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Analyse Comments Using Text Analytics

What is Text Analytics?

Text Analytics (also known as Text Analysis) is the process used to derive usable information from unstructured text.

Our proprietary Text Analysis engine quickly and accurately identifies all the topics your customers are talking about. It filters vital feedback from chatter, automatically analyses every sentence in context and categorises them into topics tailored to your business.

In addition, we can combine the feedback comments with other customer data that you supply, such as customer profiles, transactions, marketing contact histories, product ownership, etc. This will enhance the analysis and reporting of your customer opinions.

Feedback Ferret offers a fully managed service:

  • We do ALL the coding, data management and data processing which saves you time and resource;
  • We continuously monitor the quality of the results and improve the text coding to ensure very high levels of accuracy.
  • We regularly re-process all historic and current data against updated Lexicon content and reporting text analytics topic definitions.
Topic Coding

Our Text Analysis is ‘topic’ centric.  Your customers will talk about many different aspects of their experience and all topics mentioned will be presented in the text analysis results.  

Below is an example of how our topics are structured:

Feedback Ferret text analytics graphic

We use industry specific topics which are then further tailored to your organisation. The topics and categorization of feedback comments needs to be set up at a level of granularity and usefulness that works for you and your organisation. We will work with you to establish these topics and categories during the early stages of your programme.

Sentiment Scoring

Understanding a customer’s sentiment score helps understand which customers are most dissatisfied or satisfied in any particular topic.

Sentiment scores are automatically calculated for each verbatim comment at sentence, overall answer and entire survey levels.  Sentiment scores take into account the contextual meaning of comments, not simply a count of positive and negative words. Sentiment scores are retained for use in analytics and reporting and are an extremely effective proxy for satisfaction rating or where there is no rating score.

If you’d like to understand more about how our Text Analytics works, please contact us:

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