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How to Remain Compliant with AI Speech Analytics
AI-powered speech analytics software helps to drive better performance and outcomes in contact centres. But with regulations tightening, the pressure is on to ensure conversation analytics tools are used compliantly.
The regulatory pressure on contact centres has never been greater. GDPR and the Data Protection Act set the baseline. FCA Consumer Duty is now in active enforcement, requiring businesses to evidence good customer outcomes and not just document processes. PECR reforms under the Data (Use and Access) Act 2025 have raised maximum fines from £500,000 to £17.5 million. And with the EU AI Act and a UK AI Bill both on the horizon, the direction is clear: more accountability, more evidence requirements and higher stakes for getting it wrong.
Used correctly, AI speech analytics addresses most of these challenges directly. But it also needs to be implemented in a way that is itself compliant, with GDPR, with data protection obligations, and with the trust customers place in organisations that record and analyse their conversations.
Why AI Speech Analytics, Not Just Keyword Spotting
Older quality monitoring tools worked on rules. Flag a call if a specific word appeared. Miss it if the agent used different phrasing, spoke too quickly, or the system didn't recognise the accent.
AI conversation analytics works differently. Rather than matching fixed strings of text, it uses natural language processing to understand context, intent and meaning. It recognises that "I can't afford this right now" and "the payments are getting difficult" are both vulnerability signals, even though neither contains a flagged keyword. It picks up on tone, pace, and sentiment as opposed to individual words.
For compliance purposes the distinction between the two matters. A rule-based system tells you whether a phrase was said. AI tells you whether the conversation was compliant and flags the calls where the right words were used in the wrong way, or where the right words were absent entirely.
How AI Speech Analytics Supports Regulatory Compliance
Staying Compliant with GDPR and the Data Protection Act
Under UK GDPR and the Data Protection Act 2018, contact centres must inform customers that calls are being recorded, handle personal data lawfully, respond to Data Subject Access Requests within statutory timeframes, and ensure sensitive information is never captured inappropriately.
| Compliance Challenge | Conversation Analytics Feature | What It Does |
|---|---|---|
| Agents must inform customers calls are being recorded on every interaction. | Keyword and phrase tracking | Automatically scans transcripts for required disclosure language and flags calls where it is absent or delivered incorrectly. |
| Customers can request access to, amendment of, or deletion of their personal data, requiring contact centres to locate relevant interactions quickly. | Transcript search | Every interaction is transcribed and searchable by customer identifier, date range, or keyword, reducing a manual process to minutes. |
| Agents must pause call recordings during card data collection to prevent sensitive information being captured. | Audit trail and compliance logging | Provides an auditable record of whether pause protocols are being followed and surfaces calls where they may not have been. |
| AI-driven call scoring, routing, and analytics must be transparent, challengeable, and subject to human override under the DUAA 2025. | Human-in-the-loop architecture | AI augments agents rather than replacing them, satisfying the DUAA's oversight requirements by design. |
Meeting FCA Consumer Duty Obligations
Consumer Duty has moved from implementation to active enforcement. The FCA is running four cross-cutting supervisory reviews throughout 2026, and the question regulators are asking has shifted: it's no longer "have you implemented Consumer Duty?" It's "can you demonstrate, with evidence, that your business is consistently delivering good outcomes for customers?"
Most contact centres can't provide that evidence at scale. Conversation Analytics is built to change that.
| Compliance Challenge | Conversation Analytics Feature | What It Does |
|---|---|---|
| Agents must tailor interactions to individual customer needs. But assessing this consistently at scale is not possible through manual review. | Sentiment analysis | Identifies moments of customer confusion, frustration, or disengagement, flagging interactions where an agent may not have communicated clearly or adapted their approach. |
| Vulnerability isn't always declared. Signs of financial hardship, emotional distress, health conditions, or communication difficulties can be subtle and easy to miss. | Vulnerability detection | Scans every transcript for language patterns associated with vulnerability and alerts supervisors quickly so agents can adjust, follow support protocols, or escalate. |
| Agents under target pressure can drift toward assertive selling techniques that conflict with Consumer Duty expectations. | Sales conduct monitoring | Analyses keyword usage, pace, and tone across sales interactions to surface calls where the approach may not meet the required standard. |
| The FCA expects documented, data-driven proof of good customer outcomes that go beyond process documentation. | AI call scoring and compliance logging | Every scored call is logged with an auditable record, providing evidence of adherence at scale rather than across a manually reviewed sample. |
For a full breakdown of what Consumer Duty means for your operation, read our guide for contact centre teams in financial services.
Handling Complaints in Line with the Consumer Rights Act
The Consumer Rights Act requires contact centres to handle complaints effectively by addressing root causes, and demonstrating a genuine commitment to consumer satisfaction. The challenge isn't just what happens on individual calls; it's spotting recurring patterns before they become regulatory problems.
| Compliance Challenge | Conversation Analytics Feature | What It Does |
|---|---|---|
| High call volumes make it difficult to identify recurring complaint themes before they become regulatory concerns. | Topic detection | Automatically categorises complaint patterns across the full call volume, surfacing recurring issues before they escalate. |
| Resolving complaints within required timeframes and following appropriate procedures must be demonstrable. | Audit trail and compliance logging | Every interaction is transcribed, searchable, and logged, providing an auditable record of complaint handling that supports verification. |
| Generic training rarely addresses the specific gaps that lead to poor complaint outcomes. | Agent performance analysis | Identifies specific training gaps from real complaint interactions, enabling targeted coaching rather than blanket training. |
How to Monitor and Flag Compliance Issues Automatically
Knowing what compliance requires and having a platform that enforces it consistently are two different things. Here is how compliance monitoring works inside Conversation Analytics day to day.
Keyword and phrase tracking
Configure the platform to track specific language across all transcripts: mandatory disclosure statements, consent language, direct debit scripts, vulnerability indicators. Alerts fire automatically for calls where those phrases are absent, incorrectly used, or appear at the wrong point in the conversation. This runs across 100% of calls and isn’t restricted to a selected sample.
Auto-fail rules
Ensure critical breaches are never obscured by an otherwise acceptable call score. For example, a missed payment recording pause, an absent FCA disclosure or an incomplete ID verification can be configured as automatic failures, meaning every instance is flagged and logged without relying on reviewer judgement.
Real-time alerts
When a vulnerability signal or compliance phrase is detected during a call, supervisors receive an immediate alert. They can join the call, prompt the agent, or prepare for post-call review, allowing them to intervene before the situation escalates rather than discovering it in an audit.
Auditable records
Every flagged call, scored interaction, and compliance alert is logged. When a regulator, internal audit team, or legal function asks for evidence (under Consumer Duty, GDPR, or sector-specific requirements) it exists across every scored call.
Choosing an AI Analytics Platform That Is Compliant by Design
AI speech analytics only supports compliance if the platform handling your data is itself compliant. When evaluating tools, these are the questions to ask and be cautious of providers who cannot answer them clearly.
| What to Look For | Why It Matters | MaxContact's Position |
|---|---|---|
| Data residency | Processing customer call data outside the UK introduces compliance complexity under UK GDPR. | MaxContact's databases are located within the UK, so data remains subject to UK data protection law throughout its lifecycle. |
| Encryption and access controls | Data must be protected against unauthorised access, with role-based permissions limiting who can view recordings and transcripts. | Encryption, access controls, and role-based permissions ensure recordings and transcripts are accessible only to authorised users. |
| Consent and transparency | Customers must be informed their calls will be recorded and analysed. The platform should provide evidence this happened. | Conversation Analytics provides transcript evidence that disclosures were made correctly on every scored call. |
| Human oversight of AI decisions | The DUAA 2025 requires organisations to maintain a human override mechanism for AI-driven processes. | Human-in-the-loop architecture ensures AI augments rather than replaces human judgement across all platform functions. |
For full details on how MaxContact handles data security and compliance, download our security and compliance brochure.
How Honey Group Improved Compliance Coverage with Conversation Analytics
Honey Group, a financial services contact centre, was struggling to review calls for compliance at the volume their operation required. Manual review covered only a fraction of interactions, leaving significant compliance exposure unaddressed.
Working with MaxContact, Honey Group implemented Conversation Analytics to monitor calls across their full interaction volume. Using transcript search and sentiment analysis, their team now identifies inappropriate mentions of sensitive topics, verifies that required disclosures are being made consistently, and flags interactions warranting further review without the resource overhead of manual listening. The result has been a significant improvement in QA coverage and a more systematic approach to both compliance monitoring and agent training.

The Regulatory Changes Contact Centres Need to Prepare for Now
The regulatory environment is changing fast:
- PECR fines have increased 35-fold under the Data (Use and Access) Act 2025, from £500,000 to £17.5 million or 4% of global turnover
- EU AI Act chatbot and AI transparency obligations apply from August 2026, with penalties reaching €35 million or 7% of global turnover for non-compliance
- UK AI Bill is expected, adding a further governance layer to AI deployment in contact centres
The organisations that navigate this well are those treating compliance as a strategic investment rather than something to react to. Conversation Analytics is built to move with that environment by providing the audit trails, evidence of outcomes, and human oversight mechanisms that regulators are increasingly demanding.
If you're assessing how AI speech analytics fits into your compliance strategy, the UK Contact Centre Regulatory Guide covers what's changed, what's coming, and what your operation needs to do about it.
Or, if you want to see how Conversation Analytics works in your environment, book a demo and we'll show you.

The End of Random Sampling: How AI-Powered QA Transforms Contact Centre Performance
What if you could monitor every single customer interaction automatically? What if quality assurance became a real-time, comprehensive process that drives continuous improvement rather than sporadic checking?
Picture this: It's Monday morning, and your quality assurance manager sits down with a stack of randomly selected call recordings from last week. They'll spend hours listening, scoring, and writing feedback notes. By Friday, they might have reviewed 50 calls from the thousands that took place.
Meanwhile, compliance risks hide in unmonitored interactions, top-performing agents go unrecognised, and struggling team members miss opportunities for targeted improvement. The traditional approach to quality assurance isn't just inefficient—it's leaving your contact centre exposed and underperforming.
But what if you could monitor every single customer interaction automatically? What if quality assurance became a real-time, comprehensive process that drives continuous improvement rather than sporadic checking?
This transformation is exactly what AI-powered quality assurance delivers—and it's revolutionising how smart contact centres ensure compliance, develop agents, and deliver exceptional customer experiences.
The Hidden Costs of Traditional QA
Manual quality assurance creates a cascade of problems that impact every aspect of contact centre operations:
Limited Coverage: Reviewing only a tiny percentage of interactions means most quality issues, compliance risks, and coaching opportunities remain invisible.
Subjective Bias: Human reviewers bring their own perspectives and inconsistencies, leading to unfair evaluations and missed insights.
Reactive Response: By the time manual reviews identify problems, customers have already experienced poor service, and compliance breaches may have occurred.
Resource Drain: QA managers spend countless hours listening to recordings instead of developing strategies and coaching agents.
Missed Opportunities: Without comprehensive analysis, contact centres can't identify what makes their best agents successful or replicate those behaviours across teams.
The result? Compliance risks, disengaged agents, and missed opportunities to transform performance.
How AI-Powered QA Changes Everything
Modern AI-driven quality assurance systems flip this model entirely. Instead of sampling a fraction of interactions, they analyse every single customer conversation across all channels—calls, emails, web chat, and SMS.
Here's how the technology transforms QA processes:
100% Coverage: Every interaction receives quality analysis, eliminating blind spots and ensuring comprehensive oversight.
Real-Time Insights: Issues are identified immediately, enabling proactive intervention rather than reactive damage control.
Objective Analysis: AI removes human bias, providing consistent, data-driven evaluations based on defined criteria.
Multi-Channel Monitoring: Quality assurance extends beyond phone calls to encompass your entire customer engagement ecosystem.
Four Pillars of Intelligent Quality Assurance
1. Comprehensive Monitoring That Misses Nothing
AI-powered QA software monitors conversations across every channel where customers interact with your business. Whether it's a phone call about a billing query, an email complaint, or a web chat support request, every interaction receives the same thorough quality analysis.
This comprehensive approach reveals patterns and insights that single-channel monitoring misses, providing a complete picture of customer experience quality.
2. Compliance Made Simple and Bulletproof
Compliance isn't optional, and random sampling isn't sufficient. AI QA tools track, review, and evidence compliance across 100% of interactions, helping contact centres meet industry regulations consistently.
Instead of hoping your sample catches compliance issues, you gain confidence that every interaction adheres to required standards. This proactive approach protects your reputation, avoids costly fines, and gives your team the confidence to operate compliantly.
3. Insightful Coaching That Drives Real Improvement
AI-powered analysis reveals the 'why' behind customer objections, agent performance, and interaction outcomes. Instead of generic feedback, managers can provide specific, evidence-based coaching that addresses real performance gaps.
Identify what techniques your top performers use, understand common objection patterns, and create tailored training programmes that drive measurable improvement across your team.
4. Real-Time Performance Intelligence
Advanced QA systems provide instant insights into key performance metrics, balancing customer satisfaction with operational efficiency. Managers can spot trends as they develop and adjust strategies before small issues become major problems.
The Technology That Powers Transformation
Modern QA systems integrate multiple AI technologies to deliver comprehensive insights:
Speech-to-Text Analytics: Convert every conversation into searchable transcripts, enabling keyword searches for compliance terms, quality indicators, and trending topics.
Sentiment Analysis: Understand customer emotions throughout interactions, identifying positive experiences worth replicating and negative patterns that need addressing.
Success Intelligence: Analyse what makes top-performing agents successful and provide actionable recommendations for improving overall team performance.
Advanced Reporting: Real-time dashboards and analytics provide the data needed to make informed decisions about training, processes, and resource allocation.
Real-World Results: The HoneyLegal Success Story
The transformation potential is clear in real customer results. Karl from HoneyLegal explains: "AI will absolutely revolutionise the way we approach sales training and people's individual performance."
HoneyLegal transformed their QA process by gaining deep insights into call performance, compliance, and agent success. This helped them streamline quality control, enhance coaching, and scale performance improvements across their team—moving from reactive management to proactive optimisation.
The Business Case for AI-Powered QA
The benefits of implementing intelligent quality assurance extend throughout contact centre operations:
Risk Reduction: Comprehensive compliance monitoring protects against regulatory penalties and reputational damage.
Cost Efficiency: Automated analysis eliminates manual review time, freeing QA managers to focus on strategic improvement initiatives.
Performance Enhancement: Data-driven coaching delivers measurable improvements in agent effectiveness and customer satisfaction.
Scalable Operations: AI-powered systems grow with your business without proportional increases in QA resources.
Competitive Advantage: Understanding exactly what creates exceptional customer experiences enables you to consistently deliver superior service.
Moving Beyond Tick-Box QA
Traditional quality assurance often becomes a compliance exercise that provides limited value to agents or operations. AI-powered QA transforms this dynamic entirely.
Instead of random checks that may miss critical issues, you gain comprehensive insight into every customer interaction. Instead of subjective evaluations, you receive objective, data-driven analysis. Instead of reactive problem-solving, you enable proactive performance improvement.
Most importantly, QA becomes a strategic tool for business growth rather than a necessary cost centre. When you can identify exactly what creates successful customer interactions and replicate those behaviours across your team, quality assurance becomes a competitive advantage.
The Future of Contact Centre Excellence
The contact centres that succeed in today's competitive environment are those that learn from every customer interaction. They don't just handle calls—they extract intelligence that drives continuous improvement.
AI-powered quality assurance makes this comprehensive learning possible. By analysing every conversation, it reveals patterns, trends, and opportunities that traditional sampling methods miss entirely.
When you can see what works, understand what doesn't, and provide targeted coaching based on real performance data, your contact centre transforms from reactive operations to proactive excellence.
The conversations are happening. The data is there. The question is: are you using it to drive the performance and compliance your business needs?
Ready to transform your quality assurance from random sampling to comprehensive intelligence? Discover how AI-powered QA software can improve compliance, enhance agent performance, and drive better customer outcomes across every interaction.

Call Centre Outsourcing: How Can BPOs Meet Their KPIs?
Is your outsourced contact centre finding it harder to meet KPIs as customer expectations rise and margins tighten? You’re not imagining it.
Many BPO leaders are under growing pressure to deliver consistent performance, all whilst operating in an environment that’s increasingly competitive and cost-sensitive.
One of the biggest challenges is not the lack of data, but knowing how to interpret it. BPOs often track dozens of metrics, yet they still struggle to understand whether performance is strong, weak, or simply average for the market. Without a clear point of comparison, it’s impossible to know where to focus improvement efforts, or how to demonstrate value to clients.
In this article, we explore how accurate benchmarking helps outsourced contact centres to:
- Assess performance more accurately.
- Identify meaningful improvement opportunities.
- Use data to drive better outcomes across sales, service and debt collection operations.
What is Benchmarking?
Benchmarking is the process of comparing your contact centre’s performance against industry standards or peer groups to understand how well you’re really performing.
Rather than viewing KPIs in isolation, benchmarking provides context. It shows where performance is competitive, where gaps exist, and which metrics matter most for your operating model.
There are two primary approaches:
- Competitive benchmarking: Comparing performance against similar BPOs or outsourced contact centres
- Process benchmarking: Comparing workflows against recognised best practice, sometimes drawn from other industries (used less frequently in contact centres)
The Benchmarking Challenge for BPOs
In practice, benchmarking is not always straightforward. BPOs often face inconsistent data, varying KPI definitions between clients, and limited visibility of reliable industry standards. Combined with the pace and pressure of contact centre operations, this makes it difficult to establish benchmarks that are both accurate and actionable.
Despite this, benchmarking remains essential for BPO performance and long-term competitiveness.
Done well, benchmarking allows BPOs to:
- Understand whether KPIs reflect strength or emerging risk
- Use objective data to support operational and commercial decisions
- Identify best practices and apply them consistently across teams
- Spot early warning signs, such as rising agent workload or churn, before they impact service delivery
Overcoming benchmarking challenges starts with a clear strategy: defining objectives, selecting relevant KPIs and measuring performance consistently over time. Our complete guide to call centre reporting metrics explains which KPIs matter most and how they should be read together, rather than in isolation.
What are the Top KPIs Contact Centres Prioritise in 2026?
MaxContact’s 2025/26 UK Contact Centre KPI Benchmarking Insights Report reveals a shift in how contact centres prioritise performance metrics. Rather than focusing on a single efficiency measure, decision makers are increasingly balancing customer experience, responsiveness and commercial outcomes.
Based on responses from 300 UK contact centre leaders, the three most focused on KPIs are:
- Customer Satisfaction (CSAT) – prioritised by 48% of respondents
- Speed of Answer – cited by 35% as a critical performance metric
- Service Level Achievement – selected by 34% of contact centres

Close behind these sit commercially focused metrics such as conversion rate (33%), first call resolution (33%), and revenue per contact (32%), reflecting the ongoing pressure to balance service quality with financial performance.
We explore why a blended approach to call centre metrics is the best way to measure call centre efficiency.
Of course, the metrics that contact centres report on, is also dependent on the industry they operate in.
Key KPIs for Sales and Debt Resolution BPOs
Understanding which KPIs matter most is critical for BPOs operating in sales and debt resolution. While both rely on outbound performance, the metrics that drive success (and the way they should be interpreted) differ significantly between the two.
The latest benchmark data shows that high-performing BPOs don’t track more metrics than their peers. They focus on the right ones and use them together to guide decisions, not just report outcomes.
Sales-focused BPOs
For sales-driven BPOs, performance is ultimately measured by revenue. But revenue outcomes are shaped by a combination of efficiency, lead quality and agent effectiveness.
The 2025/26 Benchmark Report shows that while sales volumes have softened slightly year-on-year, revenue performance is holding up, suggesting agents are working harder and conversations are becoming more complex.
Key KPIs for sales BPOs include:
- Conversion rate: Measures the percentage of contacts that result in a sale. Benchmark data shows a mean conversion rate of 16%, with nearly 30% of teams achieving rates between 20-29%. Improving conversion is less about increasing call volume and more about better lead prioritisation, agent coaching and script effectiveness.
- First-call close rate: Indicates how often a sale is achieved on the first interaction. The benchmark mean sits at 25%, down slightly year-on-year, reflecting a tougher sales environment. Falling first-call close rates can point to lead-quality issues or gaps in agent confidence and product knowledge.
- Average revenue per call: The mean revenue per call now sits at just under £230, although this figure is heavily skewed by top performers. Over 45% of sales teams generate less than £59 per call, highlighting a significant performance gap between average and high-performing BPOs.
- Calls to success ratio: Tracks how many calls are needed to secure a sale. A rising ratio often signals inefficiencies in targeting, messaging or dialling strategy, issues that cannot be solved by increasing activity alone.
High-performing sales teams use these metrics together to understand why performance varies between campaigns, agents or lead sources, not simply whether targets were met. We explore how sales teams follow data effectively in our article Is your outbound sales team truly data-driven?
Debt Resolution BPOs
Debt resolution BPOs face a different challenge: recovering outstanding balances while navigating increasingly complex and sensitive customer conversations.
Benchmark data suggests debt collection teams are operating in a more difficult economic environment, with performance under pressure despite consistent effort.
Key KPIs for debt resolution BPOs include:
- Right Party Contact (RPC): Measures how effectively agents are reaching the correct individual. The current benchmark mean is 27%, making RPC one of the most important early indicators of list quality and call timing effectiveness.
- Promise to Pay (PTP) rate: Indicates the percentage of contacts that result in a commitment to pay. The benchmark mean sits at 28%, broadly in line with last year, suggesting agents are maintaining performance despite tougher circumstances.
- First Call Resolution (FCR): Measures whether a payment or promise to pay is achieved on the first interaction. The benchmark mean has fallen to 37%, down five percentage points year-on-year. A meaningful decline that reflects more complex debtor situations rather than declining agent capability.
- Percentage of debt collected: A high-level indicator of overall effectiveness. The benchmark mean has dropped to 28%, down from 32% last year, reinforcing the need for smarter call strategies, better timing and more personalised conversations.
For debt resolution BPOs, these KPIs must be interpreted in context. Falling FCR or recovery rates may signal broader economic pressure rather than operational failure. But without benchmarking, that distinction is impossible to make.
The Role of Technology for Benchmarking Success
Benchmarking only becomes valuable when insight leads to action. This is where technology plays a critical role.
The 2025/26 Benchmark Report shows that 66% of contact centres are already using or piloting AI, with 60% planning further investment in AI and automation in 2026. This reflects a clear shift away from retrospective reporting and towards real-time performance control.
Modern contact centre platforms enable BPOs to:
- Optimise agent performance: Use real-time dashboards, coaching tools and conversation analytics to identify what high performers do differently and replicate it at scale.
- Improve customer outcomes: Balance efficiency with experience by monitoring metrics such as conversion, FCR and CSAT together rather than in isolation.
- Drive operational efficiency: Adjust dialling strategies, lead prioritisation and resource allocation based on live performance data, not end-of-day reports.
In a highly competitive outsourcing market, technology is no longer a differentiator on its own. The advantage lies in how effectively BPOs use data to benchmark performance, guide decisions and demonstrate value to clients.
Not Sure How You Measure Up?
The 2025/26 UK Contact Centre KPI Benchmarking Insights Report provides in-depth analysis of industry performance, with actionable insight for sales and debt resolution BPOs.
Download the report to compare your KPIs against UK benchmarks, identify performance gaps and understand what high-performing outsourced contact centres do differently.

How To Improve Right-Party Contact Rates In Debt Resolution
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?
StrategyOverview
Strategy 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.
StrategyOverview
Strategy 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:
StrategyOverview
Strategy 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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The Future of Digital Customer Engagement: MaxContact's Contact Hub Boosts Agent Productivity Using Digital Channels
To keep pace with evolving customer expectations, businesses are constantly seeking ways to enhance their customer experience whilst improving operational efficiency. At MaxContact, we’re proud to introduce Contact Hub Connect, our next generation agent interface that not only meets your customers where they are but also significantly boosts agent productivity.
The Shifting Landscape of Customer Engagement
The way customers interact with businesses has undergone a dramatic transformation in recent years. As Kayleigh Tait, Head of Marketing at MaxContact, points out, “We’re looking at research around usage of digital channels. The average consumer uses 6 touchpoints across various different channels when making a purchase, and that’s in comparison to 2 touchpoints from 15 years ago.”
This shift underlines the increasing importance of digital channels in customer interactions. Customers now expect seamless communication across multiple platforms, including email, web chat, SMS, and voice. Contact Hub Connect has been designed with this multi-channel reality in mind, providing a unified interface that allows agents to effortlessly navigate between different communication channels.
MaxContact’s Commitment to User-Driven Development
At the heart of Contact Hub Connect is our commitment to user-driven development. Elin Simmonds, our UX lead, emphasises the importance of involving users throughout the design journey: “It’s very important that the people are actually building the product understand how the end users use it.”
This user-centric approach involved extensive research, including interviews and site visits with both agents and managers. By observing how agents interact with existing systems and identifying pain points, we’ve created a solution that addresses the needs of those on the front lines of sales, collections and customer service.
5 Ways Contact Hub Connect Boosts Agent Productivity
Let’s dive into the specific features that make Contact Hub Connect a game-changer for agent productivity:
1. Unified Inbox for All Digital Channels:
Contact Hub Connect introduces a streamlined inbox that consolidates all digital interactions – email, web chat, and SMS – into a single, easy-to-navigate interface. This unified approach allows agents to seamlessly switch between different channels without the need to toggle between multiple systems or windows.

2. Improved Customer History and Context:
With Contact Hub Connect, agents have instant access to comprehensive customer information and interaction history. As Elin explains, “We can see what the digital history of a customer looks like, as well as voice history.” This feature provides agents with valuable context, enabling them to provide more personalised and informed service.
3. Enhanced Canned Responses and Shortcuts
We’ve reimagined how agents can use pre-written responses and shortcuts. The new system allows for quick insertion of canned responses using keyboard shortcuts, with a preview feature that lets agents see and edit the full response before sending.

4. Integration with Spokn AI for Voice Transcripts and Insights
For users with Spokn AI enabled, Contact Hub Connect provides powerful insights derived from voice interactions. Agents can access call summaries, sentiment analysis, and key topics discussed, all within the same interface. This integration helps bridge the gap between digital and voice interactions, providing an omnichannel view of customer communications.
5. Seamless Switching Between Digital and Voice Interactions
Contact Hub Connect isn’t just about digital channels – it’s designed to work seamlessly with voice interactions as well. Agents can easily initiate a voice call from within a digital interaction, with all the familiar call controls and scripting tools available at their fingertips. This integration ensures that agents can provide consistent service regardless of the channel.

Looking to the Future
Contact Hub Connect represents a significant step forward in our vision for the future of sales, collections and customer service. By providing agents with the tools they need to work efficiently across all channels, we’re enabling businesses to meet the evolving expectations of their customers and their growth targets.
As we continue to refine and expand Contact Hub Connect, we’re excited about the possibilities for future enhancements. We’re exploring ways to further leverage AI and automation to support agents, as well as looking at additional integrations that will make the platform even more powerful and versatile.
Are you ready to upgrade your customer interactions and boost your agent productivity? Contact us today to learn more about Contact Hub.
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Unlocking the DNA of Sales Success: How AI Identifies and Analyses Sales Objections to Drive Successful Outcomes
The challenge: What makes a sales call successful?
B2C phone sales demands quick thinking, emotional intelligence, and deep product knowledge. The best salespeople can navigate objections, build rapport, and close deals – but top performers are rare, hard to find, and even harder to retain.
But what if AI could change that?
Imagine transforming any motivated individual into a sales powerhouse, regardless of their initial abilities. Instead of searching for the perfect sales candidate, AI-powered speech analytics can help any motivated individual develop their skills and become a high-performing sales agent.
Our latest speech analytics feature identifies the key behaviours, patterns and techniques that drive success, helping teams replicate what works at scale. For Contact Centre Leaders and Sales Team Managers, it changes the game. It’s about building excellence from within, turning potential into performance, and reshaping how we approach talent development in sales.
The evolution of Spokn AI: From transcription to AI-driven sales coaching.
Our speech analytics platform, Spokn AI, all started with a simple yet powerful mission: to provide businesses with deeper, actionable insights into their customer conversations.
2023: Launched as an advanced speech transcription tool.
April 2024: Expanded into a full speech analytics platform.
2025: With Success Intelligence, Spokn AI is revolutionising AI-driven sales coaching.

Introducing Success Intelligence: AI-powered sales performance analytics
Our Success Intelligence tool refines automated quality assurance processes that rely on traditional speech analytics. It moves QA beyond simple pass/fail metrics because it doesn’t just transcribe conversations – it understands them.
By identifying key success drivers, categorising objections, and analysing top-performing behaviours, Success Intelligence provides actionable insights that help teams close more deals, improve agent training and optimise call centre performance.
Why it matters for sales & contact centre leaders
- Replicate top-performing sales behaviours across teams.
- Improve objection handling to boost conversion rates.
- Align AI-driven insights with sales KPIs (e.g. meetings booked, deals closed, payments secured).
- Reduce training time and accelerate agent development.
Success Intelligence isn’t just about evaluating sales performance – it’s about unlocking potential and driving meaningful results.
Key features of Spokn AI Success Intelligence
1. AI-powered objection detection & analysis
Success Intelligence goes a step further than Spokn AI. The feature identifies common objections and how top performers overcome them. This allows sales teams to:
✔ Understand which type of objections are preventing conversions.
✔ Develop data-driven scripts to overcome those challenges and objections.
✔ Train agents based on real sales conversations, not just guesswork.

2. Performance benchmarking & AI coaching insights
Success Intelligence empowers you to uncover the ‘why’. AI analyses what top-performing agents do differently. Managers can:
✔ Identify behavioural trends that lead to success.
✔ Pinpoint specific skill gaps and provide targeted coaching.
✔ Optimise call strategies based on real performance data.
With Spokn AI and Success Intelligence, optimising your team for success has never been easier.

3. Conversation flow & engagement insights
Make sure agents are having real conversations rather than delivering robotic sales pitches. Success Intelligence evaluates:
✔ Silent time – When does a call go cold?
✔ Talk ratios – Who dominates the conversation?
✔ Monologues – Are agents talking too much or too little?
✔ Engagement patterns – What keeps a prospect listening?
Get insight into conversation quality and engagement levels, showing what works best for successful call outcomes.

The power of AI in sales coaching
AI won’t replace human-led sales coaching – but it will enhance it. With AI-powered insights, sales managers and call centre leaders can spend less time reviewing calls manually and more time developing their teams into high-performing sales agents. Here’s how Spokn AI and Success Intelligence is used to enhance the process.
What’s next? AI-generated coaching recommendations.
We’re working on delivering AI-generated coaching recommendations, helping managers provide instant, data-driven feedback to their teams.
The future of AI-driven sales success: What’s next for Spokn AI?
MaxContact is committed to continuous AI innovation. What sets Spokn AI apart is its commitment to customer-driven development. By actively seeking and incorporating feedback from users, the platform has rapidly transformed to meet the real-world needs of sales and collections teams. Unlike generic speech analytics tools, Success Intelligence is built for sales teams and shaped by real-world call centre needs.
What we’re working towards:
Advanced speaker separation: More precise agent-customer distinction.
Real-time AI alerts: Flag key sales phrases & compliance risks instantly.
Automated Quality Assurance checks: Reduce manual call reviews.
The human-centric approach: AI that enhances, not replaces.
AI should empower people, not replace them. And that’s exactly what Spokn AI does. It automates time-consuming data analysis, so managers and team leaders can focus on what matters: developing their teams, refining sales strategies, and driving business growth.
By delivering real-time, actionable insights, Spokn AI ensures that agents receive timely, personalised coaching, helping them develop faster and perform at their best. This data-driven approach not only enhances individual performance but also boosts engagement and retention by providing a clear path for career progression.
Why do call centres need AI for sales in 2025?
With increasing pressure to hit targets, contact centre leaders can’t afford to rely on guesswork. AI-driven sales analytics are the future of high-performance call centres.
Why MaxContact?
✔ 100% AI-powered call transcription & analysis.
✔ Designed for UK call centres – Built with UK speech patterns in mind.
✔ Integrates seamlessly with existing sales workflows.
Unlock sales success with AI today
- Want to see Success Intelligence in action?
- Looking to optimise your outbound sales performance?
Get in touch with our team today and see how AI-powered insights from Spokn AI and Success Intelligence can transform your sales strategy.