GTM AI Index
Index Vendors › Convert · September 2026 Edition
1 category · Ranked

Convert

53Judge labels
9First choices
2Negative labels
12 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.
Best standing
8% in Experimentation for small business buyers
Rank 3 of 69 in the mid-market standingaccepted challenger
0 of 12 models made it the first choice on the direct prompt; 0% of its 17 labels there were negative.
By buyer segmentRead the same way at every buyer size.
In experimentation · 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 Convert 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
Experimentation and personalizationMarketing8%3 of 690%17accepted challenger

Movement

This is the first edition on this tier, so no move can be computed for Convert 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 Convert across every prompt where it was named for a mid-market B2B company. Twelve models, six prompts per category.
ModelFirst choiceAlternativeMentionNegativeLabels
Claude Haiku 4.501001
GPT-5.4 mini01001
Gemini 3.5 Flash01001
Perplexity Sonar11002
Grok 4.1 Fast11002
Mistral Small01102
DeepSeek V4 Flash00000
Llama 4 Maverick10001
Qwen 3.7 Flash00000
Kimi K202002
GLM 4.7 FlashX10102
MiniMax M2.511103

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
Direct8 labels2
Paraphrase12 labels4
Comparative10 labelsNone
Budget-constrained7 labels1
Scale-constrained7 labels2
Negative9 labels3not counted in share
First choiceAlternativeMentionNegative53 labels in all, every segment counted; 9 of the 12 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.

“I would recommend Convert.com if you want a strong balance of reliability, privacy, and straightforward pricing” Perplexity Sonar · Experimentation · paraphrase prompt · first choice
“I would recommend Convert.com as the best A/B testing and personalization tool for a mid-sized B2B company” Llama 4 Maverick · Experimentation · paraphrase prompt · first choice
“Privacy-first (excellent GDPR), affordable (~$299+/month), up to 50 goals/test.” Grok 4.1 Fast · Experimentation · negative prompt · first choice
“## Top Recommendation: Convert.com” GLM 4.7 FlashX · Experimentation · paraphrase prompt · first choice

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 Convert, over the 53 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and Convert was named but was not.
ProductSame answerTook the first choice insteadHead to head
VWO46 of 5317Compare →
Optimizely CMS41 of 537Not in the top three
AB Tasty30 of 530Not in the top three
Adobe Target28 of 531Not in the top three
GrowthBook25 of 533Not in the top three
Statsig23 of 532Not in the top three
Dynamic Yield21 of 530Not in the top three
Kameleoon19 of 533Not in the top three
Mutiny18 of 531Not in the top three
PostHog15 of 534Not 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 Convert. 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 4 of the 53 answers that named Convert and are not a share of its labels.

Domains cited

vwo.com4
convert.comYour site3
gartner.com3
qualaroo.com3
abmatic.ai2
convertize.com2
cxl.com2
growthmethod.com2
learn.g2.com2
mida.so2

Twenty-two of the twenty-five domain citations in answers naming Convert came from somebody else's page.

Pages cited

Pages are listed as the models cited them.

Names read as Convert

What the judge wrote, as written, with how often. The vendor table decides that these count as Convert; a claim can dispute any of them.
Convert.com 10
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 Convert'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 Convert, 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 convert.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.