Using text analytics to build stronger, more empathetic connections with customers
When someone has a positive experience with your company — particularly, an interaction that makes them feel understood and respected — they're more likely to become or remain a customer and encourage others to become customers. Acting with empathy can increase sales, loyalty, and referrals, yet some companies don't keep a pulse on how well they treat customers and prospects.
Consumer activities like online reviews, customer service emails, chatbot conversations, and survey comments can be the key to unlocking the secrets of what drives consumer sentiment, emotional responses, and loyalty. The right tools can take this unstructured data and turn it into the information needed to improve customer interactions.
Text analytics technology meets psychology
The Bellomy Text Analytics tool is designed to shape how businesses interact with consumers. Pinpointing ways in which businesses can increase the empathy shown towards customers starts with understanding consumers' perceptions of those interactions. Using an ensemble of analytic techniques, our proprietary tool helps companies turn unstructured data into actionable insights by untangling the intricacies of sentiment and emotion.
Sentiment classification model
Text analytics can standardize emotions and identify intensity, allowing its users to uncover the underlying sentiments that drive those written or verbal survey responses. Our advanced sentiment classification model delivers higher-than-industry-standard accuracy for identifying sentiment.
Unstructured data is complex and so are the tools used to analyze it. Make sure you’re not falling for one of these five common text analytics misconceptions — but here's what to do about it if you are.
Emotional expression classification model
Sentiment classification is just the foundation for a more sophisticated approach to emotion: We built an emotional expression model that detects nuanced emotional expressions buried in consumer text. Utilizing Plutchik's Wheel of Emotions as the basis for emotional modeling, our advanced emotional expression classification model enables a deeper understanding of consumers' emotions.
Emotional expressions are often significant drivers of loyalty and future sales. A more nuanced understanding of emotion is critical to fine-tuning business workflows and practices that improve interactions between employees and consumers.
Employee soft skills identification model
Employee interactions with customers are among the most crucial touchpoints to building loyalty, repeat business, referrals, and increased revenues. An employee soft skills model enables rapid identification of encounters between consumers and employees that need review. This model provides more details about impactful interactions, like how they impact NPS or how they measure against KPIs, and lets you use findings to coach and train employees to build business-critical skills and practice emotional intelligence.
Content actionability model
When consumers make cries for help, identify safety concerns, or mention legal matters, businesses must take action to recover the customer relationship, re-establish safe operations, or head-off legal struggles. Our content actionability model identifies these scenarios without the need for custom-built topic models or complex searches. Quick resolution of customer issues keeps sentiment high and service costs low — a valuable outcome for companies and consumers alike.
Use text analytics to get in tune with your customers
With the custom text analytics model we have developed, you will uncover what customers are saying and be able to use that information to take meaningful action. Bellomy's Text Analytics tool is just one step in building a more empathetic and customer-centric organization.
Reach out to see how our tool can help you examine consumers' verbatims and transform them into insights that can help your business learn, change, and grow.
- text analytics