What are the most effective ways to measure and analyze customer emotions?

1 Emotion detection methods

When it comes to detecting customer emotions, there are various methods that can be used depending on the type and source of data available. Text analysis, for example, uses natural language processing (NLP) and sentiment analysis to extract emotional cues from written feedback, like reviews or social media posts. Tools like IBM Watson or Google Cloud Natural Language can then be used to score different emotions, such as joy, anger, or sadness. Voice analysis is another method that uses speech recognition and emotion recognition to extract emotional cues from spoken feedback. With tools like Beyond Verbal or Affectiva, you can get scores for emotions such as calmness, frustration, or excitement. Finally, facial analysis uses computer vision and facial expression recognition to extract emotional cues from visual feedback. Tools like Kairos or Microsoft Face API can be used to score different emotions such as happiness, surprise, or disgust.

2 Emotion measurement metrics

Once you have detected customer emotions, you need to measure them using metrics that can help you compare and evaluate them. A popular metric is the Net Emotion Score (NES), which is similar to the Net Promoter Score (NPS). You can use a scale from -5 (very negative) to +5 (very positive) and calculate the percentage of positive emotions minus the percentage of negative emotions. The Emotion Value Index (EVI) assigns weights to different emotions, such as joy, anger, or sadness, and calculates the average weighted score of your customer emotions. Lastly, the Emotion Map is a visual representation of your customer emotions, based on two dimensions: valence (how positive or negative the emotion is) and arousal (how intense or calm the emotion is). You can plot your customer emotions on a grid, such as the one proposed by Russell (1980), and identify clusters, patterns, and outliers.

3 Emotion analysis techniques

Once you have measured customer emotions, you need to analyze them using certain techniques to better comprehend and act on them. Emotion segmentation groups customers based on their dominant or prevalent emotions, such as happy, angry, or sad. This allows you to tailor communication, offers, and experiences to different customer segments. Emotion journey mapping maps customer emotions along their journey with your brand from awareness to retention. You can use this technique to identify the touchpoints, moments, and factors that influence your customer emotions. Lastly, emotion feedback loop involves collecting and responding to customer emotions in real time or as close as possible. This helps monitor customer emotions and create positive emotional connections with them.

Analyzing customer emotions is a powerful source of insight and innovation for your business. By using the methods, metrics, and techniques discussed here, you can measure and analyze them effectively and use them to improve your business innovation.

4 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?