Text Analytics is a tool that can convert unstructured “voice of the customer” content, such as spoken or written comments, into structured content that can be analyzed for insights. These otherwise unforeseen insights (from things like customer complaints or product questions) create opportunities to quickly resolve issues or deepen customer satisfaction.
In general, text analytics tries to make sense of large amounts of data by:
- Categorizing the comments
- Extracting key words or concepts such as brands, people, places, or products
- Capturing the sentiment of the text (for example, positive or negative)
Text analytics can help inform a business on two levels – company and customer. At the company-wide level, it can help improve operations such as identifying product defects or areas in need of process improvements. On a customer level, it can help improve customer experience, loyalty and value. In and of itself, text analytics is very helpful in understanding what your customers like or dislike about your brands, your products, etc., allowing you to uncover insights that can be used to improve products, reduce call volumes and more.
However, there is also a great opportunity to increase the value of this feedback by linking the customer feedback to your customer data. This will enable you to:
- Understand who is providing the feedback. If it is your best customers, then the takeaways may be different than those of your less valuable customers.
- Understand why customers may not be buying your products. They may be unhappy because a product was discontinued, they may have already bought something else or they may not yet be ready to buy again.
- Validate what you know about your customers. You can compare customer feedback to your expectations regarding their product preference, purchase cycle, etc.
This increased knowledge about your customers will enable you to enhance your marketing by tailoring product messages and offers to the needs and interests of different customer groups. Plus, there’s more. The real value comes from adding this data to your customer segments and what you already know about your customers. This added information can tell you which of your high-value customers may be dissatisfied and who may be at risk of defection. It can tell you which of your low-value customers have the potential to become more valuable or reveal product needs within particular sub-segments of your customer base.
These are just some of the many ways that analytics can help you improve your operations, marketing and customer loyalty. Listening to your customers’ feedback can provide valuable insights. Leveraging this information can provide even greater impact in improved customer satisfaction, reduced costs and increased revenue.
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