Emotions play a significant role in our daily lives and the decisions we make. Emotion recognition helps businesses understand the moods and behaviors of a customer using their verbal and non-verbal cues.
The customer agent evaluates the client’s experience using his/her emotions, and this helps the business pinpoint the weak areas to improve on. This process is also known as emotion detection or analysis and has proven to be effective in many business-customer support systems.
A customer’s emotions towards a company’s product or customer service test their loyalty or if they will churn. This is why many companies are embracing emotion detection as a way to improve CX.
How Does Emotion Detection Work?
It works by measuring and evaluating a consumer’s feedback using artificial intelligence. The technology works by detecting and analyzing all the details and data without requesting the customer to share any further comments about his/her issue.
There are three types of emotion detection, namely text or sentimental analysis, facial analysis, and speech analysis
Script/Text or sentimental analysis.
Script analysis is the process of defining whether a piece of writing is neutral, positive, or negative. It also allows businesses to identify shopper’s sentiment towards products and services offered. In other words; it is the voice of the customer.
Sentiment or script analysis enables you to understand your customer. That way you not get to target the right demographic, but it monitor the tone of the conversation. For example, you can increase product quality by gauging what the client needs and meeting their preferences.
You can use targeted customers to get ideas for product improvement. This helps to identify opportunities for up-selling, reducing customer churn, acquiring more clientele, and retaining the many acquired customers.
Through sentiment analysis, one can locate vital emotional triggers of a customer. Some keywords may change customers’ moods and perspectives towards certain products.
Text analysis may also play a significant role in identifying new business opportunities. Some phrases and texts from specific customers, when taken into consideration, can develop new leads allowing a business to compete favourably in a cut-throat market.
Other times, it acts as the backbone of a marketing campaign. And the data used to track the success of the initiative relies on the comments of the targeted market because the text analysis will ensure the numbers make sense.
It is the process of analyzing voice recording of the consumers or customers to find useful data using voice emotion recognition software.
Speech analysis enhances consumer fulfilment: it improves how shoppers, as well as other would-be buyers perceive your products and services. It can help one to tell what their clients want directly.
To the business, speech analysis plays the significant role of reshaping a company image, thus positively impacting people’s perspective towards the company.
Speech analysis also helps in reducing risk and liabilities exposing the company to fewer risks.
Just like the name suggests, facial analysis detects and analyzes a shopper’s facial expression via a photo or a video. It uses facial expressions such as a broad smile or grins or frown to gain insights.
This type of emotion recognition can be used by security personnel to detect danger during social events or by teachers to spot struggling students.
In business, this technology can help to understand better and mine valuable clues from a client’s facial cues e.g., during a video call. The ability to recognize simple facial movements such as a raised eyebrow can be used to decipher how a customer feels during a support experience.
Also, a customer who shows authentic facial features when praising the support agent may be classified as a good customer, and this can be used as leverage for future promotional opportunities.
How is Emotion Recognition Used in Customer Support?
Let’s look at some of the way customer support team can use emotion detection technology:
Being in tune with the customer’s emotions helps agents to personalize the conversation. Dealing with each consumer at a personal level is a show of empathy, and a way to boost customer experience.
For instance, emotion detection can identify when a customer is not happy. In response, an agent can decide how to choose their words carefully by being warm at the beginning of the conversation.
Additionally, if the customer frustrated, he should be treated differently with a happy customer.
You can route calls based on client emotion.
The data gathered from a customer’s voice, for example, tone and mood can be used to classify a call.
An example is when talking to an angry client, that call is routed to the retention team. While a happy or satisfied customer, is routed to a sales to where he is pitched a new product.
Tracking reactions with time.
Emotion recognition software offers data that can help to provide information about customer interaction.
For example, call centres can use that data to tweak their procedures, especially when emotion analytics recognizes a friendly introduction that, in most cases, is seen as annoying or intrusive.
Delivering business-level analytics.
When it comes to decision making, businesses benefit from emotion analytics. These insights help them understand the effect of their products or services on client emotion.
For instance, a cologne company can use emotion analytic to tweak their formulas based on how the customers react to a particular boy sprays.
What is the limitation of Emotion Recognition Software?
While boasting several positive effects on customer experience, emotion detection software is not without limitations. Emotion detection analytics causes numerous privacy and security issues.
First of all, is a customer okay with having their emotions analyzed ? Do we need consent to track client emotions?
Well, it will take a while to choose the right channels to define the best data to capture the information needed to enhance the customer experience. But the search is not for granted.
When it comes to improving customer experience, the ability to read a customer’s emotions has tremendous positive impacts.
The introduction of emotion recognition software has enabled computers to detect and interpret shopper emotions simultaneously, thereby creating extraordinary possibilities for a customer service team.
Emotion detection technology is enabling companies to connect with their customers on an emotional level, thus ensuring they truthfully have the shopper’s welfare at heart.