How AI Speech-to-Text Analytics Revolutionises Contact Centre Intelligence

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.

‍

Contact centres are always under pressure to remain compliant with complex laws and industry standards that frequently change. From data privacy regulations like GDPR to sector-specific rules such as those enforced by Ofcom, FCA, and Ofgem, contact centres must navigate a minefield of compliance requirements.

The increasing number of communication channels that contact centres operate through adds more complexity. Each channel – from traditional phone calls to social media and messaging apps – has its own set of compliance regulations.

One of the most common compliance pitfalls is that agents must read out specific phrases and terms to customers. These mandatory statements are essential for protecting both the customer and the business. Failure to comply can result in severe consequences, including fines and reputational damage.

This is where AI speech analytics steps in, offering a powerful solution to many of these compliance challenges. By using the capabilities of AI, contact centres can gain valuable insights into agent interactions and identify potential compliance risks. In this article, we will explore how AI speech analytics – like our Spokn AI software – can be used to improve regulatory compliance and enhance the overall customer experience.

What is AI Speech Analytics and How Does it Collect Data?

AI speech analytics relies on advanced algorithms, natural language processing and deep learning models to record and analyse phone calls. By converting audio files into text formats, speech analytics systems can extract valuable insights into customer interactions and agent performance.

The data collection process starts with the recording and storage of call transcripts in a secure database. These recordings can then be evaluated post-call, giving contact centre leaders valuable insights into agent interactions with customers against KPIs and more.

These are the key features of call recordings powered by AI speech analytics that enable it to function with advanced accuracy:

• Speech-to-text transcripts: Automatically converts spoken language into text, making it easier to review and analyse call content. These transcripts are summarised, providing an easier and quicker way to access and understand historic interactions.
• Keyword/topic spotting: Identifies specific words or phrases within the conversation, allowing for targeted analysis of key topics.
• Sentiment analysis: Determines the emotional tone of the conversation, identifying areas where customers may be frustrated or dissatisfied. Equally, it also pinpoints positive call interactions and these areas of strength can provide a blueprint for agent training.
• Categorise common objections: Sentiment analysis can be used to identify calls that started negatively and ended positively. By pinpointing the most common objections and how they are remedied effectively, call agents can learn how to successfully handle objections.
• Call quality metrics: Focuses on metrics that give better insight into call quality, such as talk-to-listen ratio, talk rate, correct call opening, and agent & customer monologues.

With these capabilities, speech analytics provides contact centre managers with the data they need to monitor agent interactions, identify compliance risks and improve overall customer satisfaction scores.

How AI Speech Analytics Data Supports Regulatory Compliance

AI speech analytics can support regulatory compliance across various industries. Contact centres can gain valuable data that help address common challenges and ensure adherence to industry standards.

Let’s take a closer look at some examples of compliance requirements that contact centres must adhere to. And assess how AI -powered speech analytics can support call centres.

GDPR: The Challenge of Data Protection

Data protection is a big concern for most contact centres, governed by both the General Data Protection Regulation (GDPR) and the Data Protection Act (DPA). While GDPR sets the overarching framework for data protection in the EU (and has been incorporated into UK law post-Brexit as the UK GDPR), the DPA sits alongside GDPR and outlines specific provisions tailored to UK legislation.

Both regulations impose strict requirements on businesses to protect personal data, but the DPA also covers areas not explicitly detailed in GDPR.

For example, the DPA stipulates that call centres must tell customers that their calls are being recorded for transparency and fairness in data collection.

Contact centres must also comply with other industry-specific regulations, such as:

• Direct debit regulations: Agents must read out specific parts of the script when setting up direct debits to ensure customers are fully informed.
• PCI DSS compliance for card information: When handling payment card information, call centres must make sure that sensitive data isn’t recorded. This involves pausing call recordings during the collection of card details to prevent unauthorised access.

Contact centres face significant challenges in complying with these complex and overlapping regulations, including:

• Handling Data Subject Access Requests (DSARs) effectively.
• Preventing and responding to data breaches.
• Obtaining informed consent and ensuring customers are aware of call recordings.
• Ensuring sensitive information is handled appropriately during calls.

AI speech analytics helps to address these challenges, helping contact centres to monitor compliance, reduce the likelihood of regulatory fines and strengthen overall data protection practices.

Here’s how AI speech analytics can help overcome these specific challenges:

Customers can request access to their personal data and ask for deletions or changes to data sharing.

Contact centres must facilitate this. However, it’s often a manual process of searching through vast amounts of recorded interactions to locate relevant information.Solution: By using AI speech analytics, contact centre managers can search through recorded interactions quickly and efficiently to fulfil Data Subject Access Requests.

Speech analytics removes the manual process of locating relevant information, and reduces the time it takes to fulfil DSARs.Challenge 5: Getting Informed Consent from Customers

Contact centres must get informed consent from customers before processing their personal data. Individuals must understand the purposes and implications of data collection and it will be used.

Call agents must communicate this information clearly and provide consent documentation.Solution: AI speech analytics provides searchable text files. These call transcripts can be manually reviewed for specific keywords or phrases to verify agents provide correct information and obtain appropriate consent.

For example, in the sales industry, informed consent means customers understand the features and benefits of a product before buying.

With speech analytics, call centre leaders can manually track keywords or phrases related to the product’s features. This helps call centres leaders to identify calls where the relevant keywords haven’t been used. It gives broader scope to check that agents explain the product clearly and customers understand what they are purchasing.

Consumer Duty Act: Ensuring Fair Treatment and Clear Information

The Consumer Duty Act places a strong emphasis on fair treatment and clear information for consumers. Contact centres must tailor customer interactions to meet individual needs, identify vulnerable customers, minimise human error, and avoid pressurised selling tactics.

So what makes the Consumer Duty Act and FCA guidelines complex to adhere to in a call centre setting?

The ChallengesHow AI Speech Analytics Can HelpChallenge 1: Tailoring Customer Interactions to Address Specific Needs

Every customer has different needs and preferences. But it’s hard for call agents to tailor their approach and give clear and fair information to each customer.

It’s even more difficult to assess whether or not the customer understands what’s been said.As well as taking the overall temperature of the call, sentiment analysis looks at individual phrases,  including responses to product explanations. Sentiment analysis shows if customers may feel confused or frustrated.

If customers express negative sentiments or ask clarifying questions, it suggests they aren’t clear about what has been said by the call agent.Challenge 2: Identifying Vulnerable Customers

Identifying vulnerable customers is difficult because the signs of vulnerability are not immediately apparent.

A vulnerable customer covers various circumstances, including disability, financial hardship, language barriers and emotional distress.

This makes it difficult to establish a single criteria for call agents to use to spot vulnerability.Solution: AI speech analytics provides valuable insights into customer behaviour and language patterns to identify vulnerable customers. Sentiment analysis considers the emotional tone of conversations and detects negativity and distress.

As all call transcripts are searchable, any specific references to communication difficulties or personal challenges, such as disabilities or financial hardship, can be manually reviewed.

Managers and agents can offer targeted support when additional needs are found.Challenge 3: Minimising Misunderstandings & Human Error

All humans make mistakes – including call agents. Sometimes it’s easy for agents to misunderstand customer questions or provide incorrect information. The challenge is how do call centres catch these incidents and rectify them?Solution: AI speech analytics can be used to analyse recorded transcripts post-call.  AI can piece together keywords, tone and pace, to give a better understanding of agent performance.

Call centre leaders can manually compare agent interactions to recommended scripts, highlighting calls where the agent may have given misleading information.

It gives contact centres the opportunity to address mistakes and provide further training.Challenge 4: Encouraging Ethical  Selling Techniques

Agents may feel under pressure to close sales and meet their KPIs, which can sometimes lead to the use of overly assertive selling techniques.

This can be difficult to define and monitor.Solution: AI-driven speech analytics can analyse keywords, tone, pace and sentiment to identify instances where sales interactions may not align with best practices. This helps ensure a positive and customer-centred approach to selling.

Consumer Rights Act: Dealing with Customer Complaints

The Consumer Rights Act outlines the fundamental rights of consumers in the UK. As part of this legislation, contact centres must effectively address customer complaints to demonstrate their commitment to consumer satisfaction and compliance with regulatory requirements.

The ChallengesHow AI Speech Analytics Can HelpChallenge 1: Identifying root causes of recurring customer complaints

Agents handle a large volume of calls everyday. So when complaints happen, it’s difficult for contact centre leaders to identify themes of complaints and assess underlying issues. Recurring issues go unnoticed, impacting customer satisfaction scores.Solution: Speech-to-text technology provides searchable call transcripts of customer interactions that are easier to QA. By analysing these call recordings, contact centres can identify common complaint themes, such as recurring issues with products or services. This information can be used to address underlying problems and prevent future complaints.Challenge 2: Addressing Customer Complaints Efficiently

Resolving customer complaints within a reasonable timeframe can be challenging, especially when dealing with complex issues or requiring coordination with multiple departments. Delays in resolution can lead to customer dissatisfaction and potential regulatory action.Solution: Speech analytics analyses call recordings at scale. This makes it easier for contact centres to verify that agents are resolving complaints within a reasonable timeframe, and following appropriate procedures.Challenge 3: Ineffective Complaints Handling Training

Generic training that fails to address the specific needs of agents can lead to ineffective complaint handling. This, in turn,can result in longer resolution times, decreased customer satisfaction, and an increase in escalated complaints. Ineffective complaint handling can also lead to non-compliance with regulations, resulting in fines or penalties.Solution: Analysing agent interactions during the complaints process can help identify training gaps related to complaint handling. This allows contact centres to provide targeted training to equip agents with the skills and knowledge to address customer concerns effectively.Challenge 4: Implementing an Effective Complaint Handling Process

Ensuring that customers are satisfied with the resolution of their complaints is essential for maintaining a positive reputation and avoiding negative publicity. It can be difficult to assess customer satisfaction and identify areas for improvement without the right tools and data.Solution: Speech analytics helps to measure customer satisfaction with the complaint resolution process itself. Customer sentiment during the process identifies areas of dissatisfaction and opportunities for improvement.

Why AI Speech Analytics?

Compared to traditional speech analytics, AI-powered software is much more effective – particularly when it comes to supporting compliance. AI has the ability to recognise nuances in conversation, adapting seamlessly to variances in language and emotion compared to rule based keyword spotting alone.

This means that AI speech analytics is much more accurate when assessing agent performance against intricate regulations. This, combined with the AI software’s capability to process and analyse large volumes of calls makes it offers a time-efficient solution for ensuring compliance with GDPR, DPA, PCI DSS, and other regulations.

Overcoming Common Concerns

Of course, it’s critical that we don’t ignore common concerns that some contact centres have around AI speech analytics.

Questions are often asked around how contact centres can ensure that collected data is handled and stored securely in compliance with regulations. And then there’s the issue of agent resistance, with some call teams expressing concerns over job security and privacy.

While these concerns are all valid conversations to have, they can easily be addressed by putting the right procedures in place:

• To ensure data sovereignty and compliance with regulations like those enforced by the FCA, work with providers like MaxContact – as our databases are all located within the UK.
• Use encryption, access controls, and regular backups to protect sensitive data and implement robust data security measures.
• Take the time to explain how AI speech analytics can improve efficiency, quality and compliance to the wider team.
• Offer training to help agents understand how speech analytics can be used to enhance their performance.

Involve agents in the implementation process and seek their input, addressing their concerns and gaining their buy-in.

Reaping the Benefits of AI Speech Analytics

The concerns outlined above are easier to navigate when you work with a trusted provider. MaxContact has worked with numerous contact centres to help them implement our Spokn AI platform – and the results speak for themselves.  

Honey Group, a financial services company, was struggling to review all calls for compliance purposes due to limited resources. They worked with MaxContact to implement our AI speech analytics software.

Honey Group has leveraged call transcripts and sentiment analysis to monitor inappropriate mentions of sensitive topics, ensuring compliance with industry regulations. As a result of Spokn AI, Honey Group has drastically improved quality assurance and the way they approach agent training.

[Read the full case study]

AI speech analytics empowers contact centres to stay ahead of complex regulatory compliance. But, by leveraging the power of AI, contact centres can gain valuable insights into agent interactions, identify compliance risks and ensure adherence to industry standards.

From GDPR to the Consumer Duty Act, AI speech analytics offers a robust solution for addressing many compliance challenges.

As regulatory requirements continue to evolve, AI speech analytics can adapt alongside them for effective compliance management.

Ready to take your contact centre compliance to the next level? See how Spokn AI, MaxContact’s industry-leading speech analytics platform, can transform your operations.

Book a free demo today!

‍

If you work in a contact centre, you know quality assurance (QA) can often feel like a box-ticking exercise. Yet, QA is the backbone of exceptional customer service, agent development and operational efficiency. The challenge? Many QA processes are time-consuming, resource-intensive and limited in the insights they provide.

What if your QA process could do more? Imagine evaluating every customer interaction, uncovering what drives success, and delivering precise, actionable feedback – all without additional effort. This is where AI speech analytics steps in, offering transformative solutions that redefine how QA drives results.

At MaxContact, we’re taking this a step further with Spokn AI Success Intelligence. Designed for revenue-driven teams, this next-generation platform delivers actionable insights to optimise performance, ensure compliance and boost customer experiences.

The challenges with traditional QA in contact centres

Do your current QA methods give you the insights you need to truly drive agent performance?

QA is essential, especially when you consider that 93% of customers are likely to make repeat purchases from companies offering excellent customer service (HubSpot). However, traditional QA methods often struggle to meet the demands of modern contact centres. Here’s why:

1. Resource constraints: Reviewing even a small sample of calls manually is time-intensive and costly. Due to limited resources, many contact centres evaluate only a fraction of their total interactions, leaving critical insights untapped.
2. Subjectivity and bias: Human evaluators often bring unconscious biases into assessments, leading to inconsistent results and insights that may not accurately reflect agent performance or customer sentiment.
3. Shallow insights: Traditional QA often focuses on generic metrics like call handling time or first call resolution. While useful, these metrics don’t capture the complexities of customer interactions or agent effectiveness.
4. Missed opportunities: Manual QA rarely identifies deeper trends, such as recurring objections, common customer frustrations, or effective objection-handling techniques. These insights could shape training, scripting and processes to drive better results.

For sales and collections teams under pressure to deliver more with fewer resources, these limitations highlight the need for a smarter, more scalable approach.

How does AI speech analytics transform QA?

AI-powered speech analytics addresses the challenges of traditional quality assurance by automating call analysis and uncovering insights that traditional methods miss. Tools like Spokn AI transcribe 100% of calls from speech to searchable text files, providing a more comprehensive view of performance.

Key benefits of AI speech analytics

• Comprehensive call coverage: By evaluating every interaction, AI eliminates sampling errors and ensures that no valuable insight is missed.
• Objective assessments: AI removes human bias, delivering consistent evaluations based on data rather than opinion.
• Nuanced insights: Sentiment analysis, phrase identification, and trend tracking aid a deeper understanding of customer-agent interactions.
• Faster feedback loops: With automated insights, managers can provide near-real-time feedback to agents, reducing time between evaluation and improvement.

By automating the labour-intensive aspects of QA, contact centres can focus on driving results instead of sifting through data.

Set clear QA objectives with AI speech analytics

To make the most of AI, it’s essential to align your QA process with clear objectives. Here’s how to get started:

Step 1: Identify QA challenges

Focus on areas where your current QA process is falling short. For example:

• Are call agents struggling to follow scripts?
• Is customer satisfaction lagging?

Understanding these pain points will guide how to strengthen the output of QA processes with AI speech analytics.

Step 2: Define success metrics

Traditional metrics like average call handling time or first call resolution are helpful but don’t tell the whole story. AI speech analytics allows you to measure more nuanced factors, such as:

• Sentiment shifts during calls.
• Frequency and type of customer objections.
• Agent adherence to compliance scripts.

The real power of AI lies in turning data into action. Use insights to refine training programs, improve scripts, and optimise processes, ensuring continuous improvement across the board.

Practical applications of AI speech analytics

Now we’ve defined why using AI speech analytics to aid QA is better than traditional methods, let’s explore how tools like Spokn AI can be used to address specific QA challenges and improve outcomes.

1. Identifying training needs

AI can quickly identify where agents struggle – whether it’s handling objections, following scripts, or navigating sensitive customer issues. With a clearer view of these challenges, managers can:

• Develop targeted training programs that address specific skill gaps.
• Track progress over time to ensure improvements are sustained.

2. Enhancing compliance

Non-compliance can lead to fines and reputational damage. Speech analytics platforms, like Spokn AI, makes compliance checks faster and more reliable by helping QA teams to uncover calls where agents:

• Fail to disclose required information.
• Use unapproved language or phrases.

Without the use of AI speech analytics, this part of the process relies on quality assurance teams listening to calls, which is not only time consuming but focuses on a very small sample of calls.

The capability to search or track text transcripts for specific keywords related to compliance, speeds up the process and makes it much more scalable and robust, protecting your organisation from unnecessary risks.

3. Providing tailored feedback

Generic feedback rarely drives meaningful improvement. AI powered speech analytics software allows managers to deliver precise, data-driven feedback tailored to each agent. For instance:

• Highlight areas of strength, such as effective objection handling or empathy.
• Address weaknesses with actionable suggestions, like improving script adherence.

This targeted approach empowers agents to improve rapidly while creating a culture of continuous learning.

4. Recognising top performers

Spokn AI identifies challenges, yes. But it also highlights what’s working well. By analysing successful calls, contact centres can learn what top-performing agents do differently and replicate their techniques across teams.

Rewarding and recognising these agents boosts morale, also reduces turnover, and sets a standard of excellence for others to follow.

Ready to welcome AI speech analytics? Build your business case.

Can we take quality assurance even further with speech analytics?

Quality assurance is undeniably a crucial part of contact centre operations, with 83% of contact centres recognising it as a critical process, according to our benchmark report. But even with the help of speech analytics, QA is often limited to providing only surface-level insights.

For revenue-driven teams in particular – such as those in sales or collections – standard QA outputs often fall short. These teams need more than just metrics; they need precise, targeted and rapid feedback to drive results.This is where advanced solutions like Spokn AI Success Intelligence come in, elevating QA from a process of evaluation to a driver of performance and improvement.

Introducing Spokn AI Success Intelligence

Designed for revenue-driven teams, our upcoming Spokn AI Success Intelligence feature provides deeper insights into what drives performance, enabling more targeted coaching and process optimisation.

By delivering actionable insights into the “why” behind performance metrics, it empowers teams to go beyond compliance and drive real business growth.

So, what’s the difference?

To understand what Spokn AI Success Intelligence is, you need to know how it moves beyond traditional speech analytics to add a deeper level of insight into sales and collections processes:

Objection handling analysis

Categorises common objections, correlates them with outcomes, and provides actionable insights to refine scripts and coaching strategies.

Call DNA mapping

Identifies the key elements of successful calls—such as sentiment shifts and effective phrasing—allowing teams to replicate these across the organisation.

Enhanced coaching tools

Provides tailored insights that empower managers to deliver precise, impactful feedback, accelerating agent development.

Scalable automation

Analyses 100% of calls without additional effort, freeing QA teams to focus on implementing insights and driving improvements.

Transform QA into a driver of growth

MaxContact has over 20 years of experience in the sales and collections space, working closely with leading AI providers to develop best-in-class solutions.

• Deliver tailored coaching that drives measurable improvement.
• Optimise processes and scripts to maximise performance.
• Enhance customer experiences by addressing systemic issues proactively.

With Spokn AI Success Intelligence, we’re helping contact centres unlock the full potential of their teams and processes.Ready to see it in action? Request a demo today.

‍

We caught up with Ben Booth, CEO of MaxContact, Matthew Yates, VP of Engineering at MaxContact, and James Revell, Director of Whistl Contact Solutions to discuss the transformative impact of artificial intelligence (AI) in the contact centre. In this blog, taken from the rich discussion in a previous webinar, we explore the meteoric impact AI is having on customer experience and contact centres. We’ll look at the explosion of interest in AI over the past 12 months, why businesses can’t afford to ignore it, and what the future may hold as these lightning-fast technological shifts unfold.

The Dawning of a New Era

We are undeniably in an era of rapid advancement for AI and machine learning. From chatbots to speech analytics, AI-driven technologies are evolving quicker than ever before – and the customer experience landscape is being fundamentally reshaped as a result.

According to recent research, worldwide annual spending on conversational AI for contact centres is predicted to rise substantially by 15% to $18.6 billion in 2023 alone. These staggering stats make it clear that AI-powered solutions are the future for many businesses across all industries. Those who embrace AI with a robust strategy and an eye toward human collaboration will gain a competitive edge.

Automation for Efficiency, Insight for Innovation

For customers, AI promises highly personalised, consistent, and always accessible service. As Matthew Yates, VP of engineering at MaxContact, noted, “AI can help understand the intent behind customer questions, and it can do two or many more things like instantly fast-track consumers to an agent trained to solve my specific issue. Or if I’m a caller with a simple query who wants it resolved as quickly as possible, I can speak to an AI chatbot.”

For agents, AI eliminates the most tedious and time-consuming administrative tasks, freeing them up to focus on more complex interactions. And for businesses, conversational AI unlocks invaluable data insights to spot trends and opportunities for optimisation.

AI-powered systems are already spurring exciting developments across the board:

• Automated identity verification and intent detection can fast-track customers to the right solutions without lengthy wait times or repetition of information.

• Real-time call summarisation with metadata tagging equips agents with instant case notes and critical context on each interaction.

• Aggregate data analysis allows managers to quickly identify changes in contact drivers and agent performance over time. When applied strategically alongside human skills and abilities, AI promises to optimise efficiency, consistency, innovation and more across the entire customer journey.

But it is not a silver bullet…

The Perils of Viewing AI as a Silver Bullet

In the pressure cooker environment that many companies find themselves in today, there is a very real risk that AI could be viewed as a quick fix, a silver bullet to instantly solve all business problems.

As Ben Booth, CEO of MaxContact, cautioned, “There is a bit of an arbitrage around AI’s neck currently.” The reality is never so simple. Automating certain emotional interactions – like debt negotiation calls – may increase efficiency but lacks human empathy. Overuse of AI without careful consideration for collaboration with human agents is likely to cause backlash from frustrated customers.

As Booth emphasised, while AI cannot match the innate human abilities to build rapport, interpret emotion, and creatively problem-solve in real-time, there are “always improvements in overall customer experience, but also agent and business efficiencies.”

Contact centres must work to find the balance between AI and human interaction. This means mapping AI to appropriate use cases where it excels while retaining readily available human touchpoints for addressing complex queries. Those contact centres that embrace AI as an optimisation tool rather than an outright replacement are far more likely to unlock its full potential.

The Future Role of The Human Agent

Will the explosion of AI spell the end for the contact centre agents? Our webinar panel unanimously agreed this is highly unlikely. However, the role of agents will inevitably need to adapt and evolve along with advancing technology. As James Revell, Director of Whistl Contact Solutions, noted, AI technology, such as speech analytics, will allow each agent to “get up to speed faster” by providing “real-time knowledge appropriate to the conversation.” It is expected that up to 70% of current repetitive tasks could be automated by 2030, freeing agents to focus purely on high-value customer interactions. This transfer of mundane responsibilities to AI assistants broadly signals positive news for employees. Rather than displace human roles, AI should augment inherently human strengths like emotional intelligence, judgement calls and creative problem-solving.

However, dealing exclusively with the most challenging issues may take an additional toll on agent well-being even as routine matters are automated. This demands more significant consideration from employers around updated training, coaching, incentives, scheduling, stress management and more to keep human agents positively engaged as automation expands.

With proper change management, cultural integration, and updated skill-building, forward-looking contact centres can empower their people and technologies to collaborate and combine forces for exceptional customer and employee experiences. The agents of the future will not be replaced outright by machines but rather continually reinvented.

Navigating the Road Ahead

From data analytics to automated self-service interactions to enhanced human performance, it’s clear that AI harbours the nearly boundless potential to transform contact centre operations. But to build sustainable success, the companies that thrive will be those that embrace AI as an optimisation tool rather than a replacement for existing roles. This winning strategy plays to the strengths of both intelligent machines and thoughtful people skills.

While the benefits may be profound, rapid AI advancement also raises pressing challenges around ethics, security, privacy and compliance. Legal and regulatory frameworks are struggling to keep pace with such fast-moving technological innovation. There are likely growing gaps that urgently need addressing regarding social impacts, transparency, accountability and more as AI permeates existing business processes. Both private companies and public policymakers need to work diligently to get ahead of these rising challenges.

In the meantime, contact centres must take stock of their unique responsibilities today. This means thoroughly vetting any AI systems to safeguard against issues like bias or misuse of customer data. It also requires open, transparent communication with staff to cover intended AI applications and how their roles may need to adapt. Like any transformation, success will be determined not merely by the technology itself, but rather by the thoughtfulness of the associated change management and cultural integration.

The Future Remains Bright

In closing, the future remains exciting. Conversational AI still has a vast, largely untapped scope to transform operations through human and machine collaboration. But sustainable success lies in integrating human intelligence and artificial intelligence in a responsible, ethical and supportive fashion.

The metaphorical butterfly effect is already in motion today, with much greater change still to come across industries. Contact centres have an opportunity to lead responsibly and realise monumental gains for customers, employees and their broader communities alike if they navigate wisely.

To find out more about how MaxContact can support your contact centre’s AI journey, get in touch with our team here.

‍