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The Power to Read Between the Lines
Text analytics, a key technology of NICE Interaction Analytics, allows organizations to derive high-quality insights from customer interactions to better understand why customers contact the company and correct root-cause issues.
Customer interactions, whether they’re spoken or written, contain valuable information companies can use to increase customer satisfaction and loyalty, improve operational efficiency, and gain a competitive advantage. But only if you have the technology to extract the content and aggregate it. You see, an individual conversation can point to issues driving personal dissatisfaction. But having the power to combine one customer’s voice with hundreds of others— through the content of their emails, phone calls, faxes, text chats and other customer interactions— can uncover the causes of dissatisfaction across the entire customer base and enable your company to take action. That’s exactly what NICE's text analytics is designed to do.
NICE's text analytics technology transcribes customer calls and customer feedback from speech to text and combines it with other forms of text interactions such as email and online chat. It then uses natural language processing models along with statistical models to find and surface patterns.
Frequently Mentioned Topics
Text analytics can help identify the most frequent topics mentioned by customers during their interactions with your company and point to the root cause behind them. For example, by analyzing all calls about billing, you can find the recurring issues and questions customers have about their bills.
In addition to frequent topic analysis, text analytics also reveals the context in which topics are mentioned during interactions. For example, the topic “charges” might be found to be closely linked to the words “long distance.”
Text analytics also is used to identify the attitude of the speaker or the writer— another dimension with which companies can assess dissatisfaction and its main drivers. For example, interactions in which customers express negative sentiment are analyzed with frequently mentioned topics to identify which issues correlate with negative customer sentiment.
Text analytics is an important part of NICE Interaction Analytics. It surfaces otherwise hidden insights in customer interactions to help improve customer satisfaction, loyalty and operational efficiency. Click to learn more about NICE solutions for contact center operational efficiency, customer experience and revenue growth.