Text analytics is a peculiar software market segment. Vendors typically have a main offering that heavily relies on text mining and analytics, but they rarely position themselves explicitly as “text analytics platforms.” Some examples:
If you noticed that there are two distinct market segments above, you are right. There are indeed two segments, distinguished by how they mine and analyze text:
- That people generate in social posts, emails, product reviews, transcribed contact center conversations, answers to open-ended questions in VoC surveys, etc. This is mostly free-form text with little to no consistent structure.
- In documents such as invoices, purchase orders, credit applications, insurance claims, etc. These documents are often generated by ERP and other business applications, where they are semistructured with numbers, dates, and open text in predefined fields and tables.
For the last few years, we have called these markets “people-oriented text analytics platforms” and “document-oriented text analytics platforms,” respectively. These segment names worked relatively well, but there were a couple issues.
- The key idea of “mining” was missing. These platforms first mine out structure from unstructured texts and semistructured documents and then analyze the results.
- Enterprise sourcing and vendor management pros rarely use the terms “people-oriented” and “document-oriented” in their technology taxonomies.
As a result, in the soon-to-be-kicked-off process to refresh our text analytics vendor landscape research, Forrester will be simplifying and renaming the market segments as follows:
Have questions? Please set up an inquiry with me.
