Contact Centers have become, in terms of customer experience, what Forrester calls “The Age of Customer.”
If we look at the statistics, the share of customers in the United States who contacted customer service for any reason from 2015 to 2020 things have significantly changed.
Source: Statista 2022
For results to be visible in the Customer Age, organizations need to improve their approach to customer experience. And where does this journey best begin, if not from a contact center?
If we were to say what is the recipe for the success of an uplifting experience for a client, we could summarize it in two things: understanding and capitalizing on the emotions from the interactions with the clients.
It is easy to understand that emotion is a decisive factor in developing a strong, lasting, and sustainable relationship with the organization’s clients.
Emotional Connections
The whole context of the last few years has created a huge urgency to offer an exceptional Customer Experience (CX). The good part about this is that organizations are starting to invest in talent and technology.
The reality is that companies around the globe are losing billions a year because of avoidable consumer change. Future-oriented organizations are investing aggressively to turn this risk into competitive gain.
In addition to investing in human talent and technology, organizations implement Speech Analytics and Artificial Intelligence solutions in contact centers, thus valuing feelings to help understand and analyze emotions.
In a nutshell, emotion analysis is the process of understanding a customer’s feelings when it comes to the products, promotions, brand, or interaction they have with an organization. The result of the process is a thorough and personal look at the true voice of the client.
Emotion analysis is based on speech analysis technology. And it allows companies to evaluate the language used, the tone, and the tempo in customer interactions.
Benefits of Emotions Analysis
As we said, Emotion Analysis is based on the principles of Speech Analytics, and, like this solution, Emotion Analysis brings several benefits, such as:
- Emotional Accuracy – The use of conversational data will bring industry-leading accuracy;
- Richer Insight – Obtaining a detailed understanding of what the client is feeling, evaluating everything through a spectrum of emotions – positive, negative feelings;
- Context Empowered – Conversational behaviors take into account the meaning of understanding the causes that trigger “moments of truth.”
12 key emotions to know for creating an uplifting Customer Experience
First, to determine how emotions, influence a client’s decision, it is necessary to understand whether emotion helps or confuses customer loyalty.
The 12 emotions listed below were divided into four categories, as follows:
#1 Category - Loyalty
Emotions: Happiness and Satisfaction
These are the pinnacle of customer experience. A positive experience comes from the best products and quick fixes, hence satisfaction and loyalty.
#2 Category - Interest
Emotions: Excitement and Surprise
Excitement, surprise have a direct impact on short-term spending. How? An offer can meet or even exceed the needs and expectations of customers. Once you get the attention, you can intervene in solving the need.
#3 Category - Negative Interest
Emotions: Fear, Guilt, Shame
These emotions harm short-term spending. How? For example, the introduction of a new procedure or a new feature without being supported by explanations.
#4 - Destructive
Emotions: Anger, Irate, Contempt, Disappointment, and Disgust
This is a “no-no” category, but if so, you should notice these emotions as soon as possible and try to combat them, and then avoid them.
Emotion Analysis - How does it work?
Conversation analysis tools that analyze emotions provide objective solutions to interaction data without requiring any customer intervention.
Post-call surveys are often ignored by clients, but the detection of emotions through AI. Detection and analysis of emotions are done by the following methods:
Sentiment Analysis in text
Email or chat interactions, voice calls, and metadata are converted to data-rich text formats, then sentimental expressions are searched.
Speech Analysis
The client’s call is analyzed for emotional cues. In addition to the analysis mentioned in the step above, speech analysis examines elements such as tone, voice, percentage of silent times, etc.
Emotions Categories
The solutions offered by conversation intelligence platforms offer categories of 15-20 emotions.
Emotional Classification
AI solutions take on the heaviest task, combining keyword sentiments with speech analysis data, and creating an index score.
Getting Actionable Insights from Emotion Analysis
Emotion Analysis is done through Artificial Intelligence and machine learning, these tools give you valuable information not only about what customers say but how they say it. Here are the actionable insights you can get if you implement such a solution:
- Improving the outcome through historical analysis,
- Prevents customer churn,
- Capitalize on the customer’s voice,
- Delivers in real-time the possibility of intervention.
The Bottom Line
In conclusion, in this age of focusing on the client and the experience offered to him, only those who act emotionally intelligently can survive.
Interestingly, organizations have begun to allocate time and financial resources to create customer-focused strategies.
Customers expect that their brand understands their needs, challenges, and feelings. An emotional connection has become a standard in the world of customer service.
The solutions offered by RepsMate are meant to bring you actionable insights to offer a quality experience to your customers.
