Conversation intelligence: definition and examples

What is conversation intelligence?

Conversation intelligence software allows businesses to analyse vast quantities of speech and text data from customer conversations using artificial intelligence (AI), creating insights to drive business action.

By utilising machine learning and natural language, conversational intelligence can pinpoint keywords and topics in your customer interactions to give a more detailed picture of your customer experience. Data pulled from call and chat transcripts can help you see what customers value and where they feel improvements can be made.

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What data can conversation intelligence analyse?

Conversation intelligence can be applied to vast swathes of data, but for customer experience, it’s best applied to:

• Customer calls data, such as sales call or customer service call recordings
• Chatbot transcripts
• Social media customer service transcripts

From these sources of data, conversation intelligence can provide you with:

• Transcriptions of calls
• The key themes and keywords present in these conversations
• Statistics on speech ratios, customer interactivity, and how long calls last
• Insights into customer sentiment
• Suggested actions to take

How is conversation intelligence different from call tracking software?

Call tracking software can provide analysis on the format of your calls: when they’re made, for how long, from whom and to which call centre. However, it can’t necessarily track why a customer has made contact, what they’re seeking to get out of the interaction or how they feel about your business. That’s where conversational intelligence comes in.

Why is conversation intelligence important?

There are several reasons why using conversation intelligence is important. We’ve outlined the most pertinent reasons below.

It improves conversions

Without insights into what your customers care about and what’s holding them back from making a purchase, you’re using guesswork to understand their motivations. Conversational intelligence allows you to derive meaningful insights into customer behaviour and how they respond to your marketing and sales efforts.

For example, how do customers respond to your cold calls? What do they bring up as the reason for turning down a sale? Which scripts worked, and which didn’t?

From a customer service perspective, what issue prevented them from being satisfied with a purchase (that could affect future purchases)? Were there customer journey problems that stopped customers from buying in the first place?

This type of data analysis gives you oversight into which areas of the customer journey need work and what the most common obstacles are for conversions, allowing you to take action to improve.

It enhances the customer experience

The best way to improve the customer experience is to get information about it in the customer’s voice. What do they care about? What do they contact you about the most? What appeals to them most in sales conversations?

Using the insights from the conversations you have with customers, you can improve the customer experience. Are your customers fed up with your payment process? Do they find your website confusing? Are they looking for more information before they make a purchase? Are they more likely to make a purchase after a conversation?

Armed with this information, you can make adjustments to your customer experience. Not only that, but by using conversational intelligence over time, you’ll be able to see how these changes make a difference.

It provides you with in-depth customer research

Conversation intelligence can act as a sophisticated research tool, using data from the most important source: your customers. How do they feel about your products? What aspects work, and which don’t?

Using a conversation intelligence platform allows you to pull overarching themes and drill down on specific sentiments about the products or services your customers mention in their conversations. This allows your revenue leaders to take action – either amending product or service lines or providing better information to avoid common issues.

It helps sales leaders

Businesses often analyse calls to judge their sales team’s efficacy. However, using human resources to understand what techniques are effective and which agents are performing well means you can only cover a small portion of the thousands of conversations businesses have with their customers.

Rather than analysing a snapshot of calls and chats that might not be truly representative of customer views and agent performance, conversational intelligence allows you to analyse every interaction and pull accurate insights from all the data available.

This helps your sales leaders to see what issues they’ll need to tackle most, and which scripts work best. This in turn improves their sales coaching and their team’s performance and streamlines the customer experience.

It increases customer loyalty and customer retention

When customers feel they’ve been heard, they are more likely to engage with your business. In our Global Consumer Trends 2022 report, we found that:

• Two-thirds of consumers think that companies need to be better at listening to feedback
• Over 60% of consumers believe businesses need to care more about them – and that they’d buy more if they felt cared for

It’s clear that businesses who demonstrate that they hear customers’ concerns and listen to their feedback will come out on top. By investing in conversation intelligence software, you can gather not only the feedback customers give you directly through surveys, but what they’re saying indirectly to you in the conversations they have with your teams.

By taking action on what matters, you can improve customer loyalty and retention.

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What can the best conversation intelligence platforms do?

There are several options for conversation intelligence platforms out there, but not all of them have the same capabilities. When searching for a tool, you’ll need to look out for the following features:

• Can it analyse customer emotion, intent, and effort?
• Can it identify opportunities for upselling or flag product issues?
• Can it provide deeper detail for customer profiles based on their conversations with your brand?
• Can it provide industry-specific insights?
• Can it automate workflows to ensure your teams get the insights they need and know what actions they need to take?

How to use conversation intelligence to enhance the customer experience and increase ROI

So how do you go about using conversation intelligence software to enhance your customer experience and improve your bottom line?

Below are a few use cases to help you see the benefit of using this type of software.

Find nuanced feedback and solve product issues

Sometimes, it’s hard for businesses to figure out the scale of a problem. With call centres all over the globe and many teams working remotely with each other, it’s easy for data to get lost and large-scale themes to be missed. Using conversation AI to analyse all the data you can gather on what customers say means you can find out what’s going wrong and the scale of the problem to fix.

For example, if your customer service call centre logs an issue in a generic way – “customer said product X was too hard to use” – this means you’re not getting to the nitty-gritty of what the problem is. You know there’s an issue, but you’re not sure how to go about fixing it with such a generic designation.

You also might find that customers are feeding back on this problem, but as it’s not the main focus of their customer service call, the issue isn’t flagged on the scale it’s being experienced. They’re telling you they want a refund, but in passing mention that it’s because they found the setup too difficult.

Combine this with fragmented data from different call centres, and you might find:

• You don’t see the scale of the issue because of siloed data
• You’re not seeing the scale of the problem because it’s mentioned in passing in conversations
• You’re missing out on the nuanced detail of the problem because your call reps can only flag issues in a generic way

By analysing conversations, you can see which problems are at the core of customer dissatisfaction. You can transform generic insights from “it’s too hard to use” into “product X’s instructions aren’t clear enough for customers to use this product effectively”. The issue isn’t the product – it’s the explanation of how to use the product that causes customer headaches.

Finding this nuance means you can then set your production team to solving the actual problems that affect customers, improving customer experience in the present, and preventing issues in the future.

Get the full scope of customer feedback

Your customers might already be giving you feedback on their experiences via surveys such as Net Promoter Score (NPS) or customer effort (CES). However, this relies on customers being motivated enough to provide direct feedback, meaning you might be missing out on a large proportion of experience data.

By analysing phone calls, chat logs, and more, you can see the full scope of customer feedback, both from what they give you directly and what they’re saying indirectly in conversations. You can analyse conversations for intent, effort, and emotion, meaning you’re able to get a deeper understanding of what drives your customers and take action to overcome objections in the future.

See how your sales team is performing

How can you distinguish your top-performing reps without putting an extra burden on your sales leaders? Using conversational AI, you can analyse the discussions your reps are having with customers for their efficacy in making a sale. This type of analysis can uncover which scripts help with building rapport, and what conversation styles drive more deals. This in turn means sales managers can train new reps more effectively and create best practices for your team going forward.