Top ten benefits of sentiment analysis

Sentiment analysis is the new kid on the live chat block. Only now are brands beginning to understand the benefits of sentiment analysis wrapped within their chat channels. This new technology detects the emotional tone behind text, offering key insights into customer satisfaction.

Sentiment analysis is powered by smart language algorithms. In a nutshell, it works by identifying and quantifying the positive and negative feelings within our words.

This kind of subtle wordplay can often be lost within the flow of a busy live chat service. Agents are trying their hardest to respond quickly and accurately, and deeper analysis is difficult.

So, when used to support your chatting customers, sentiment analysis provides insight into the real mood behind the messages. This sounds cool, but is it useful? Here’s a handy list outlining some of the top benefits of sentiment analysis in live chat software.

1.    Upselling opportunities

Happy customers are more likely to be receptive to upselling. With sentiment analysis, you can easily identify your happiest customers.

This helps you recognise chatters who might be receptive to spending more, as well as avoiding upsetting disgruntled customers with any unwelcome sales pitches.

2.    Agent monitoring

You no doubt monitor agent efficiency. But how do you monitor agent empathy? Or emotional intelligence? In terms of your operations, one of the most helpful benefits of sentiment analysis is its utility as a performance measurement tool.

Sentiment analysis gives you a clear overview of customer satisfaction, agent by agent. This means you can keep an eye on the quality of service each team member is offering customers, as well as their more subtle ability to create happy customers.

Sentiment analysis calculates agent satsifaction scores

3.    Training chatbots

The benefits of sentiment analysis go beyond helping your human agents. If you have a chatbot on your site, it can benefit from sentiment analysis too. That’s because it can train your chatbot to recognise, and respond to, customer mood.

💡 Sentiment analysis could detect when a chat needs escalating to a human agent, or route an engaged prospect through to a sales team. Click To Tweet

4.    Identifying key emotional triggers

Emotional triggers drive our decisions. Using sentiment analysis, you can identify what messages and conversations act as emotive triggers that change customer mood.

Perhaps the phrase “Please wait”, for example, often triggers customer annoyance. Or perhaps using emojis has a positive effect on the conversation’s overall tone.

Understanding what messages trigger certain emotions in your customers can help you give better service, and is also useful for creating effective marketing materials.

5.    Handling multiple customers

In a chat session, agents can find themselves handling more than one customer at a time. Keeping track of how each customer is feeling can be a challenge – particularly at busy times.

So, another of the benefits of sentiment analysis is its ability to provide a helping hand during peak chat volumes. At a glance, you can see which chats are going smoothly, and which need further attention.

💡 For busy contact centres, sentiment analysis reduces the risk of reading the (chat)room wrong. Click To Tweet

6.    Adaptive customer service

Your human agents are great at providing flexible service, but it can be difficult to identify the best approach for each customer. With sentiment analysis, it’s easier for your team to adapt their service to the mood of the customer early on.

Empathetic service makes for a great experience. (See also: empathy statements.)

7.    Live insights

Customer mood can change at any point during a customer service interaction, and this isn’t always clear.

With sentiment analysis, not only can your agents see the mood of each customer in a session, visual indicators display how this mood changes in real-time. Your agents get a live insight into how well a chat is going, and the ongoing mood of even the flightiest customers.

Real-time indicators help gauge the chat mood at a glance

8.    Quick escalations

For your management team, another of the top benefits of sentiment analysis is the speedy escalation system it provides. Potential issues are nipped in the bud.

With sentiment analysis, chats with irritated customers can be quickly identified and escalated – either into bespoke support tickets or through to higher-level support representatives. This ensures that even the grumpiest of customers get satisfying service.

9.    Reduce customer churn

The benefits of sentiment analysis extend into your bottom line. With sentiment analysis, you can identify a dissatisfied customer as and when they’re chatting with your team.

This enables your agents to offer a smooth service and quick resolution to appease, and ultimately retain, the customer.

10.  Tracking overall customer satisfaction

Sentiment analysis scoring puts a quantifiable number on customer satisfaction.

It enables you to see the impressions and moods of customers when they approach you, before they get support, and how effective your service is at increasing satisfaction.

In other words, you get the bigger picture, rather than just a case-by-case view.

Bonus: Detect changes in customer opinion

There are many more benefits of sentiment analysis, but we’ll throw in just one more bonus here.

Sentiment analysis also means you’ll be able to detect changes in the overall opinion towards your brand.

Because it provides insight into the way your customers are feeling when they approach you, you can monitor trends and see if overall opinion towards your company drops or rises. You can then use this insight to keep your brand appreciation on track.

💡 Use sentiment analysis to track changes in how customers feel about your brand over time. Click To Tweet

Benefits of sentiment analysis

Sentiment analysis has a lot to offer. When combined with your live chat channel, it helps you give smarter support than ever.

The benefits of sentiment analysis spread from more empathetic service for each customer, to better chatbots, to an insight to the overall performance of both your support team and your brand.

And the best of it is: it’s grounded in algorithmic logic, not guesswork.