GTM AI Index
Index Vendors › Thematic · September 2026 Edition
2 categories · Named, not ranked

Thematic

8Judge labels
0First choices
1Negative labels
7 of 12Models named it
2Categories
September 2026 Edition. Every number here is derived from the raw labels under vendor table v2026-09-16.3, every buyer segment counted.
Standing
3 labels, too few to rank
A product needs 10 labels in a category before a share or quadrant is stated. Thematic was named 3 times in Customer intel and 1 other category, where Google Analytics 4 led with 16%. The labels and the evidence are below, counted exactly.
By buyer segmentRead the same way at every buyer size.
In customer intel · each standing computed within its segment · bars are 0 to 100 · the accent bar is the product's own best reading

Standing by category

Every category where a model named Thematic for a mid-market B2B company. Share is first choices across the direct, paraphrase, budget and scale prompts; rank is within every product named in that category.
CategoryFunctionShareRankNegative rateLabelsQuadrant
Customer intelligence and data scienceGTM data and infrastructure0%56 of 1580%2under 10 labels · led by Google Analytics 4 at 16%
Customer feedback and surveysCustomer0%66 of 1040%1under 10 labels · led by Google Forms at 15%

Movement

This is the first edition on this tier, so no move can be computed for Thematic yet. The next is due October 1, 2026. From the next edition this section shows, per buyer segment, whether its share moved by more than the measured noise floor.

By model

How each model treated Thematic across every prompt where it was named for a mid-market B2B company. Twelve models, six prompts per category.
ModelFirst choiceAlternativeMentionNegativeLabels
Claude Haiku 4.500000
GPT-5.4 mini00000
Gemini 3.5 Flash00000
Perplexity Sonar00000
Grok 4.1 Fast00000
Mistral Small00000
DeepSeek V4 Flash00000
Llama 4 Maverick00000
Qwen 3.7 Flash01001
Kimi K201001
GLM 4.7 FlashX00000
MiniMax M2.501001

By framing

Which of the six questions produced the naming. By model says how often; this says asked what. The first-choice count on the right carries the marks of the models that produced it.
FramingLabels by classFirst choices
Direct3 labelsNone
Paraphrase0 labelsNone
Comparative1 labelNone
Budget-constrained0 labelsNone
Scale-constrained1 labelNone
Negative3 labelsNone
First choiceAlternativeMentionNegative8 labels in all, every segment counted; 0 of the 0 first choices count toward share, since the comparative and negative framings do not. The bar is one segment per label class, to scale within the framing.

What the models said for it

Verbatim evidence the judge attached to positive labels.

“toward newer platforms like Enterpret, Chattermill, or Thematic” Qwen 3.7 Flash · Customer intel · negative prompt · alternative
“Best at extracting and quantifying themes from unstructured text at scale” Kimi K2 · Feedback · comparative prompt · alternative
“Good alternative to Chattermill for mid-market product teams” MiniMax M2.5 · Customer intel · direct prompt · alternative

And against it

Verbatim evidence attached to negative labels. A warning on a product with few labels is a warning; on a product with many, it is one voice among them.

No model argued against it.

Named alongside

The products named in the same answers as Thematic, over the 8 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and Thematic was named but was not.
ProductSame answerTook the first choice insteadHead to head
Chattermill7 of 80Not in the top three
Medallia6 of 80Not in the top three
Enterpret5 of 82Not in the top three
Qualtrics5 of 80Not in the top three
SurveyMonkey5 of 80Not in the top three
InMoment3 of 80Not in the top three
Typeform3 of 80Not in the top three
Alchemer2 of 80Not in the top three
Dovetail2 of 80Not in the top three
Hotjar2 of 80Not in the top three
A head-to-head page exists where both products are in a category's top three. The other rows are the same fact without a page behind them, so they link to the product instead.

What carried it into the answer

The sites and pages cited by the answers that named Thematic. A fact about retrieval, not a lever on the model.

Citations exist only for the models that return a source list, four of the twelve in this edition, so these counts come from 1 of the 8 answers that named Thematic and are not a share of its labels.

Domains cited

blog.buildbetter.ai1
customergauge.com1
deeto.com1
feedback.tools1
feeds.thedunvegangroup.com1
front.com1
getperspective.ai1
syncly.app1

Eight of the eight domain citations in answers naming Thematic came from somebody else's page.

Pages cited

Pages are listed as the models cited them.

Is this your product?

Claim this page

Claiming is free and changes nothing in the data. A claimed page shows a verified contact who is told when each edition publishes and when Thematic's standing changes by more than the noise floor; the right to propose corrections to the vendor table, meaning names the judge wrote that should or should not read as Thematic, applied by version and listed in the change log; and a one-line description supplied by the vendor and marked as such.

It does not get any change to labels, shares or verdicts, any preview, or any say over which quotes appear. A verification link goes to your work email; an address at thematic.com is approved on the spot, any other address is reviewed by hand.

Your name and company appear on the claimed page, or the company alone if you ask below. A title and a LinkedIn address appear there too if you give them, and are left off if you do not. Your email address is never published.

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