GTM AI Index

Index › Vendors › AdOpt · September 2026 Edition

1 category · Named, not ranked

AdOpt

11Judge labels

0First choices

1Negative 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

3 labels, too few to rank

A product needs 10 labels in a category before a share or quadrant is stated. AdOpt was named 3 times in Consent, where Enzuzo led with 25%. The labels and the evidence are below, counted exactly.

By buyer segmentRead the same way at every buyer size.

Small business13 of 38

under the label threshold

Mid-market21 of 39

under the label threshold

Enterprisenot named

No model named it for this buyer.

In consent · 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 AdOpt 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.

Category	Function	Share	Rank	Negative rate	Labels	Quadrant
Consent and privacy management	GTM data and infrastructure	0%	21 of 39	33%	3	under 10 labels · led by Enzuzo at 25%

Movement

This is the first edition on this tier, so no move can be computed for AdOpt 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 AdOpt across every prompt where it was named for a mid-market B2B company. Twelve models, six prompts per category.

Model	Alternative	Negative	Labels
Claude Haiku 4.5	0	0	0
GPT-5.4 mini	0	0	0
Gemini 3.5 Flash	0	0	0
Perplexity Sonar	0	0	0
Grok 4.1 Fast	0	1	1
Mistral Small	0	0	0
DeepSeek V4 Flash	0	0	0
Llama 4 Maverick	0	0	0
Qwen 3.7 Flash	0	0	0
Kimi K2	0	0	0
GLM 4.7 FlashX	2	0	2
MiniMax M2.5	0	0	0

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

Direct4 labelsNone

Paraphrase0 labelsNone

Comparative2 labels2not counted in share

Budget-constrained4 labelsNone

Scale-constrained0 labelsNone

Negative1 labelNone

First choiceAlternativeMentionNegative11 labels in all, every segment counted; 0 of the 2 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.

“### 3. AdOpt - Simple & Direct” GLM 4.7 FlashX · Consent · budget prompt · alternative

“AdOpt: 4.9/5 on G2” GLM 4.7 FlashX · Consent · negative 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.

“G2 leaders (AdOpt, CookieScript) skew smaller sites.” Grok 4.1 Fast · Consent · direct prompt · soft negative

Named alongside

The products named in the same answers as AdOpt, over the 11 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and AdOpt was named but was not.

ProductSame answerTook the first choice insteadHead to head

CookieYes11 of 116Not in the top three

CookieScript6 of 110Not in the top three

OneTrust5 of 110Not in the top three

Cookiebot4 of 111Not in the top three

Termly4 of 111Not in the top three

Osano4 of 110Not in the top three

Usercentrics4 of 110Not in the top three

Enzuzo3 of 112Not in the top three

Complianz3 of 110Not in the top three

Didomi3 of 110Not 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 AdOpt. 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 2 of the 11 answers that named AdOpt and are not a share of its labels.

Domains cited

elementor.com2

enzuzo.com2

expertinsights.com2

learn.g2.com2

comparitech.com1

cookie-script.com1

cookieyes.com1

designrush.com1

didomi.io1

ethyca.com1

Fourteen of the fourteen domain citations in answers naming AdOpt came from somebody else's page.

Pages cited

elementor.com/blog/consent-management-small2

enzuzo.com/blog/best-consent-management-platforms2

expertinsights.com/compliance/the-top-consent-management-solutions2

learn.g2.com/best-consent-management-platforms2

comparitech.com/data-privacy-management/best-consent-management-platforms1

cookie-script.com/blog/compare-consent-management-platforms1

cookieyes.com/blog/best-consent-management-platforms1

designrush.com/agency/it-services/trends/best-consent-management-platforms1

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 AdOpt'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 AdOpt, 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 adoptkit.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.