GTM AI Index
Index Vendors › Klear · September 2026 Edition
1 category · Named, not ranked

Klear

17Judge labels
0First choices
9Negative labels
7 of 12Models named it
1Category
September 2026 Edition. Every number here is derived from the raw labels under vendor table v2026-09-16.3, every buyer segment counted.
Standing
7 labels, too few to rank
A product needs 10 labels in a category before a share or quadrant is stated. Klear was named 7 times in Influencer, where Favikon led with 27%. The labels and the evidence are below, counted exactly.
By buyer segmentRead the same way at every buyer size.
In influencer · 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 Klear 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
Influencer platformsMarketing0%78 of 7957%7under 10 labels · led by Favikon at 27%

Movement

This is the first edition on this tier, so no move can be computed for Klear 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 Klear 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 mini00011
Gemini 3.5 Flash00000
Perplexity Sonar00101
Grok 4.1 Fast00000
Mistral Small00000
DeepSeek V4 Flash00000
Llama 4 Maverick00000
Qwen 3.7 Flash00011
Kimi K201023
GLM 4.7 FlashX00000
MiniMax M2.500101

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
Direct2 labelsNone
Paraphrase0 labelsNone
Comparative6 labelsNone
Budget-constrained1 labelNone
Scale-constrained1 labelNone
Negative7 labelsNone
First choiceAlternativeMentionNegative17 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.

“Best for: Audience insight and niche discovery” Kimi K2 · Influencer · comparative 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.

“Enterprise platforms (AspireIQ, Klear, CreatorIQ) typically start at $2,000–$5,000+/month with annual contracts—likely overkill” Kimi K2 · Influencer · scale prompt · soft negative
“Availability and packaging can change, so verify current offerings before shortlisting.” GPT-5.4 mini · Influencer · comparative prompt · soft negative
“likely too expensive and slow to deploy” Qwen 3.7 Flash · Influencer · direct prompt · soft negative
“Data accuracy complaints” Kimi K2 · Influencer · negative prompt · soft negative

Named alongside

The products named in the same answers as Klear, over the 17 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and Klear was named but was not.
ProductSame answerTook the first choice insteadHead to head
CreatorIQ16 of 173Not in the top three
GRIN15 of 170Not in the top three
Upfluence13 of 170Not in the top three
Traackr12 of 171Not in the top three
Modash10 of 171Not in the top three
HypeAuditor10 of 170Not in the top three
Aspire9 of 170Not in the top three
Afluencer7 of 170Not in the top three
AspireIQ6 of 170Not in the top three
Influee6 of 170Not 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 Klear. 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 3 of the 17 answers that named Klear and are not a share of its labels.

Domains cited

aspire.io2
guideflow.com2
influee.co2
modash.io2
toolradar.com2
blog.hubspot.com1
brandchamp.io1
businessofapps.com1
creatoriq.com1
devopsschool.com1

Fifteen of the fifteen domain citations in answers naming Klear came from somebody else's page.

Pages cited

Pages are listed as the models cited them.

Names read as Klear

What the judge wrote, as written, with how often. The vendor table decides that these count as Klear; a claim can dispute any of them.
Meltwater/Klear 1
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 Klear'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 Klear, 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 klear.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.