GTM AI Index

Index › Vendors › Meta · September 2026 Edition

5 categories · Named, not ranked

Meta

21Judge labels

0First choices

13Negative labels

10 of 12Models named it

5Categories

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. Meta was named 7 times in Paid ads and 4 other categories, where Google Ads led with 10%. The labels and the evidence are below, counted exactly.

By buyer segmentRead the same way at every buyer size.

Small business87 of 135

under the label threshold

Mid-market92 of 137

under the label threshold

Enterprise59 of 102

under the label threshold

In paid ads · 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 Meta 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
Search and social advertising platforms	Marketing	0%	92 of 137	33%	3	under 10 labels · led by Google Ads at 10%
Attribution and marketing mix modeling	Marketing	0%	111 of 124	100%	1	under 10 labels · led by Dreamdata at 29%
Data management platforms	GTM data and infrastructure	0%	166 of 183	100%	1	under 10 labels · led by Segment at 18%
Ecommerce marketing	Marketing	0%	91 of 154	0%	1	under 10 labels · led by HubSpot Marketing Hub at 36%
Video marketing and hosting	Marketing	0%	35 of 56	100%	1	under 10 labels · led by Wistia at 56%

Movement

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

Model	Alternative	Mention	Negative	Labels
Claude Haiku 4.5	0	0	1	1
GPT-5.4 mini	0	0	1	1
Gemini 3.5 Flash	0	0	0	0
Perplexity Sonar	0	1	0	1
Grok 4.1 Fast	0	0	0	0
Mistral Small	0	0	0	0
DeepSeek V4 Flash	0	0	0	0
Llama 4 Maverick	0	0	0	0
Qwen 3.7 Flash	1	0	0	1
Kimi K2	0	0	0	0
GLM 4.7 FlashX	0	0	0	0
MiniMax M2.5	0	1	2	3

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

Comparative2 labelsNone

Budget-constrained0 labelsNone

Scale-constrained1 labelNone

Negative15 labelsNone

First choiceAlternativeMentionNegative21 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.

“ranks Google Ads, Microsoft/Bing Ads, Meta (Facebook), and LinkedIn as the most reliable for quality traffic” Qwen 3.7 Flash · Paid ads · 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.

“Meta Pixel healthcare data capture: Embedded on hospital websites, collecting diagnoses, prescriptions... without patient consent” MiniMax M2.5 · DMP · negative prompt · hard negative

“Google and Meta, for example, are known to attribute conversions to themselves regardless of whether they were the true driver.” Claude Haiku 4.5 · Attribution & MMM · negative prompt · soft negative

“This platform has the most documented issues recently... Frequent bugs and disruptions” MiniMax M2.5 · Paid ads · negative prompt · soft negative

“including YouTube, TikTok, Twitch, Snapchat, X, Meta, and others” GPT-5.4 mini · Video hosting · negative prompt · soft negative

Named alongside

The products named in the same answers as Meta, over the 21 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and Meta was named but was not.

ProductSame answerTook the first choice insteadHead to head

Google Ads9 of 212Not in the top three

LinkedIn Campaign Manager9 of 210Not in the top three

TikTok Ads6 of 210Not in the top three

HubSpot Marketing Hub4 of 210Not in the top three

Microsoft Advertising3 of 212Not in the top three

Mailchimp3 of 211Not in the top three

WordStream3 of 211Not in the top three

Amazon Ads3 of 210Not in the top three

LinkedIn3 of 210Not in the top three

Pinterest3 of 210Not 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 Meta. 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 7 of the 21 answers that named Meta and are not a share of its labels.

Domains cited

cometly.com2

forbes.com2

funnel.io2

improvado.io2

influencermarketinghub.com2

theretailexec.com2

thesmallbusinessexpo.com2

10web.io1

acfe.com1

admanage.ai1

Seventeen of the seventeen domain citations in answers naming Meta came from somebody else's page.

Pages cited

thesmallbusinessexpo.com/blog/challenges-of-marketing-attribution2

10web.io/blog/enterprise-ecommerce-platform1

acfe.com/acfe-insights-blog/blog-detail1

admanage.ai/blog/google-ads-alternatives1

amraandelma.com/influencer-fraud-statistics1

articlecube.com/6-enterprise-ecommerce-platform-challenges-and-solutions1

bitcot.com/enterprise-ecommerce-platforms1

blog.hubspot.com/website/ecommerce-website-platforms1

Pages are listed as the models cited them.

Names read as Meta

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

Meta (Facebook/Instagram) 2Meta (Facebook) 1Meta (Facebook/Instagram Ads) 1

The company

MetaBase is the company behind Meta.

Website: metabase.com
Headquarters: United States

From Wikidata, fetched September 14, 2026. These describe the company, not the product's standing, and a claimed page can dispute any of them. · Wikidata · Crunchbase

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 Meta'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 Meta, 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 metabase.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.