Text analytics is the process of extracting the meaning out of text. Text analytics can be used to analyze unstructured information from sources such as survey responses, emails, support tickets, call center notes, product reviews, social media posts, and any other feedback. Text analytics enables businesses to discover insight and understand what their customers really care about and why.
These insights can be used to automate competitive analysis, business processes, create management reports, and more. One area that can provide such insights is recorded customer service calls which can provide the necessary data to:
- Track call center and agent performance
- Analyze performance of various service areas
- Improve customer satisfaction
Commonly Used Techniques in Text Analysis
The typical kinds of information extracted from text include:
Topics: this technique helps identify collections of keywords and phrases relevant to your customer experience strategy. Topics can represent concepts, such as “politeness” or “ownership” — or key business elements like product names and store locations. Within topics, you can assign all the keywords that occur in conversations related to the topics.
Themes: this technique is the grouping or bucketing of similar themes that can be relevant for the business & the industry (eg. ‘Food quality’, ‘Staff efficiency’ or ‘Product availability’)
Custom phrases: In many business operations, keywords are not easily understood by generic NLU engines. This technique helps identify specialty words unique to your business.
Sentiment: this technique helps identify the underlying sentiment (say positive, neutral, and/or negative) of text responses.
Redactions: Redactions represent keywords that you do not want transcribed or stored for business purposes— for instance PII (Personally Identifiable Information) such as credit card, social security, or telephone numbers.
After analyzing customer feedback (like product reviews or NPS responses) or examining the content of customer support tickets with text analysis tools, you can leverage these results using text analytics to help you detect opportunities for improvement and adapt your product or service to your clients’ needs and expectations. See how SuccessKPI text analytics can help you improve your customer experience.