GTM AI Index
Index Vendors › StackAdapt · September 2026 Edition
9 categories · Ranked

StackAdapt

327Judge labels
88First choices
27Negative labels
12 of 12Models named it
9Categories
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
61% in Programmatic for mid-market buyers
Rank 1 of 96 in the mid-market standingendorsed leader
10 of 12 models made it the first choice on the direct prompt; 7% of its 54 labels there were negative.
By buyer segmentStrongest at mid-market.
In programmatic · 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 StackAdapt 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
Programmatic and display advertisingMarketing61%1 of 967%54endorsed leader
Video advertisingMarketing24%1 of 1213%31accepted challenger
Native and content advertisingMarketing23%1 of 725%40accepted challenger
Retail, proximity and IoT marketingMarketing2%23 of 1310%1under 10 labels · led by Radar at 19%
Data management platformsGTM data and infrastructure2%30 of 1830%1under 10 labels · led by Segment at 18%
Search and social advertising platformsMarketing2%19 of 1370%3under 10 labels · led by Google Ads at 10%
Account-based marketing platformsMarketing0%75 of 76100%2under 10 labels · led by AdRoll ABM at 56%
Channel partner and local marketingPartner and channel0%90 of 1080%1under 10 labels · led by JourneyBee at 15%
Video marketing and hostingMarketing0%29 of 560%1under 10 labels · led by Wistia at 56%

Movement

This is the first edition on this tier, so no move can be computed for StackAdapt 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 StackAdapt across every prompt where it was named for a mid-market B2B company. Twelve models, six prompts per category.
ModelFirst choiceAlternativeMentionNegativeLabels
Claude Haiku 4.533107
GPT-5.4 mini21014
Gemini 3.5 Flash631010
Perplexity Sonar631111
Grok 4.1 Fast651214
Mistral Small544013
DeepSeek V4 Flash772218
Llama 4 Maverick316010
Qwen 3.7 Flash33309
Kimi K2660012
GLM 4.7 FlashX450110
MiniMax M2.5662216

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
Direct71 labels34
Paraphrase63 labels30
Comparative89 labels12not counted in share
Budget-constrained39 labels10
Scale-constrained35 labels14
Negative30 labels9not counted in share
First choiceAlternativeMentionNegative327 labels in all, every segment counted; 88 of the 109 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.

“StackAdapt appears frequently as a top recommendation for mid-market B2B companies specifically due to its balance of features and accessibility.” MiniMax M2.5 · Paid ads · direct prompt · first choice
“I'd choose StackAdapt for most companies with a limited budget because it is the most consistently recommended *low-to-mid budget* platform” Perplexity Sonar · Programmatic · budget prompt · first choice
“Highly regarded for its intuitive UI, excellent customer support, absence of heavy minimum spends, and robust AI-driven optimizations” Gemini 3.5 Flash · Programmatic · scale prompt · first choice
“StackAdapt is a standout here. It requires no ad-ops specialist... For B2B / ABM campaigns: Start with StackAdapt.” Qwen 3.7 Flash · Programmatic · scale 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.

“Why avoid: If CTV represents over 40% of planned spend, these platforms should be eliminated” GLM 4.7 FlashX · Programmatic · negative prompt · hard negative
“Avoid Taboola, Outbrain (now Teads), StackAdapt, and other premium platforms” DeepSeek V4 Flash · Native ads · budget prompt · hard negative
“Avoid platforms like StackAdapt (~$2,500+/month) initially” MiniMax M2.5 · Native ads · budget prompt · hard negative
“StackAdapt if CTV is a major share of your budget, you need access to major walled gardens” Perplexity Sonar · Programmatic · negative prompt · soft negative

Named alongside

The products named in the same answers as StackAdapt, over the 327 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and StackAdapt was named but was not.
ProductSame answerTook the first choice insteadHead to head
Teads109 of 32711Compare →
Taboola98 of 32718Not in the top three
Amazon DSP98 of 3273Not in the top three
Google Display & Video 36087 of 32718Not in the top three
MGID76 of 32716Compare →
Revcontent71 of 32712Not in the top three
Demandbase70 of 32713Not in the top three
Nativo57 of 3271Not 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 StackAdapt. 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 54 of the 327 answers that named StackAdapt and are not a share of its labels.

Domains cited

vibe.co27
improvado.io22
aidigital.com20
getadlib.com18
demandbase.com17
guideflow.com16
6sense.com15
business.quora.com15
heysid.com15
syntermedia.ai15

180 of the 180 domain citations in answers naming StackAdapt came from somebody else's page.

Pages cited

Pages are listed as the models cited them.

Names read as StackAdapt

What the judge wrote, as written, with how often. The vendor table decides that these count as StackAdapt; a claim can dispute any of them.
The Trade Desk/StackAdapt 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 StackAdapt'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 StackAdapt, 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 stackadapt.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.

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