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Text IQ Management and Best Practices

  • April 30, 2026
  • 1 reply
  • 6 views
N
Level 1 ●
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Hi XM Community!

I’m looking for real-world guidance and best practices for managing text IQ.

 

Here’s a little back story:

When we set up our Qualtrics CX platform, we selected various Text IQ topics from the standard Qualtrics library.  This worked for the initial set up, but now I want to take a more dedicated approach to collecting and tagging insights on customer comments, utilizing the Text IQ Table to communicate emerging trends and topics.  As it stands today, some customer feedback is tagged with many topics while others aren’t tagged at all. 

 

Here’s where I need guidance:

  • What is the ideal number of topics per customer comment so topics are not diluted?
  • Do you actively manage Text IQ, manually tagging or re-assigning tags to individual comments or do you treat it as passive tagging?  To date, I have been letting Text IQ passively tag without much review.
  • What recommendations do you have for cleaning up text IQ so topics are more relevant.

If you are willing, please share how you manage Text IQ to make it most meaningful.  I’d like to learn from you so that I can refine my program and eventually start triangulating against CX scores.

 

Many thanks!

 

1 reply

J
Level 2 ●●
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  • joel bautista
  • Level 2 ●●
  • April 30, 2026

There is no ideal minimum or maximum number of themes per comment. The number of themes largely depends on how Text iQ is configured, particularly on the use of general versus more specific keywords. When broader terms are used, it is common for a single comment to be linked to multiple themes; more specific configurations, on the other hand, help achieve more precise theme assignment.
In my case, I manage Text iQ on a periodic basis. My main focus is not necessarily to limit the number of themes per comment, but rather to ensure that the sentiment is accurately identified and that the categorization truly reflects the customer’s intent.
At this point, I would describe my approach as semi‑active management: instead of manually tagging each individual comment, I review and adjust theme configurations when I identify patterns, ambiguities, or inconsistencies. This helps me maintain a balance between automation and quality control.
As a general recommendation to improve theme quality and prevent dilution, I suggest:

  • First understanding the type of survey and its objective.
  • Reviewing the type of questions (open‑ended, closed, emotional, operational, etc.).
  • Analyzing how customers express themselves, including informal language, synonyms, and recurring phrases.

With this foundation, it becomes easier to define clear, specific, and actionable themes, avoiding overly broad categories that provide limited analytical value.
This approach has proven useful in making Text iQ more accurate and relevant, and it also facilitates future comparisons between themes and CX metrics.

 

sorry for my english is not my principal language 

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