find this useful. If you’ve got any feedback, let us know. We’ll link to the couple of things that we mentioned around integrations and WhatsApp as well in the follow-up emails so you can get those answers.

00:40:54.000 –> 00:41:01.000: And that’s it from us. Thank you very much, Ben. And thank you very much for joining us.

Your Questions Answered

During the webinar, we covered some of the most pressing questions around AI, customer interactions, and best practices for contact centres. Here’s a recap of the key discussions:

1. How can businesses access the full research report?

The report is set for release in the next few weeks. You can sign up here for pre-release to get it sent directly to your inbox.

2. What’s the best way to balance AI and human interaction?

AI should enhance efficiency, but human agents remain critical for complex queries, complaints, and emotional interactions. Businesses should use AI for routine tasks while ensuring human support is available when needed.

3. Why does response time impact conversion rates so dramatically?

Customers are most engaged when they first reach out. Our research shows that responding within five minutes can achieve 70% conversion rates, whereas waiting over 24 hours drops it to just 2%.

4. How can businesses personalise customer interactions at scale?

Understanding consumer preferences through data-driven insights allows businesses to tailor interactions. AI-driven speech analytics and intelligent contact routing can improve personalisation without increasing agent workload.

5. What’s the biggest challenge in AI adoption for customer interactions?

The AI acceptance gap—while younger consumers are more open to AI-driven interactions, over half of older customers prefer speaking to a human. Businesses need to balance AI automation with accessible human support.

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