Know thyself. Know the customer. INNOVATE. (Beth Comstock)
Traditional vs AI
Discovering how customers feel about a company’s brand or service is vital to ensuring customer satisfaction and the longevity of a business: after all, if customers are not pleased, they are not likely to return, and the business is unlikely to succeed.
Companies thus collect customer feedback in the form of surveys to determine their customers’ thoughts about the service they received. These surveys often make use of customer feedback scores to analyze the results and ascertain customer experience.
However, these metrics do not deliver the complete picture: they cannot determine pertinent factors such as customer emotions when answering the survey. They are also unable to analyze why customers gave a particular score during the survey, albeit without more context.
Using artificial intelligence (AI) within your customer experience program helps resolve these issues. It can help companies improve their feedback analysis and help deliver accurate and actionable customer insights.
How AI Delivers Customer Insights
Machine learning and Natural Language Processing (NLP) are the AI technologies used in analyzing customer feedback.
NLP is used to perform text analytics on customer reviews. It scans the text for words that customers use to express emotions such as joy, love, surprise, anger, sadness, and fear. It then gives an account of the overall sentiment by detecting the frequency of these words and their usage. The AI can then generate a report, classifying the feedback depending on the emotions expressed: positivity, neutrality, or negativity.
Machine learning analyzes large sets of customer feedback data and detects patterns. With these patterns, it predicts customer behaviors. This predictive analysis identifies the factors that cause specific customers to frequent the business or lead to customer churn. It is far more efficient than manual predictive methods.
The Benefits of AI in Customer Feedback Analysis
The application of AI to feedback analysis offers a wealth of benefits to businesses:
- Efficiency: Unlike manual methods, AI technology accurately and quickly examines large amounts of feedback data. Businesses can thus expend less time and human effort in customer feedback data collection and analytics.
- Determine customer emotions in real-time: NLP scans feedback data to determine how customers felt when answering a survey or giving a review. This analysis prevents customer emotions from being lost in the feedback data over time. NLP can also determine why customers give the scores they do: this provides more actionable customer feedback data.
- Predict customer behavior: Machine learning technology observes patterns various customers of a company exhibit when giving reviews or answering surveys and makes predictions based on these patterns.
- Improve customer experience: Companies can use customer insights obtained using AI to tailor their products and services to specific customers. Companies can also better determine customer pain points from AI analysis of feedback data and thus resolve the issues customers face during service delivery. This increases customer satisfaction and reduces customer churn, as customers receive the services and products they desire.
Conclusion
AI can offer ways to improve the customer experience via understanding the customer’s level of frustration, the need for escalation, and quicker resolution of problems. (Oded Agam)
AI is a powerful tool for businesses seeking to improve customer experience and thus guarantee customer satisfaction and customer loyalty. AI takes the hassle out of analyzing feedback and provides actionable data businesses need to drive the success of their brand.
