Learn how conversational analytics can help businesses understand their customer base, gather valuable insights, and improve overall customer experience through AI-powered machine learning.

Conversational analytics is a trending form of market research that helps businesses gather granular insights about their customers’ behavior, motivations, and desired outcomes.

But what exactly is it and can it have a positive impact on how businesses make decisions moving forward? Read on to find out and learn:

• What conversational analytics is and how it works.
• Its benefits and why it’s important.
• Real examples of use cases for conversational analytics.

Let’s switch on our AI machines and dive in.

What Are Conversational Analytics?

The term is a mouthful but the concept is straightforward. Conversational analytics is about evaluating customer conversations through the use of AI and deriving actionable data in the process.

Customer interactions by telephone, chats, reviews and even social media mentions can be used to gather nuanced insights about your customer base that would otherwise be difficult or impossible to obtain.

How It Works

Conversational analytics uses artificial intelligence (AI) and machine learning to do natural language processing (NLP), which basically means getting computers to understand and make sense of speech like humans do.

The technology behind conversational analytics can be applied to do live transcribing and analysis of phone calls, chats, reviews, and other areas of written or verbal interaction to get insights into how your customers react with and perceive your brand.

Why It’s Important

Similar to how companies continuously evaluate their customer service, conversational analytics allows businesses to learn from customer interactions and answer complex questions such as:

• What trends can be seen in customer behavior, motivations, and interactions?
• What are the desired outcomes customers look for when interacting with sales reps and customer service agents?
• What topics and questions get frequently brought up by customers?
• What are the common trends from customers towards pricing, promotions, and products?
• How can the customer experience be improved in meaningful ways?

By analyzing customer conversations, you can identify patterns in the buyer’s journey and make informed decisions with data-backed feedback.

Main Benefits of Conversational Analytics

From driving sales to improving your product, here are the main ways companies can benefit from conversational analytics.

Boost Sales and Conversion Rates

Sales teams that operate by phone constantly review and assess their calls. But with the help of AI, calls can be analyzed in real-time to identify certain patterns across conversations.

For example, if certain points frequently come up in conversations, conversational analytics software can inform sales teams about these patterns and help them better prepare and improve.

Examples of such patterns are:

• Most frequent pain points mentioned.
• Competitor mentions from customers.
• Most common objections.
• Product features most asked about.

And so on. The more actionable insights you have, the easier it is to improve your sales process and address customer concerns in ways that drive sales.

Get Nuanced Insights Into the Customer Experience

By analyzing customer speech and text interactions with AI-powered machine learning, companies can get an understanding of the customer experience and how it can be improved.

Analytics tools give businesses a competitive advantage and help them understand:

• Customer sentiment and how it changes throughout the buyer’s journey.
• What triggers customer frustrations.
• Types of customer pain points.
• Patterns in customer interactions and behavior over text and phone.
• Differences between over-the-phone and digital customer experiences.

This wealth of data helps point businesses in the right direction to easily make informed decisions on what channels to focus on and what needs tweaking.

Reduce Customer Burden and Churn Rates

Conversational analytics lets you gain customer feedback without asking for it through surveys or questionnaires. This helps lessen interruptions in the buyer’s journey for an overall smoother process.

When addressing churn rates (the rate at which customers no longer want to do business with a brand), companies can analyze and look for patterns in the events that eventually led to a customer leaving.

If there is a common trend, companies can easily identify and potentially resolve the issues that lead to churn rates.

Improve Your Brand and Quality Control

Customer service and quality control often go hand in hand. But with conversational analytics, you can quickly spot what customer frustrations and pain points arise from all channels of interaction and act accordingly.

For example, keyword terms and phrases such as: “I wish there was an XYZ feature,” or “You should add a so and so button,” can be automatically tagged and noted for product design and development.

Conversational Analytics Use Cases

Any industry with customer interaction can benefit from conversational analytics. From healthcare to retail to customer service, AI-powered algorithms can help extract valuable data at scale.

JetBlue Case Study

Popular airline company JetBlue uses multiple AI integrations to streamline its operations, including conversational analytics. Across JetBlue contact centers, customer sentiment was analyzed to create a list of pop-up scripts and instructions based on customer inquiries.

In another instance, when running a promotional campaign that included free baggage, conversational analytics helped pick up that the vast majority of passengers did not consider this offer reason enough to fly with JetBlue. As a result, JetBlue readjusted its promotional offer to one that was much better received by customers.

While these changes may seem small, they result in a significant overall impact on the customer experience and sales processes. It’s these simple tweaks that can make all the difference for a company and put it far ahead of competition.

Key Takeaways 

Conversational analytics helps teams and businesses leverage customer communication in new ways to gain valuable insights. Any industry with regular customer interactions can use AI to make data-backed decisions to improve how customers interact with brands.

The key highlights of conversational analytics are:

• You can directly gain insights into your customer base.
• Sales and marketing teams can use conversational analytics to quickly and easily spot recurring patterns and the reasons behind them in customer interactions.
• Conversational analytics gives actionable data on which areas businesses can improve or need tweaking across several areas.
• Businesses can easily make high-impact, data-backed decisions with the help of AI-powered analytics.

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