Every category where a model named DoubleVerify 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	Since September 2026
Click fraud protection	Marketing	0%	20 of 52	0%	3	under 10 labels · led by ClickCease at 36%
Mobile apps	Marketing	0%	63 of 117	0%	1	under 10 labels · led by Customer.io at 17%	newNew since September 2026: not ranked then, 0% now.
Programmatic and display advertising	Marketing	0%	77 of 92	100%	1	under 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.

Movement

This is the first edition on this tier, so no move can be computed for DoubleVerify yet. From the next edition this section shows, per buyer segment and per category, whether its share moved by more than the measured noise floor.

By model

How each model treated DoubleVerify across every prompt where it was named for a mid-market B2B company. Fourteen models, six prompts per category.

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Model	Alternative	Mention	Negative	Labels
Claude Haiku 4.5	0	0	0	0
GPT-5.4 mini	0	0	0	0
Gemini 3.5 Flash	0	0	0	0
Perplexity Sonar	0	0	0	0
Grok 4.20	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	1	0	0	1
GLM 4.7 FlashX	0	0	1	1
MiniMax M2.5	1	1	0	2
GPT-6 Luna	0	0	0	0
Muse Glimmer 30B	0	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

Direct1 labelNone

Paraphrase6 labels1

Comparative6 labelsNone

Budget-constrained4 labels1

Scale-constrained2 labelsNone

Negative10 labelsNone

First choiceAlternativeMentionNegative29 labels in all, every segment counted; 2 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.

“DV acts as an impartial auditor... Best for: Enterprises managing massive media buying budgets.” Qwen 3.7 Flash · Click fraud protection · comparative prompt · alternative

“Programmatic/display focus, need brand safety | DoubleVerify or IAS” Kimi K2 · Click fraud protection · comparative prompt · alternative

“Use fraud detection tools like TrafficGuard, IAS, or DoubleVerify” MiniMax M2.5 · Mobile apps · 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.

“recent reports suggest caution is needed regarding *how* they filter inventory” GLM 4.7 FlashX · Programmatic · negative prompt · soft negative

Named alongside

The products named in the same answers as DoubleVerify, over the 29 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and DoubleVerify was named but was not.

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ProductSame answerTook the first choice insteadHead to head

Cheq14 of 295Not among the top eight

IAS14 of 290Not among the top eight

HUMAN Security13 of 292Not among the top eight

Integral Ad Science12 of 290Not among the top eight

Lunio11 of 296Not among the top eight

TrafficGuard11 of 290Not among the top eight

ClickCease10 of 293Not among the top eight

ClickGUARD7 of 292Not among the top eight

Anura6 of 291Not among the top eight

DataDome5 of 291Not 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 DoubleVerify. 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 28 of the 29 answers that named DoubleVerify and are not a share of its labels.

Domains cited

lunio.ai15

clickpatrol.com14

guideflow.com14

improvado.io12

joindatacops.com12

trafficguard.ai12

clickguardian.ai10

clickcease.com9

sourceforge.net9

zipdo.co7

114 of the 114 domain citations in answers naming DoubleVerify came from somebody else's page.

Pages cited

guideflow.com/blog/best-click-fraud-software12

lunio.ai/blog/best-click-fraud-detection-tools-for-enterprise-advertisers12

lunio.ai/blog/the-9-best-click-fraud-detection-tools-ranked10

improvado.io/blog/best-ad-fraud-detection-software8

joindatacops.com/resources/enterprise-click-fraud-protection8

clickpatrol.com/best-click-fraud-protection-software7

trafficguard.ai/blog/best-click-fraud-protection-software-protect-your-ppc-campaigns7

sourceforge.net/software/click-fraud/for-enterprise6

Pages are listed as the models cited them.

Search and answers

doubleverify.com is not in Google's top ten for any of the category's searches. In the answers, DoubleVerify takes 0% of first choices and ClickCease takes 36%.

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In search

Google, US estimates

Position for “click fraud protection tool”

–

not in the top ten

Position for “best click fraud protection tool”

–

not in the top ten

Searches for its name, Google: 5,400 a month (“doubleverify”)
AI search demand for its name, est.: 206 a month
Organic visits to its site: about 3,605 a month
Searches its site ranks for: 500 · 57 in the top three
Sites linking to it: 5,888
Paid Google search: No ads found in the estimate; that does not mean it runs none

Ads on GoogleDetailLess

18 ads · 16 video, 2 image · 12 shown in the last 30 days

First shown October 2024, as DoubleVerify Inc, verified. Ads started 2025-11 to 2026-10: 4 in the year, 14 before. 50 more by other advertisers linking to it.

On Google's pages: 1 2 3 4

In answers

This edition

Share of first choices

rank 20 of 52 in click fraud protection

Segment leader

36%

ClickCease

First choices: 2 across its categories
Named in: 29 answers
Its own site cited: in 28 of the answers that named it

Search figures are US estimates from DataForSEO, read October 5, 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

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Addresses on doubleverify.com

542

subdomains included

Content

303

counted in the table below

Documentation

Product · Integration

18 · 0

Kind	Pages	Last 90 days	Latest
News or press	133	9	2026-09-17
Blog	99	16	2026-09-18
Report or ebook	40	0	2024-01-17
Case study	21	undated
Webinar or virtual event	10	undated

Most recent

2026-09-18Just because its a direct deal doesnt always mean its fraud free blog
2026-09-17Fraud alert the 170 billion problem hiding in ctv apps blog
2026-09-17Dv launches ask neura expanding natural language access to media intelligence news or press
2026-09-15Content alert microdramas without brand reputation drama blog
2026-09-14Fraud alert your ctv buys might be fake ipod touch sessions blog
2026-09-11Doubleverify deepens investment in malaysia building on local growth news or press

How it is countedHide how it is counted

Every page doubleverify.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. An event counts as online when its address or title says so (webinar, on demand, virtual or online summit); a conference, summit, trade show, expo or roadshow that does not say so is counted as a conference or event, which on a vendor's site is mostly in person. Read September 29, 2026.

Names read as DoubleVerify

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

DoubleVerify (DV) 2

Follow DoubleVerify

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

DoubleVerify is its own company.

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In its own words

Stated by the vendor, not checked

Positioning: DV is the leading media effectiveness platform that leverages AI to drive superior outcomes for global brands.
doubleverify.com
For: global brands
doubleverify.com
Certifications: iab badgetag caf badgetag bsc badgeaicpa soc badgeisoiec msecb badgeAPEC CBPRAPEC PRPCCPA
Customers named: TikTokWeightWatchersNortonLifeLockFanduelDQ&A TechnologyWPP MediaNewsweekVerve
Not stated on the pages read: Price, starting price, free plan or trial, integrations, hosting

What DoubleVerify's own pages state, read October 5, 2026: doubleverify.com, trust.doubleverify.com, doubleverify.com/products/neura, doubleverify.com/es/products/marketplace. 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 DoubleVerify'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 DoubleVerify, 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 DoubleVerify by email, built from the raw record of the edition. It shows:

where DoubleVerify 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 DoubleVerify, 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.