How Generative AI is Transforming Contact Centres

There is a quote which says that “there are decades where nothing happens; and there are weeks where decades happen”. When looking at the last months, I see a leap on contract centres transformation, AI is revolutionising contact centres from even before first ring to post-call analytics!

Generative AI is redefining the entire landscape of customer service. Through intelligent routing, real-time agent assistance, and deep post-call analytics, AI empowers contact centres to deliver unparalleled customer experiences while also enhancing agent performance. The journey from the initial ring to post-call feedback is smoother, more personalised, and efficient, setting new standards for what customers and businesses can expect from their interactions.

Contact centres are the frontline of engagement, where every call, message, or interaction can turn a customer into a loyal advocate or a detractor (NPS). The integration of generative AI into contact centres represents a leap forward, offering personalisation, predictive capabilities, and real-time assistance. This transformation is not just about enhancing operational efficiency; it's about reimagining the very nature of customer interactions.

Your data is Key! Data is the only competitive advantage in AI.

Read below my other blog on data gravity.

In a modern contact centres, the data flywheel starts with the accumulation and understanding of customer data. This step is foundational, as it provides the insights necessary for all other stages. As we gain a deeper understanding of customer behaviours, preferences, and needs, we can then move to the next stage: tailoring services to fit individual customer profiles.

Customised services lead to a more satisfying interaction for the customer, which should be the heart of a contact centre's operation. Personalisation can result in a more efficient operation as resources are allocated based on predicted needs, leading to better management of time and staff.

Enhanced efficiency naturally contributes to reducing operational costs. Savings can then be reinvested into further improving customer service—be it through training, better software, or other resources—thus beginning the cycle anew.

Art of Possible: Harnessing Generative AI for the Next-Generation Contact Centre

Initial Touchpoint

Artificial Intelligence transforms contact centre experience by predicting why customers are calling before they're even connected to an agent. This predictive calling capability is powered by analysing customer data, including previous interactions, transaction history, and common queries related to the time of day or recent events. Agents receive a comprehensive data snapshot, enabling them to understand and address the customer's needs more efficiently.

• Call and Customer Issue Categorisation: Generative AI can automatically categorise calls based on the customer's inquiry, allowing for efficient routing to the most appropriate agent or self-service resources.
• Proactive Engagement: Based on customer profiles and past interactions, voice bots can proactively reach out to customers with appointment reminders, personalised offers, or alerts about potential service disruptions.
• Next-Generation IVR with Voice Bots: Voice bots represent a leap from traditional IVR systems. Instead of pushing buttons, customers simply speak their concerns and are understood by natural language. These bots can handle a range of requests, from simple queries to complex issues, and direct customers to the appropriate service channel, dramatically enhancing the user experience.
• Advanced Voice ID Authentication: By analysing unique voice biometrics, AI can verify a caller's identity, reducing the need for security questions and speeding up the authentication process. This tightens security but also adds a layer of convenience, as returning customers can be authenticated more swiftly.
• Fraud Prevention: AI and machine learning are at the forefront of detecting and preventing fraud. By monitoring call source analytics and using multilayered authentication techniques, such as voice biometrics and behaviour analysis, AI systems can flag unusual patterns of behaviour that may indicate fraudulent activity. For instance, if the system detects that a number is frequently used for short calls across multiple accounts, it can raise an alert for potential fraud.
• Entity Resolution for Customer Profiles: Generative AI can extract key information from caller interactions (name, address, account details) and update customer profiles in real-time. This ensures agents have access to the most up-to-date customer data.
• Conversational Profile Building: During interactions, voice bots can build customer profiles by asking relevant questions and capturing preferences or past interactions. This allows for more personalised service and targeted recommendations.

Omnichannel engagement

Consumers expect seamless service across multiple channels—whether that's through voice calls, live chat, virtual agents, or social media platforms. By integrating them, we can create a unified layer of predictive engagement that transcends individual channels. This approach allows us to not only anticipate and understand customer needs before they even articulate them but also ensure robust authentication and fraud prevention measures across all touchpoints. Such a comprehensive, AI-powered omnichannel strategy doesn't just meet customer expectations—it exceeds them.

Self Service

Imagine a customer picking up the phone or typing in a chat window and being greeted by an AI that can talk just like a human. This is what's happening with advanced conversational bots, which are a form of generative AI. These bots are smart enough to understand what the customer needs through natural, easy conversation. They can make their way through complicated questions and decisions, pick up important details, and often sort out the customer's problems right there—no need for a real person to step in. This kind of self-service shows us just how clever AI has become at handling our questions and tasks.

• Virtual Assistant Integration: Virtual Assistant can help in everyday tasks like answering common questions, guiding through FAQs, and organising appointments. Generative AI can help decrease the number of calls that require a human on the other end. When a customer asks something that's heard often—like "What are your opening hours?"—a virtual assistant can steps in immediately, leaving the human agents free to deal with more complicated matters.
• Personalised Hold Messages with Progress Updates: Instead of generic hold music, generative AI can create informative messages tailored to the customer's inquiry, keeping them updated on wait times and offering relevant resources, upselling or cross selling. Generating Personalised Holiday Greetings, during peak seasons, generative AI can create personalised holiday greetings for customers and subtly suggest relevant seasonal products or promotions.
• Real-time Transcription and Translation: During multilingual calls, AI can provide real-time transcription and translation, ensuring clear communication between the customer and agent.
• Sentiment Analysis: AI can analyse a customer's voice and words to understand their emotions in real time, allowing agents to tailor their approach and improve customer satisfaction

Intelligent Routing

Voice bots and conversational AI are redefining the first-line of defence, these systems can now instantly write out what's said and translate between languages, making sure customers get help fast, no matter what language they speak. If a query is too complex for the AI, it hands off the call to a human agent. But it's not just any agent—the AI chooses one who's got the right skills for this particular issue, based on what it knows about the customer and the problem. This selection isn't only about who's available; it also considers which agent is best suited for the customer's current mood and needs, making the connection not just fast, but smart.

• Skill-Based and Sentiment-Based Routing: Generative AI can analyse the customer's query, their sentiment, and past interactions, ensuring they are connected to the agent best suited to their needs. This might mean matching a customer with an agent specialising in the product they're inquiring about or routing a particularly frustrated caller to an agent skilled in de-escalation techniques.
• Real-Time Agent Availability and Status: AI doesn’t stop at intelligent routing; it also manages real-time agent availability, predicting when agents will be free based on ongoing call durations, break schedules, and after-call work. This capability ensures that calls are distributed efficiently, minimising wait times and optimising the workload among available agents.
• Queue Prioritisation: Generative AI can analyse call urgency and customer profiles to prioritise calls in waiting queues, ensuring critical issues are addressed first or based on the customers loyalty status.
• Agent Ranking and Scheduling: Based on performance metrics, skillsets, and real-time availability, AI can rank agents to optimise call scheduling for efficiency and customer satisfaction.
• Call Re-routing (re-balancing) and Overflow Management: When a specific queue experiences high call volume, AI can intelligently re-route calls to other available agents with relevant expertise in queue that can serve as an alternative or offer self service options or call backs.

Agent Experience

Generative AI is reshaping the support agents receive, acting as an ever-present digital helper. It whispers the best responses, digs up information quickly, and can even wrap up the main points of a conversation. This means agents can give their full attention to the person on the other end of the line, making the service more personal and efficient. As the conversation unfolds, the AI is there every step of the way, offering agents advice on how to talk, what information to use, and how to smoothly navigate tough the conversation. This ongoing support allows agents to adjust their approach immediately, ensuring every customer interaction gets better as it goes.

• Real-time Coaching Prompts: Generative AI can analyse call content in real-time and suggest coaching prompts for agents, helping them improve their communication style, knowledge, and de-escalation techniques.
• Voicemail Transcription and Pre-Answering: Generative AI can transcribe voicemails into text for easier agent review and generate the response to any open questions on the voicemail, task or followup needed.
• Automatic Reminder Systems: Generative AI can create and deliver automated reminders to customers or agents about upcoming appointments, service renewals, or important information.
• Task Creation and Management: Based on call content, generative AI can automatically create follow-up tasks for agents (e.g., sending invoices, scheduling appointments) or generate reports for further analysis.
• Generating Response Drafts for Customer: Generative AI can draft measured and professional response templates for faster and more consistent customer service.
• Summarisation and Follow-up Emails: After a call, generative AI can automatically summarise the key points of the conversation and generate a follow-up email to the customer. This email can reiterate any solutions discussed and provide additional resources, ensuring the customer has a clear record of the interaction.
• Improved Agent Onboarding & Training: Generative AI can create realistic call simulations to train new agents. These simulations can expose agents to a variety of scenarios and help them develop their communication and problem-solving skills.
• Personalised Training Material Generation: Based on agent performance reviews and call data, generative AI can create personalised training modules that address specific knowledge gaps or communication weaknesses.

Supervisors

Workforce Management, by analysing call volume trends and historical data, generative AI can assist with scheduling agents, optimising capacity planning, and forecasting future staffing needs for efficient workforce management.

• Predictive Call Volume Forecasting: Generative AI can analyse historical trends, seasonality, and marketing campaigns to predict future call volume, allowing for proactive resource allocation.
• Predictive Agent Requirements: Based on projected call volume, generative AI can predict the number of agents needed to maintain efficient service levels during different periods.
• Post-Call Analysis and Quality Assurance: Generative AI can automatically summarise key points from calls, it can create an automated call scoring and sentiment analysis, providing valuable data for objective agent performance reviews and coaching sessions.
• Agent Scheduling and Workload Management: Forecasting demand for live agents begins by understanding your desired service lever, such as answering 80% of calls within 30 seconds. As illustrated in the diagram below, you then follow a process that enables you to forecast the workload (number of live agents) required to meet your SLA

In order to forecast workload, contact centre managers often use an Erlang C calculator. The key inputs are:

• Average talk time, or ATT (in seconds)
• Average after call work, or ACW, time (in seconds)
• Number of calls
• Service-level objective (in seconds)
• Shrinkage

?The output looks something like the image below. It enables contact centre managers to determine how many agents they’ll need to reach the desired SLA

Additional Use Cases

• Rating Prediction: Generative AI can analyse call content and predict customer satisfaction ratings, allowing for proactive intervention if a negative review is likely.
• Call Escalation Prediction: By analysing call data and agent responses, generative AI can predict the likelihood of a call needing escalation, prompting early intervention to prevent customer frustration.
• AI-powered Lead Qualification: During sales calls, generative AI can analyse customer responses and qualify leads in real-time, helping agents prioritise high-potential opportunities.
• Post-call Surveys with Personalised Recommendations: Generative AI can craft targeted surveys after a call, gathering feedback and suggesting relevant products or services based on the customer's interaction.
• Proactive Outreach and Reminders: AI can analyse customer data to predict potential issues and proactively reach out to customers. For instance, it could call a customer about an expiring warranty or recommend a product upgrade based on their past purchases.
• Content creation for self-service channels: Generative AI can analyse call recordings to identify frequently asked questions and top customer concerns, informing FAQ updates and agent training. This content can be used also for self-service channels like FAQs and knowledge bases.
• Data analysis and insights: Generative AI can be used to analyse call centre data to identify trends and improve efficiency. For example, it can be used to identify common customer issues and develop solutions to prevent them.

Enhancing Customer and Agent Satisfaction

The introduction of generative AI into contact centres has created a paradigm shift, where personalised customer service is delivered more efficiently and effectively than ever before. From the moment a customer initiates contact, through the conversation with agents, and in the follow-up and analysis that requires, AI plays a pivotal role in ensuring a seamless, satisfying experience. For agents, AI not only provides real-time support and guidance but also contributes to their development and job satisfaction by reducing those repetitive tasks and allowing agents to dedicate more time and energy to tasks that require human judgment.

As we look to the future, it's clear that the role of generative AI in contact centres will continue to evolve and expand. With advancements in AI technology, we can expect even more sophisticated analysis of customer sentiment, deeper personalisation of customer interactions, and further automation of routine processes. The potential for AI to enhance the efficiency of contact centres and the quality of customer service is vast and largely untapped.