How Emotions Analytics Will Change the Way You Engage With Your Customers

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Customer data gives you a clearer picture of your audience. Just knowing the basic demographics of your customers helps you identify the right channels to target and refine your messaging.

While information like age and income levels are useful, they don’t exactly tell you how customers feel about your products or services. Nor do they provide insights on what led to their purchasing decision in the first place.

What if there’s a way you can dig deeper and uncover your customers’ emotional state as they engage with your brand? You’d be able to deliver better customer experiences.

This is where emotions analytics comes in — a relatively new field that promises more insight into how your customers think and feel.

Here we’ll look at the definition of emotions analytics, how it works, and how it will change how you engage with customers.

What is Emotions Analytics?

Emotions analytics involves analyzing customers’ verbal and nonverbal communications to understand their moods. The idea is to gain insight into how a customer feels about a product or service. Emotions analytics is invaluable, as you can use it to deliver better experiences.

In a study by StuDocu on the impact of COVID-19 on students’ mental health, feelings of stress, anxiety, and loneliness were more prevalent amongst respondents.

Data like this, which can be collected through emotions analytics, helps companies understand what their target customers need and how to approach them. These businesses can then adapt their marketing to match the emotions their audience is feeling.

How Emotions Analytics Works

Customer satisfaction surveys are often issued to gauge how satisfied customers were with an interaction. A low score is a cause of concern, but it doesn’t tell you what customers were unhappy with (unless they mention it).

Emotions analytics goes a step further by detecting emotional undertones in real-time. Here are methods that companies use to gather emotional data.

Sentiment Analysis

Sentiment analysis involves analyzing text and using machine learning to detect certain emotions. It can be applied to the text found on customer reviews and even social media posts.

By performing a sentiment analysis on what customers are writing about your business, you can detect negative undertones (e.g., “The program wasn’t working for me”) and follow up with an appropriate response.

Speech Analysis

In addition to text, you can infer a person’s emotional state from their voice. If someone on the other end raises their voice, you can deduce that the person isn’t happy about something. You can then change your tone of voice or route the customer to the customer retention team.

More call centers are now using voice-analysis software to help support agents understand how customers are feeling and respond appropriately.

Facial Analysis

Facial analysis uses facial recognition technology that can capture faces and categorize expressions as sadness, fear, anger, happiness, surprise, or disgust.

By analyzing facial expressions, companies can gain more insight into how customers feel at a particular moment. If a customer expresses “disgust” after taking the first bite of a meal, we can reasonably infer they didn’t enjoy it.

Increasing Customer Engagement With Emotions Analytics

Emotions analytics helps you understand what your customers are thinking and feeling about your brand. Here’s how you can use this data across your business to increase customer engagement and drive more sales.

Optimize Marketing Campaigns

The most common application for emotions analytics is in marketing. Measuring engagement levels can tell you if you’re on the right track.

Kellogg’s showed different versions of a commercial for its Crunchy Nut cereal to viewers and captured their expressions using facial recognition software. The software revealed that a version featuring an alien (over various animals) had higher engagement rates.

Based on these insights, Kellogg’s decided to roll out these ads, which reportedly increased sales of its new cereal. This is just one example of how companies are turning to emotions analytics to make marketing decisions.

Another example comes from PandaDoc. Instead of pushing its products to potential customers and making them angry, the company publishes helpful blog posts, like this one on DocuSign alternatives, in which they offer different solutions.

Deliver Better Customer Service

Customer service plays a crucial role in any business. By prioritizing your customers and exceeding their expectations, you can generate repeat sales and even drive referrals.

Emotions analytics can be a complete game-changer for how you engage with customers. One example is using software that analyzes a customer’s voice when they phone support to determine their mood.

Cogito offers AI intelligence software that can analyze phone calls in real-time and understand how customers are feeling. The software can even provide support agents with suggestions based on this data (e.g., change speaking tones, show more empathy, etc.).

The software provided by Cogito has helped Humana, a health insurance company, greatly improve its Net Promoter Score (NPS) — the percentage of customers who say they’re likely to recommend a product or service to a friend.

When an agent is tuned into how a customer is feeling, they can take appropriate steps to show that they understand. For example, a support agent may change their tone when speaking with a frustrated customer or even escalate the call to a manager.

Make Product Improvements

It’s easier than ever for consumers to voice their opinions. They can turn to review sites like Capterra for software, Yelp for restaurants, Amazon for products, and social media to voice general opinions.

But having to read through all these reviews isn’t exactly practical. Instead, you can use a text analysis tool that identifies emotional undertones like positive or negative reactions. This can provide insights that you can use to make product improvements.

If customers are complaining about a certain feature (or lack of), you can route those tickets to your project management pipeline for the team to address in a timely manner.

Improve the Website User Experience

Another use case for emotions analytics is improving your website’s user experience. If visitors can’t easily navigate your site or can’t find what they’re looking for, they’ll feel frustrated and bounce at a higher rate.

With a tool like Semrush, you can analyze what your customers are doing on your site and keep track of metrics like visit duration and bounce rate. If the tool shows that your site has a high bounce rate, it’s important that you take steps to keep visitors on the page.

Important Considerations of Emotions Analytics

Emotions analytics offers a number of tangible benefits. The insights you gain from understanding the emotional state of your customers can help you improve your marketing, deliver better customer experiences, and revamp your products.

But when handling any sensitive data about your customers, it’s important that you have a data center infrastructure that complies with privacy standards in place. This will ensure that your organization isn’t violating any privacy laws.

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