There are many reasons why companies don’t succeed, but one important reason is not analyzing customer feedback correctly, and hence making bad decisions. How do you know what your customers like or dislike about your product or service? Isn’t it valuable data for you? Of course it is.
https://www.influencive.com/5-proven-growth-hacks-leverage-customer-feedback/
Most customer service professionals are familiar with the two most common customer service metrics: the Customer Satisfaction (CSAT) Score and the Net Promoter Score (NPS). NPS asks customers how likely they are to recommend a company to their friends or colleagues on a scale of 0 (not at all likely) to 10 (extremely likely), while CSAT typically asks customers to rate the quality of specific experiences, like a customer service chat or a store visit.
https://www.business2community.com/customer-experience/care-customer-effort-score-01840420/
Traditionally, customer satisfaction surveys have focused on collecting aggregate data. In the world of market research, this approach makes sense. It’s statistically accurate, high-level, and shows trending data—all great things for market researchers. But as customers have become more aware and their expectations have risen, this “open-loop” system falls short. Customers expect that if they take the time to provide personal feedback, then someone should take the time to provide personal follow-up.
https://www.peoplemetrics.com/blog/5-necessities-of-an-effective-closed-loop-customer-feedback-program/
Forbes.com says that bad customer service costs $338.5 billion globally each year. In the US alone, that’s about $83 billion, or an average of $289 per lost relationship.
Most companies today accept the fact that good customer service has a profound effect on reducing customer churn, and eventually the bottomline. Measuring customer satisfaction has become a key function in most Fortune 500 companies.
https://hiverhq.com/blog/measuring-customer-satisfaction/
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