Every category where a model named Warmly 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
Conversational marketing platforms	Marketing	2%	14 of 87	0%	3	under 10 labels · led by Tidio at 13%
B2B intent data providers	Sales	2%	11 of 60	0%	8	under 10 labels · led by Apollo.io at 27%	▲+2Since September 2026: 0% → 2%, +2 points. Inside the 11-point floor: within noise. Read over the models both editions asked.
Identity resolution	GTM data and infrastructure	0%	37 of 140	0%	4	under 10 labels · led by Hightouch Adaptive Identity Resolution at 12%	▼−2Since September 2026: 2% → 0%, −2 points. Inside the 11-point floor: within noise. Read over the models both editions asked.
AI marketing agents	Marketing	0%	44 of 157	0%	3	under 10 labels · led by HubSpot Breeze at 24%
AI SDR agents	Sales	0%	68 of 77	33%	3	under 10 labels · led by Apollo.io at 24%	newNew since September 2026: not ranked then, 0% now.
Account-based marketing platforms	Marketing	0%	62 of 71	0%	1	under 10 labels · led by AdRoll ABM at 53%	=heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.
Session replay and heatmaps	GTM data and infrastructure	0%	52 of 56	0%	1	under 10 labels · led by Microsoft Clarity at 33%

Movement

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

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Model	First choice	Alternative	Mention	Negative	Labels
Claude Haiku 4.5	0	2	2	0	4
GPT-5.4 mini	0	0	0	0	0
Gemini 3.5 Flash	0	3	2	0	5
Perplexity Sonar	0	0	0	0	0
Grok 4.1 Fast	0	1	2	0	3
Mistral Small	1	0	0	1	2
DeepSeek V4 Flash	0	1	0	0	1
Llama 4 Maverick	0	1	0	0	1
Qwen 3.7 Flash	0	1	1	0	2
Kimi K2	1	0	1	0	2
GLM 4.7 FlashX	0	0	1	0	1
MiniMax M2.5	0	0	0	0	0
GPT-6 Luna	0	0	0	0	0
Muse Glimmer 30B	0	2	0	0	2

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

Direct12 labels1

Paraphrase10 labels2

Comparative13 labels2not counted in share

Budget-constrained5 labelsNone

Scale-constrained7 labels1

Negative11 labelsNone

First choiceAlternativeMentionNegative58 labels in all, every segment counted; 4 of the 6 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.

“For most mid-sized B2B companies, Warmly is the best recommendation due to its balance of affordability, ease of use, and comprehensive intent data.” Mistral Small · Intent data · paraphrase prompt · first choice

“Warmly stands out as the sweet spot for mid-market B2B companies” Kimi K2 · Conversational mktg · paraphrase prompt · first choice

“Warmly (Best for Automated Orchestration) ... Perfect for mid-market teams that want to immediately activate the resolved identity data” Gemini 3.5 Flash · Identity · direct prompt · alternative

“Turning buyer-intent signals into automated outbound and chat, with free tier and paid plans priced for mid-market GTM teams” Claude Haiku 4.5 · AI marketing agents · direct 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.

“These platforms are cited as having 50-70% annual churn” Mistral Small · AI SDR · negative prompt · hard negative

Named alongside

The products named in the same answers as Warmly, over the 58 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and Warmly was named but was not.

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ProductSame answerTook the first choice insteadHead to head

6sense26 of 580Not among the top eight

Demandbase23 of 580Not among the top eight

Apollo.io18 of 587Not among the top eight

Bombora17 of 581Not among the top eight

RB2B17 of 580Not among the top eight

ZoomInfo13 of 580Not among the top eight

Dealfront11 of 581Not among the top eight

G2 Buyer Intent11 of 580Not among the top eight

Drift10 of 580Not among the top eight

Qualified9 of 586Not 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 Warmly. 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 57 of the 58 answers that named Warmly and are not a share of its labels.

Domains cited

warmly.aiYour site29

demandbase.com18

pipeline.zoominfo.com17

salesmotion.io16

rb2b.com13

zenabm.com13

g2.com12

marketbetter.ai12

autobound.ai11

saleshandy.com10

122 of the 151 domain citations in answers naming Warmly came from somebody else's page.

Pages cited

demandbase.com/blog/b2b-intent-data-providers14

rb2b.com/learn/intent-data-providers12

zenabm.com/blog/b2b-intent-data-providers10

percepture.com/sales-intelligence/best-b2b-intent-data-providers9

saleshandy.com/blog/b2b-intent-data-providers9

salesmotion.io/blog/intent-data-providers8

default.com/post/b2b-intent-data-providers7

marketbetter.ai/blog/best-intent-data-providers-20267

Pages are listed as the models cited them.

Search and answers

warmly.ai is not in Google's top ten for any of the category's searches. In the answers, Warmly takes 2% of first choices and Tidio takes 13%.

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In search

Google, US estimates

Position for “conversational marketing platform”

–

not in the top ten

Searches for its name, Google: 4,400 a month (“warmly”)
AI search demand for its name, est.: 805 a month
Organic visits to its site: about 13,997 a month
Searches its site ranks for: 1,294 · 63 in the top three
Sites linking to it: 1,952
Paid Google search: No ads found in the estimate; that does not mean it runs none

Ads on GoogleDetailLess

10 ads · 9 text, 1 video · 0 shown in the last 30 days

First shown May 2024, as Max Greenwald, verified. Ads started 2025-10 to 2026-09: 6 in the year, 4 before.

On Google's pages: 1 2 3 4

In answers

This edition

Share of first choices

rank 14 of 87 in conversational mktg

Segment leader

13%

Tidio

First choices: 4 across its categories
Named in: 58 answers
Its own site cited: in 57 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

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Addresses on warmly.ai

1,004

subdomains included

Content

574

counted in the table below

Documentation

320

Product · Integration

31 · 5

Kind	Pages	Last 90 days	Latest	Categories named
Blog	334	5	2026-07-29	ABM, Enrichment
Comparison	124	4	2026-07-29
Case study	64	0	2026-04-16
Report or ebook	39	undated		CRM
Glossary or explainer	6	0	2026-03-18
Template or tool	4	0	2026-03-18
Conference or event	3	0	2023-08-01

Most recent

2026-07-29Ipfingerprint alternatives comparison
2026-07-29Visual visitor pricing blog
2026-07-23Visual visitor alternatives comparison
2026-07-16Salesloft pricing blog
2026-07-10Artisan ai pricing blog
2026-07-10Salesloft alternatives comparison

How it is countedHide how it is counted

Every page warmly.ai 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 Warmly

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

Warmly (GTM Platform) 1

Follow Warmly

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

Warmly is its own company.

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In its own words

Stated by the vendor, not checked

Positioning: Autonomous Revenue Agents for B2B
warmly.ai
For: GTM teams
warmly.ai
Price stated: Four products. One AI worker per workflow. Pay quarterly to try, switch to annual to save. warmly.ai/p/pricing
Starting price: 10000 warmly.ai/p/pricing
Integrations claimed: 40 warmly.ai
Certifications: GDPR Compliant
Customers named: ContinuInnerspaceTigerGraphOrum
Not stated on the pages read: Free plan or trial, hosting

What Warmly's own pages state, read September 28, 2026: warmly.ai, warmly.ai/p/pricing, warmly.ai/p/solutions/sdr. 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 Warmly'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 Warmly, 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 Warmly by email, built from the raw record of the edition. It shows:

where Warmly 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 Warmly, 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.