Using Real-Time Analytics to Create Fluent Customer Interactions

Artificial intelligence (AI) tools have become ubiquitous in all parts of our lives — and they’re continually improving to help companies deliver faster and more personalised services. With these advances, consumer expectations have also risen, and they have less patience for subpar experiences. Acting in real time is essential to meet baseline expectations for today’s consumers.

With AI, customer experience (CX) agents can instantly understand what customers want and take action. Previously, contact centre supervisors and managers had to listen to live calls and assist agents in the moment. Now there’s no need to have several people listening; virtual agents can actively listen to detect emotions, surface knowledge or coach the agent in real time. And, thanks to AI, they can capture and understand nuances in interactions and summarise them.

AI also impacts the employee experience. To provide excellent service, your customer support teams need to access the latest customer information, during the interaction, to resolve problems quickly and with empathy. Having this customer journey data on the agent desktop becomes an analytics source for agents.

It gives them relevant context, so they can understand what the customer is trying to accomplish, such as searching for a particular product. This not only makes customers happy, but it also enhances employee engagement and improves job satisfaction.

AI works in real time to translate a call or detect intent. This information is then surfaced through analytics, such as speech and text analytics. Together, these insights give companies the ability to truly personalise customer interactions – creating differentiation from their competitors. Let’s look at how companies can use next-gen analytics to win in the experience economy.

The Business Case for Real-Time Analytics

Real-time data gives you a snapshot of a specific moment in time. It can be social data or data captured in a business ecosystem. Its value, particularly in customer interactions, is that having data instantly and automatically available to any authorised user – including all business systems and processes – means that it can be monitored and visualised, for example, on dashboards.

Insights from this massive volume of data can be very valuable to:

  • Inform and support humans during interactions
  • Enhance operational efficiency by reducing repeated interactions
  • Reduce handle time and the number of transfers required
  • Improve sales conversions
  • Reduce churn by using agent assistants/copilot in real time

The analytics and insights produced through AI algorithms enable the best possible decisions, such as driving smarter and more personalised customer engagements.

By engaging in fluent conversations with customers and capturing their intent, AI-powered bots play an important role in understanding customer needs and demands. All the data captured throughout the conversation can be shared across the business for different purposes, including self-service, routing, reporting and other agent interactions. The business can also use that information to proactively deliver preferred services.


A company is only as good as its service, say 86% of consumers globally in a Genesys report on customer experience. And one-third of those surveyed switched brands after a bad experience in the past year.
The State of Customer Experience, Genesys, 2023


What It Means to Orchestrate Better Experiences

Experience orchestration goes way beyond traditional methods of personalisation. It combines real-time analytics and insights with past behaviours, using AI to drive better experiences. It enables you to gain visibility into where your customers are experiencing issues, such as being unable to transfer money, pay a bill or schedule an appointment. You can surface these insights and collaborate with teams to fix the issues and help customers achieve their goals.

Modern customer journey management technology provides the insights you need so that each interaction reflects a customer’s entire experience with an organisation. As a result, every interaction is highly personalised because it’s based on each customer’s objectives and preferences. It’s a more strategic perspective on the customer and employee experience because it streamlines journeys and improves overall business outcomes.

By analysing large amounts of data during this process, AI algorithms identify patterns and intents that humans might overlook or can’t respond to quickly. This real-time capability enables businesses to provide value that truly addresses customer needs in the moment.

Focus on Results with Real-time Data and Analytics

When you begin exploring use cases for real-time data and analytics, start with the results you want to achieve and how they’ll help customers, employees and your business. Here are several ways AI has a direct and positive impact on your contact centre.

  • Identify Clear Patterns with Contact Centre AI Routing

Real-time data lets you move beyond static routing rules and embrace truly dynamic routing  strategies. Predictive routing, also known as AI routing or automated routing, represents a paradigm shift from using other, more limited and manually configured routing.

AI routing systems can identify clear patterns in complex interaction data — and they’re constantly learning. This means your system can spot patterns that will lead to the best customer-to-agent matches.

As engagement patterns change, the AI adapts to find the new ideal outcomes, with minimal human input needed. All these changes can be based on KPIs you choose, such as calibrating your system to optimise routing for metrics like customer satisfaction (CSAT), seasonal sales targets and others.

With AI tools driving your routing strategy, you can automatically direct incoming interactions to the appropriate agents or resources. This saves agents time and makes it easier for customers to reach a resolution.

  • Act on Insights with Customer Journey Management

Consumers use countless digital channels to reach out to companies. And they expect simplicity and speed from customer service interactions. Yet, most customer journeys are fragmented and frustrating.

The best way to meet preferences for multiple channels is to be channel-agnostic. This requires orchestrating optimal experiences to deliver a connected customer journey that moves seamlessly across digital and voice channels. It should also move customers closer to a resolution — faster.

Orchestrating the end-to-end customer journey can bridge silos and eliminate obstacles. It enables you to provide fluid, personalised journeys across channels — at scale and in real time.

Journey mapping uses predictive engagement to inform customer interactions in real time. It gives you a way to envision the best pathways, while customer journey analytics provides insight into your customers’ actual behaviours. It also allows you to identify issues and opportunities in existing processes.

This is a powerful combination that not only enables companies to improve CX, but also to increase alignment across the enterprise. Plus, successful journeys can shape customer behaviour, reduce customer effort, improve efficiency and build customer loyalty.

  • Identify the Root Cause of Escalations

With real-time analytics, you can detect and remediate issues the moment they happen to improve overall efficiency. Ultimately, this leads to optimised operational performance.

Let’s look at a real-world example of using customer journeys for root cause analysis. A call centre manager noticed a jump in multiple agent transfers and handle times. By analysing IVR interactions, call drivers and recordings, the manager found that 30% of customers encounter an issue with their router. Of those 30%, almost half visit an FAQ page advising them to reboot their router — but rebooting fails to resolve the issue.

That’s when customers place a call. A customer service representative walks them through the reboot process, not knowing they’ve already completed this step. Then they’re transferred to a technical support agent to resolve the issue, increasing call minutes.

But when the company had real-time insight into the entire customer journey, the call centre manager worked with the IVR director to directly route customers who’ve initiated a device reboot in the past 24 hours to technical support. This initiative decreased average handle time by 3% and agent transfers by 5%. And it increased the Net Promoter Score for repair journeys.

Unlock AI with a Real-Time Data Strategy

Using the power of AI, real-time data and analytics insights solve major issues for modern customer-first businesses. As you explore where AI fits into your strategy, think about results first. Focus on essential use cases that support your business goals and the customers you serve.

To keep up with rising customer expectations and stand out from the competition, companies need to understand where their customers are in their journeys — and where they’ve been.

AI creates this world of unprecedented understanding and insight — and can transform every area of business. Learn more about capabilities that create the most value for your customers, employees an business in the 2024 Contact Centre Buyer’s Guide. Plus, you’ll get information on key questions to ask vendors about their AI solutions.