GTM AI Index
September 2026 Edition, expanded tier · The six flagship models on every category, as published September 9, 2026. The public index runs on the standard tier; this record is what the Expanded Edition Pack delivers on one category. The category page →
Index Marketing September 2026 Edition

Programmatic and display advertising

Asked as “programmatic advertising platform”, and as “demand-side platform for display ads”, on behalf of a mid-market B2B software company. 46 first choices recorded across the direct, paraphrase, budget and scale prompts, six models each.
Standing
Clear leader
61% of first choices, clear leader.

01The standing

Share is the count of first choices across the direct, paraphrase, budget and scale prompts, over all six models, for a mid-market B2B software company. Ordered by share.
ProductFirst-choice shareNegative rateLabelsQuadrant
01StackAdapt61%7%54endorsed leader
02AdRoll13%10%10accepted challenger
03The Trade Desk11%41%56criticized challenger
04Choozle4%23%13accepted challenger
05Demandbase2%29%17criticized challenger
Show the nine products at 0%, ordered by negative rate
14DV3600%59%22criticized challenger
13MediaMath0%50%10criticized challenger
12Adobe Advertising0%31%13criticized challenger
08Amazon DSP0%24%34accepted challenger
06Google Display & Video 3600%21%28accepted challenger
11Simpli.fi0%10%10accepted challenger
07Basis0%7%15accepted challenger
09Hey Sid0%0%11accepted challenger
10LinkedIn Campaign Manager0%0%10accepted challenger
Bars are the share of first choices, 0 to 100Every product with at least 10 labels here. Every product name links to its vendor page.

One product takes 61% of first choices here, so the chart would put thirteen markers in one corner and one at the far edge. The two measurements it plots are columns in the standing above: share, and the negative label rate. Five products carry a negative rate above 25% in this category. Jump to the standing

02What they warned about

A high negative share on a product with few labels is a warning. A low share on a product with many labels is salience, not sentiment.
The Trade Desk
41%
23 of 56 labels negative · 11 of 6 models · 5 hard negative
“Avoid DV360/Trade Desk/Amazon DSP: High mins ($25K–$50K/month), fees make them unviable below that.” Grok 4.1 Fast, budget prompt
DV360
59%
13 of 22 labels negative · 8 of 6 models · 4 hard negative
“Platforms to AVOID with Limited Budgets ... Requires $25,000-$50,000/month minimum” Kimi K2, budget prompt
Amazon DSP
24%
8 of 34 labels negative · 6 of 6 models · 3 hard negative
“**Amazon DSP**: High CPMs, limited B2B advantage outside retail” Mistral Small, direct prompt
MediaMath
50%
5 of 10 labels negative · 5 of 6 models · 1 hard negative
“And stay away entirely from MediaMath (bankrupt)” DeepSeek V4 Flash, negative prompt

03What they cite

Citations exist only for the models that return a source list: four of the six in this edition.

Sites the answers cite

20 of 72 answers in this category came back with a source list, from 4 of 6 models: citations where the model returns them, or the search results it consulted. 6 of those lists are Google grounding redirects that name no site and are left out of the counts. 172 links across 84 sites, every framing counted. Ranked by the number of answers carrying the site or page. The other 2 models searched through a gateway that returned no source list on this edition.

vendor site · Improvado8 answers · 14 citations · 2 models
vendor site · Vibe.co8 answers · 8 citations · 2 models
6 answers · 7 citations · 2 models
6 answers · 6 citations · 2 models
6 answers · 6 citations · 2 models
vendor site · Reddit4 answers · 5 citations · 1 model
4 answers · 4 citations · 2 models
vendor site · 6sense3 answers · 3 citations · 3 models
3 answers · 3 citations · 1 model
3 answers · 3 citations · 2 models
vendor site · Quora3 answers · 3 citations · 2 models
3 answers · 3 citations · 1 model

Pages the answers cite

The ten pages named in the most answers, by full address. A page here is one the models returned with a recommendation, not one the index endorses.

04How they answered

Six framings of the same buying question, each sent to every model in a fresh session with search on. One row per model, so a row shows whether it held its answer under rewording, what it named when cost was the constraint, and what it argued against. Computed from the raw judge labels.
ModelDirect“What is the best programmatic advertising platform for a mid-market B2B company?”Paraphrase“Which demand-side platform for display ads would you recommend to a mid-sized B2B company?”Comparative“What are the top programmatic advertising platforms and how do they differ?”Budget-constrained“What is the best programmatic advertising platform for a company with a limited budget?”Scale-constrained“We are a 500 person company evaluating a programmatic advertising platform. What should we look at?”Negative“Which programmatic advertising platforms should I avoid or be cautious about?”
Claude Opus 5no first choiceno first choiceno first choiceno first choiceno first choicenothing named
Claude Opus 4.8no first choiceno first choiceno first choiceno first choiceno first choicenothing named
GPT-6 Astrano first choiceno first choiceno first choiceno first choiceno first choicenothing named
GPT-5.6 Solno first choiceno first choiceno first choiceno first choiceno first choicenothing named
Gemini 3.1 Prono first choiceno first choiceno first choiceno first choiceno first choicenothing named
Perplexity Sonar Prono first choiceno first choiceno first choiceno first choiceno first choicenothing named
Bold is the first choiceAlternatives are counted; the count opens them.What the answer argued against

05The record

One row per call: the version string exactly as returned, whether the model searched, sources cited, and latency. Full answer text is in the free responses file. Download the record
Zero rows: every prompt, every model, every answer.
PromptModelVersion stringTime (UTC)SearchedSourcesLatency

Normalization in this category

Every judgment call made between the raw labels and the numbers above, listed so it is visible and reversible.

Category-scoped readings
Adobe read as Adobe Advertising
Google read as Google Display & Video 360
LinkedIn read as LinkedIn Campaign Manager
Meta read as Meta Ads
Unresolved, counted raw
Adform Studio
Adobe DSP
Cheetah Mobile
Criteo Commerce Max
DO Global
Google Display/Video 360
Google's ecosystem (DV360, Google Ads)
Independent DSPs
Kika Tech
MediaMath SOURCE
Microsoft Monetize
Version2 (ORION)
Xandr / Microsoft Advertising DSP
Yahoo Ad Tech / Viant
Discontinued, still offered
No shut-down product was recommended here.
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