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How AI can Help You Track Real-time Customer Insights
The most frequent approaches for tracking client feelings have a major flaw: they miss significant emotional responses. As a result, qualitative surveys such as the Net Promoter Score lose key information.
Fremont, CA: Customers often express their genuine feelings and opinions in the open-ended comment boxes seen at the end of surveys. AI can help firms forecast customer behavior better by utilizing this valuable data. There are six specific advantages of using AI to examine this feedback: It can
1) show you what's missing in your qualitative surveys
2) assist you in training your employees based on what customers care about
3) identify root causes of problems
4) capture customer responses in real-time
5) detect and prevent sales declines
6) prioritize actions to improve customer experience.
Companies must comprehend what their clients are thinking and experiencing to flourish. As a result, companies invest a significant amount of time and money in gaining a deeper understanding of their clients. However, despite this considerable expenditure, most businesses are not particularly effective at listening to their customers. It's not for lack of trying; the tools they're employing and the data they're trying to collect may be inadequate
Quantitative surveys have been the industry standard for years. Customers are asked a single question: On a scale of 0 to 10, how pleased are you with this company's product or service? Or, how likely are you to tell a friend or colleague about this product? While these surveys are time and resource costly, and customers are becoming less willing to participate as they get more intrusive, they have remained a key component of organizations' customer knowledge strategy.
The difficulty is that these surveys are unable to detect crucial emotional reactions, resulting in the omission of critical feedback. Customers frequently rate companies highly in surveys, even when they have severe difficulties with their products or services, according to our research — a critical reaction that they overlook. These surveys can also cause businesses to lose consumers without them realizing it because they disguise serious customer unhappiness.
However, if you know where to search and how to interpret data, you might find a treasure of helpful information. For example, customers frequently express their actual opinions and thoughts in the open-ended comment sections found at the end of surveys. The content of these comments, on the whole, is a significantly better predictor of a customer's behavior. Unfortunately, however, these are frequently overlooked, and if they are used at all, it is usually after the scores have been computed.
The good news is that most businesses can rapidly fix this blunder. We created an AI-driven strategy that practitioners may use as a template to tweak their customer feedback procedures.