CX leaders have risen to the challenge and are now exploring how generative AI could be used to deliver more satisfying care. According to the same report, 70% of them plan to integrate it into many of their touchpoints in the coming years .
But before you get excited about the AI tools that are transforming customer service, you need to understand what data insights are.
Summary
Data analysis and interpretation are canada whatsapp number list key for companies looking to improve their processes and deliver greater customer satisfaction. In the context of CX, this information is valuable, as people expect interactions that feel increasingly human and familiar.
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What is data interpretation?
Data interpretation is the process that follows data analysis. It is what gives meaning to the information studied in a given context and allows it to be used to make decisions. In the business field, its objective is to relate the findings to the business context and draw conclusions and possible solutions.
Examples of data interpretation in customer service
Example 1: Reducing waiting times in a call center
A company performs data analysis of its call center to better understand the factors that influence customer satisfaction. After analyzing thousands of call records and satisfaction surveys, it discovers that the wait time before a customer receives service has a strong negative correlation with the customer satisfaction score.
Example 2: Improving the quality of service in live chat
An e-commerce company analyzes transcripts and satisfaction scores from its live chat service. Data interpretation shows that interactions that are resolved in less than ten minutes have a significantly higher customer satisfaction score than those that take longer.