Empathy analysis using artificial intelligence (AI) has the ability to determine how well a conversation is going on a phone call. By combining different metrics to create an accurate picture, empathy analysis can revolutionise communications as we know it, boosting productivity, improving customer experiences, and even helping mental health within organisations of all sizes.
Empathy analysis, which is also known as sentiment analysis, can be a strong indicator of the effectiveness of company representatives. If used well, it can lead to better processes, enhanced training, more effective interactions and improved outcomes.
Words used
Empathy statements are the number one tool in a representative’s tool box. Handling angry or dissatisfied customers involves taking on their perspectives and communicating understanding and empathy. Here are examples of the words used in empathy statements that will score well when calls are analysed:
- I understand your frustration…
- I get why this is a problem for you…
- If I were you, I’d be unhappy too
- Thank you for contacting us about this issue. We need to resolve it
The pitch of the voices
Pitch refers to the highness or lowness of voice and there are stereotypes associated with them. Pitch expresses the emotional state of the speaker. For example, a high pitch voice is considered tense and nervous, whereas a low pitch is associated with strength, maturity, and calmness. If company representatives can keep the pitch of their voice low without becoming a monotone, they are likely to earn a customer’s trust faster.
The tone of the voices
To communicate effectively, one’s tone of voice is extremely important. The words can be exactly the same but it’s how you say them that will ensure what you mean is interpreted correctly by the listener. As a representative fielding calls from customers, prospects, partners, and others, it’s important that they use a welcoming tone that is friendly, pleasant and respectful.
The cadence of the conversation
Getting the speed of an exchange right is another important aspect of a phone conversation. Cadence is the flow or the rhythm of your speaking pattern. You want to avoid becoming sing-songy or unnatural. To do that you need to focus on your words and emphasise the important ones. Faster, slower, pause – all create variety and keep listeners engaged.
Cross Connects’ latest version features sentiment analysis
TSI have introduced enhanced Call Transcription and Sentiment Analysis in Cross Connect. This tool automatically parses call recordings by user, transcribes them, and then separates the text by speaker for a visual representation of the conversation.
This feature offers added value to customers who want a transcription of recorded phone calls. It provides an historical assessment on the context of a call and assists in determining if a customer was handled properly and professionally.
Call transcription converts the spoken word into text, which is then matched against a comprehensive list of similarly ranked text words in English, with AI providing a brief summary of the entire call.
Sentiment analysis adds another, more sophisticated review. The methodology is based on additional algorithms where other information beyond just the spoken word translated to text is analysed by DeepGram, which uses enhanced artificial intelligence and adds more variables to better analyse and provide more accuracy to the context of the conversation.
Call History can be filtered by the required % of positive, neutral or negative sentiments of a call, and also by the closing sentiment of the call, with the top three topics of the call displayed.
TSI brings this premium feature to every customer at a very low cost per minute of recording. Call transcription is included with the sentiment analysis cost.
The promise of empathy analysis is significant with lots of compelling use cases. It should be able to help improve sales cycles, improve customer support and user experience, and provide great productivity gains as organisations optimise their processes based on it.