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GTM AI Index
Index › Products › Teads · October 2026 Edition
4 categories · Ranked

Teads

215Judge labels
8First choices
71Negative labels
14 / 14Models named it
4Categories
October 2026 Edition. Every number here is derived from the raw labels under vendor table v2026-10-05.2, every buyer segment counted.
Best standing
8% in Native ads for enterprise buyers
Rank 5 of 86 in the mid-market standingaccepted challenger
0 of 14 models made it the first choice on the direct prompt; 22% of its 74 labels there were negative.
What the models named instead of Teads →
By buyer segmentRead the same way at every buyer size.
In native 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 Teads 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 rateLabelsQuadrantSince September 2026
Native and content advertisingMarketing4%5 of 8622%74accepted challenger▼−11Since September 2026: 14% → 2%, −11 points. Past the 11-point floor: movement. Read over the models both editions asked.
Programmatic and display advertisingMarketing0%92 of 92100%2under 10 labels · led by StackAdapt at 48%=heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.
Content marketing platformsMarketing0%118 of 135100%1under 10 labels · led by HubSpot Content Hub at 33%newNew since September 2026: not ranked then, 0% now.
Video advertisingMarketing0%111 of 114100%1under 10 labels · led by StackAdapt at 32%=heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.

Movement

Since September 2026, Teads moved past the floor in one of four categories: Native ads, −11 points to 2%. It held within the floor in the other three.

Best category · Native ads · by segment

Small business▲+1Since September 2026: 4% → 4%, +1 point. Inside the 11-point floor: within noise. Read over the models both editions asked.
4%from 4% in September 2026
Inside the floor by 10 pointsRank 6 → 7 of 61
Mid-market▼−11Since September 2026: 14% → 2%, −11 points. Past the 11-point floor: movement. Read over the models both editions asked.
2%from 14% in September 2026
Cleared the floor by 0 pointsRank 3 → 6 of 79
Enterprise=heldSince September 2026: 9% → 9%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.
9%from 9% in September 2026
Inside the floor by 11 pointsRank 4 → 5 of 65

All categories · Mid-market

CategorySeptember 2026NowChangeReadingRank
Native ads14%2%▼−11Since September 2026: 14% → 2%, −11 points. Past the 11-point floor: movement. Read over the models both editions asked.Moved past the floorRank 3 → 5 of 86
Programmatic0%0%=heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.Within noiseRank 88 → 92 of 92
Content marketing0%0%newNew since September 2026: not ranked then, 0% now.New this editionRank 118 of 135, unchanged
Video ads0%0%=heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.Within noiseRank 39 → 111 of 114

Shares here are read over the models both editions asked, so they can differ by a point or two from the standing above, which counts every model in this edition.

The floor is 11 points of share, measured: how far the models move a leader on their own when the same questions are asked twice with nothing changed. A larger change is movement; a smaller one is noise, and both are shown. Movement is read over the twelve models both editions asked; GPT-6 Luna, Muse Glimmer 30B joined this edition and are in the standing but not yet in the comparison. How the floor is measured · The editions

By model

How each model treated Teads across every prompt where it was named for a mid-market B2B company. Fourteen models, six prompts per category.
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ModelFirst choiceAlternativeMentionNegativeLabels
Claude Haiku 4.502114
GPT-5.4 mini21003
Gemini 3.5 Flash01157
Perplexity Sonar10113
Grok 4.2012418
Mistral Small01416
DeepSeek V4 Flash03317
Llama 4 Maverick01506
Qwen 3.7 Flash12148
Kimi K212126
GLM 4.7 FlashX02327
MiniMax M2.511013
GPT-6 Luna11114
Muse Glimmer 30B05106

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
Direct27 labelsNone
Paraphrase41 labels4
Comparative49 labels14not counted in share
Budget-constrained31 labels1
Scale-constrained23 labels3
Negative44 labels3not counted in share
First choiceAlternativeMentionNegative215 labels in all, every segment counted; 8 of the 25 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.

“Reputable alternatives (fewer complaints): Outbrain, Taboola (with controls), Sharethrough.” Grok 4.20 · Native ads · negative prompt · first choice
“Best for: Performance marketing, content-driven brands, premium publisher environments” Kimi K2 · Native ads · comparative prompt · first choice
“Choose Taboola or Outbrain if you want scale and mainstream publisher reach” Perplexity Sonar · Native ads · comparative prompt · first choice
“Taboola/Outbrain for larger campaigns ... Outbrain for premium editorial” MiniMax M2.5 · Native ads · comparative 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.

“notorious for three reasons: Fraudulent Traffic:” Qwen 3.7 Flash · Video ads · negative prompt · hard negative
“Avoid the "big two" (Taboola/Outbrain)” Kimi K2 · Native ads · budget prompt · hard negative
“networks like Taboola and Outbrain. While they are legitimate companies, their primary business model involves driving cheap traffic to websites that are often highly monetized MFA pages.” Gemini 3.5 Flash · Programmatic · negative prompt · soft negative
“be very careful reading Taboola or Outbrain agreements. They historically include aggressive exclusivity clauses and auto-renewal traps.” Gemini 3.5 Flash · Native ads · negative prompt · soft negative

Named alongside

The products named in the same answers as Teads, over the 198 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and Teads was named but was not.
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ProductSame answerTook the first choice insteadHead to head
Taboola175 of 19816Compare →
MGID97 of 19823Compare →
Nativo68 of 1987Not among the top eight
TripleLift32 of 1982Not among the top eight
The Trade Desk17 of 1985Not among the top eight
Yahoo Gemini16 of 1980Not among the top eight
A head-to-head page exists where both products are among a category's top eight. 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 Teads. A fact about retrieval, not a lever on the model.

Citations exist only for the models that return a source list, five of the fourteen in this edition, so these counts come from 186 of the 198 answers that named Teads and are not a share of its labels.

Domains cited

aidigital.com101
madgicx.com82
guideflow.com75
realize.com57
g2.com56
admetrics.io48
smartyads.com48
business.quora.com43
openadlibrary.com42
zigpoll.com40

592 of the 592 domain citations in answers naming Teads came from somebody else's page.

Pages cited

Pages are listed as the models cited them.

Search and answers

teads.com is not in Google's top ten for any of the category's searches. In the answers, Teads takes 4% of first choices and StackAdapt takes 41%.
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In search

Google, US estimates
Position for “native advertising platform”
–
not in the top ten
Position for “best native advertising platform”
–
not in the top ten
Searches for its name, Google
1,900 a month (“teads”)
AI search demand for its name, est.
177 a month
Organic visits to its site
about 1,756 a month
Searches its site ranks for
275 · 38 in the top three
Sites linking to it
5,309
Paid Google search
No ads found in the estimate; that does not mean it runs none
Ads on GoogleDetailLess
7 ads · 7 text · 0 shown in the last 30 days

First shown November 2025, as Teads Holding Co, verified. Ads started 2025-10 to 2026-09: 7 in the year. 11 more by other advertisers linking to it.

On Google's pages: 1 2 3 4

In answers

This edition
Share of first choices
4%
rank 5 of 86 in native ads
Segment leader
41%
StackAdapt
First choices
8 across its categories
Named in
198 answers
Its own site cited
in 186 of the answers that named it

Search figures are US estimates from DataForSEO, read September 28, 2026; AI search demand is its modeled, directional estimate, not a count of queries to any assistant. The answers are this edition's. Two measurements side by side: neither is read as the cause of the other.

What it publishes

ShowHide
Addresses on teads.com
244
subdomains included
Content
105
counted in the table below
Documentation
122
Product · Integration
0 · 0
KindPagesLast 90 days2025-10 to 2026-09LatestCategories named
Case study87undated
Blog13undated
News or press3undated
Glossary or explainer2undated
How it is countedHide how it is counted

Every page teads.com exposes, subdomains included. Kind is read from the address and title. The last 90 days, the latest date and the twelve months count pages by when they were published, from the site's feeds, a date in the address, or the page's own publication date, read from up to a hundred of its most recently changed pages; a page that says only when it last changed is counted in its kind but not in when, so the recent counts are a floor, and a kind none of whose pages gives a publication date reads undated. Read September 29, 2026.

Names read as Teads

What the judge wrote, as written, with how often. The vendor table decides that these count as Teads; a claim can dispute any of them.
Outbrain 50Outbrain (now Teads) 4Teads (formerly Outbrain) 4Outbrain/Teads 3Outbrain (now merged with Teads) 1Outbrain (now part of Teads) 1Outbrain / Teads 1Teads (merged with Outbrain) 1Teads/Outbrain 1

Follow Teads

An email the morning each edition publishes: where this product moved, where it held, and by how much against the noise floor. One address, confirmed by a click; a stop link in every email.

Already following? Everything you follow, with a stop for each.

The company

Q28872999 is the company behind Teads.
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On record

Wikidata
Website
teads.com
Headquarters
New York City, United States
Founded
2005

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

In its own words

Stated by the vendor, not checked
Positioning
The omnichannel outcomes platform
Customers named
ALL AccorLeicaSkodaLenovoBYD Shark 6TelepassVattenfallE.ON
Not stated on the pages read
Price, starting price, free plan or trial, integrations, certifications, hosting

What Teads's own pages state, read September 28, 2026: teads.com, teads.com/blog/case-studies. A claimed page can correct any of 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 Teads'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 Teads, applied by version and listed in the change log; and a one-line description supplied by the vendor and marked as such.

What a new claim receivesHide what a new claim receives

A new claim receives the current edition's vendor brief for Teads by email, built from the raw record of the edition. It shows:

  • where Teads is named, by buyer and by framing, and which cells hold its first choices;
  • the claims the models make when they name it, ranked, with the strongest and the weakest quoted;
  • its vocabulary against the segment leader's, and the pages the models cited;
  • who was chosen in the answers that did not name Teads, and every reason the record gives;
  • a battlecard for each top rival: the head-to-head split, why they win, and the reservation quoted against them;
  • one page of published figures cleared to show a buyer.

A verification link goes to your work email; an address at teads.com is approved on the spot, any other is reviewed by hand. Your email is never published. Claiming gives no say over labels, shares, verdicts or which quotes appear.