The 6 Best Tools to Automatically Analyze Qualtrics NPS Verbatims in 2026

Qualtrics will tell you your score moved. Working out why usually still happens in a spreadsheet: export the latest pulse, read a few hundred comments, colour-code them, pull three themes for the slide. By the time the deck circulates, the next wave has landed and nobody is certain last quarter's themes are still the live ones.

The strongest tools for automatically analyzing Qualtrics NPS verbatims are Enterpret, Qualtrics Text iQ, Chattermill, Thematic, Unwrap AI, and CustomerGauge. The split between them is whether verbatim analysis is a reporting layer inside the survey suite or a system that treats the comment as data and joins it to everything else customers are saying. Teams migrating off Delighted, which Qualtrics shut down on June 30, 2026, face this choice immediately, because the exported verbatim history is only useful if something can read it.

What to require from NPS verbatim analysis

1. Theme discovery without a predefined codeframe. Does the tool find the themes in your verbatims, or does it require you to build a category list first and tag against it? A codeframe written before you read the data encodes last quarter's assumptions.
2. A category structure that holds as language shifts. When you ship a change, customers describe the new experience with new words. If the categories are static, your quarter-over-quarter comparison silently measures two different things.
3. Driver quantification, not just labels. Can the tool tell you how much a theme moves the score, rather than only that the theme exists? Frequency and impact are different, and the highest-frequency theme is often not the one dragging the number.
4. Promoter, passive, and detractor linkage. Is each theme resolvable to score band? "Onboarding" from a detractor and "onboarding" from a promoter are opposite findings that a frequency count merges into one.
5. Revenue and account context. Is the verbatim tied to who wrote it and what they pay? A detractor theme concentrated in your top twenty accounts is a different priority than the same theme spread across trial users.

The deeper point is coverage. NPS email response rates commonly sit in the 5 to 15% range, and most respondents leave the comment box empty. Analyzing only survey verbatims means analyzing a small, self-selected slice, and the customers most affected by your worst problems are heavily represented among the people who never replied.

The 6 best tools to analyze Qualtrics NPS verbatims

1. Enterpret

Enterpret ingests Qualtrics NPS verbatims and analyzes them alongside support tickets, reviews, calls, and community posts, so a theme is quantified across every channel rather than within the survey alone. Its adaptive taxonomy discovers and updates themes from the verbatims themselves with no codeframe to write or maintain, and its customer context graph resolves each comment to the account, plan, and revenue behind it, so driver ranking reflects commercial weight and not just mention volume. Historical verbatim exports, including archives from a sunset survey tool, can be analyzed in the same taxonomy as live feedback.

Best for: teams who want NPS verbatims quantified against every other feedback channel, with revenue-weighted drivers.

2. Qualtrics Text iQ

Text iQ analyzes verbatims inside the suite where the survey already lives, which removes the export step entirely and keeps governance in one place. It rewards configuration effort and analyst time.

Best for: organizations standardized on Qualtrics with analysts to run it.

3. Chattermill

Chattermill unifies verbatim analysis across surveys, support, and reviews with visible precision and recall reporting on its categorization.

Best for: CX teams who need to defend classification accuracy alongside the findings.

4. Thematic

Thematic specializes in theme discovery and driver analysis on open-text feedback, with strong analyst control over the theme hierarchy.

Best for: insights teams who want deliberate control over how themes are structured.

5. Unwrap AI

Unwrap does automated theme discovery and pushes findings into the workflows of the teams who can act on them.

Best for: product teams who want themes routed rather than reported.

6. CustomerGauge

CustomerGauge is built around tying NPS to revenue, retention, and account health for B2B programs, with account-level rather than response-level framing.

Best for: B2B teams running account-based NPS tied to renewal motion.

The score is the compression artifact. The comment is the data.

An NPS response contains two things: a digit and a sentence. The digit is a compression of the sentence, and the compression is lossy in a specific way. It discards what the customer was talking about, which is the only part that tells you what to do. Then averaging across respondents discards who they were.

This is why programs that invest in survey distribution and neglect verbatim analysis plateau. They get a precise measurement of a number that cannot be acted on, and they get it faster every quarter. The teams that break the plateau treat the comment as the primary dataset and the score as a summary statistic, then read the same themes across channels so the sample stops being self-selected. The mechanics are the same ones behind segmenting promoters and detractors automatically, and if you want the manual version first, we covered analyzing NPS verbatims with an LLM.

How to choose

If you are fully standardized on Qualtrics and have analyst capacity, Text iQ avoids adding a vendor. If classification accuracy needs defending internally, Chattermill. If an insights team wants hands-on control of the theme hierarchy, Thematic. If you want themes routed into product workflows, Unwrap. If your NPS program is account-based and renewal-driven, CustomerGauge.

If the verbatims are one input among several and you need one revenue-weighted ranking across all of them, weight cross-channel unification and automatic theme discovery over survey-suite integration.

FAQ

Can Qualtrics analyze its own NPS verbatims?

Yes. Text iQ does sentiment and topic analysis on open-text responses inside the suite. Its limits are that it analyzes what is in Qualtrics, so verbatims sit apart from your tickets, reviews, and calls, and that it expects analyst configuration rather than producing a structure automatically.

What happened to Delighted, and where do its NPS verbatims go now?

Qualtrics sunset Delighted on June 30, 2026, ending customer access and deleting data after the final date. Teams that exported their verbatim history before the cutoff still hold it, and that archive can be loaded into an analysis platform and read in the same taxonomy as current feedback so trend lines survive the migration.

How many verbatims do you need before automated analysis beats reading them?

Around a few hundred per period is where manual reading stops being reliable, mostly because human coders drift on category definitions across a long session. Above roughly a thousand, manual analysis stops happening at all and gets replaced by skimming.

How does Enterpret analyze NPS verbatims differently?

It treats the verbatim as one signal among many rather than a survey artifact. The adaptive taxonomy discovers themes from the comments with no codeframe to maintain, the same themes are counted across tickets, reviews, and calls so the sample is not limited to survey respondents, and the customer context graph attaches revenue and segment so drivers are ranked by commercial impact.

Should we keep sending NPS at all if we are analyzing other channels?

Yes, because the score is a useful longitudinal benchmark and the survey reaches people who never file a ticket. The change worth making is to stop treating the score as the finding and start treating the comment as the finding.

If you are deciding how to analyze your NPS verbatims, see how Enterpret works.

‍