How AI Analytics Can Improve Call Centre Performance

Modern call centres have implemented artificial intelligence (AI) into their operations for several years, providing helpful features like auto-diallers, interactive voice response (IVR) systems, and real-time agent guidance.

AI analytics has further assisted call centres with drilling down important metrics, reviewing conversations, and better understanding customers.

In this post, CallMiner explores role of AI analytics in call centre performance, including:

• How AI analytics has transformed the modern call centre
• 5 ways AI analytics improves call centre performance
• Agents get real-time feedback
• Supervisors can readily identify strengths and areas needing improvement
• Call centres learn customer behavior
• AI analytics help reduce costs
• Call centres may see reduced agent turnover
• Analyze conversations to deliver better performance
• Frequently asked questions

How AI Analytics Has Transformed the Modern Call Centre

Earlier versions of call centres required agents to be a lot more hands-on with tasks like call routing, after-call notes and organization, customer categorization, and QA scoring.

Today, call centres rely heavily on AI to complete these tasks while gaining more insightful information than they could gather manually, like customer sentiment and customer journey mapping.

AI analytics specifically targets how a call centre gathers and makes sense of data. AI technologies can analyze customer interactions across channels, customer satisfaction scores, and customer behaviors to help call centres make positive changes for customers.

5 Ways AI Analytics Improves Call Centre Performance

Call centres can turn to AI analytics to enhance agent performance, better understand their customers, and improve efficiency to reduce costs.

1. Agents Get Real-Time Feedback

One type of AI analytics, conversation analytics, monitors and breaks down conversations between agents and customers into actionable insights.

Conversation analytics determines if a customer needs more assistance than an agent is currently providing by analyzing sentiment, emotion, and language, and identifies when and how an agent can provide that help.

As a result of conversation analysis, an AI-powered call centre platform can provide feedback to agents in real time as they communicate with customers to steer the conversation in the right direction, increase sales, and improve customer satisfaction.

This happens in the form of live suggestions straight to agent dashboards and insights delivered to supervisors as calls happen, allowing for speedy coaching opportunities.

2. Supervisors Can Readily Identify Strengths and Areas Needing Improvement

AI analytics helps supervisors see the strengths and improvement areas of the call centre as a whole and each agent individually to ensure the best customer experiences.

This drill-down allows supervisors to coach agents in key areas and identify ways for the team to enhance customer interactions.

3. Call Centres Learn Customer Behavior

By tracking customer interactions, AI analytics can determine what actions tend to drive certain customer behaviors, like deciding to buy a product or service or requesting a call escalation. These insights give call centres the information they need to meet customer needs and improve customer experiences.

4. AI Analytics Help Reduce Costs

AI analytics can increase efficiency by handling many tedious tasks that call centre agents would typically be responsible for.

By determining where calls need to be routed, how to organize customer calls, and when to offer additional help, like a chatbot, AI analytics can cut down on the time it would otherwise take to manage customer contacts. In turn, a call centre could reduce labor costs and costs associated with customer churn.

5. Call Centres May See Reduced Agent Turnover

AI analytics may help call centre agents feel more prepared to handle customer needs. By analyzing when to provide feedback and suggestions and reducing the need for agents to complete repetitive tasks, agents could feel more confident in their abilities to help customers and, as a result, more satisfied with their jobs.

Analyze Conversations to Deliver Better Performance

Conversation intelligence software helps today’s call centres work smarter instead of harder. AI analytics constantly works in the background to learn more about your call centre, your agents, and your customers, providing deep, accurate insights that allow your call centre to deliver the performance customers expect.

Frequently Asked Questions

How Can AI Analytics Improve Customer Service?

AI analytics scours customer conversation and behavior data to provide actionable insights to call centre agents and teams, allowing them to learn more about what their customers want and how to address their needs.

AI analytics can tell call centres information like what phrases tend to increase sales, at what point in the buying journey customers drop off most, and which agents are most successful at preventing customer churn.

How Can AI Analytics Improve Call Centre Agent Performance?

AI analytics provides customer and performance data that shapes how agents interact with customers. For example, AI can analyze a customer conversation, identify areas in the conversation that lean negative, and suggest ways for the agent to improve the conversation’s trajectory.

Supervisors can also gather data about agent performance, like positive phrasing, call time, and overall helpfulness, to use for training and coaching.

How Do You Analyze Data in a Call Centre?

AI analytics software can help call centres analyze large volumes of data from customer conversations. The software uses multiple forms of AI technology, including conversation analytics and speech recognition, to provide a holistic view of performance from individual agents to the call centre as a whole.

This blog post has been re-published by kind permission of CallMiner – View the Original Article

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Call Centre Helper is not responsible for the content of these guest blog posts. The opinions expressed in this article are those of the author, and do not necessarily reflect those of Call Centre Helper.

Author: CallMiner