See Smart Vision Europe’s new Text Categoriser with Watsonx.ai in action

Text comments often contain the richest insight in a dataset, but they are also the hardest to analyse consistently at scale. Text analytics helps turn unstructured text into structured evidence by identifying themes, sentiments and patterns across sources such as surveys, support tickets, reviews and assessment remarks.

In this webinar, we demonstrate a new SPSS-integrated Text Categoriser powered by IBM watsonx.ai. You’ll see how you can move from raw free-text responses to creating usable variables and outputs for reporting, segmentation, and further statistical analysis, without having to process every comment manually.

There are multiple scenarios where the Text Categoriser can be applied:

• Customer and tenant feedback
• Client/Patient feedback
• Survey verbatims
• Product reviews and service reviews
• Support tickets and contact centre notes

We will show easy it is to use the text categoriser and demonstrate some of its key capabilities:

• Runs from within IBM SPSS Statistics
• Uses IBM watsonx.ai to classify open-ended text in SPSS datasets
• Supports topic-only and topic-plus-sentiment classification
• Classifies text comments and generates a new set of SPSS variables
• Includes a Discovery mode to suggest which topics/categories should be created
• Creates a rich set of SPSS outputs highlighting the interrelationships and persistency of category topic
• Shows how text topics and sentiment drives key outcomes like satisfaction and likelihood to recommend

Click here to book your free place