Every category where a model named Habu 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
Data clean rooms	GTM data and infrastructure	2%	11 of 100	14%	14	accepted challenger
Data management platforms	GTM data and infrastructure	0%	73 of 159	0%	1	under 10 labels · led by Segment at 37%	newNew since September 2026: not ranked then, 0% now.

Movement

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

ShowHide

Model	First choice	Alternative	Mention	Negative	Labels
Claude Haiku 4.5	0	0	0	0	0
GPT-5.4 mini	0	1	0	0	1
Gemini 3.5 Flash	0	3	0	1	4
Perplexity Sonar	0	0	0	0	0
Grok 4.20	0	0	0	0	0
Mistral Small	0	2	0	0	2
DeepSeek V4 Flash	1	1	0	1	3
Llama 4 Maverick	0	0	0	0	0
Qwen 3.7 Flash	0	0	0	0	0
Kimi K2	0	2	1	0	3
GLM 4.7 FlashX	0	1	0	0	1
MiniMax M2.5	0	0	1	0	1
GPT-6 Luna	0	0	0	0	0
Muse Glimmer 30B	0	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

Direct9 labelsNone

Paraphrase5 labels2

Comparative12 labelsNone

Budget-constrained5 labelsNone

Scale-constrained8 labelsNone

Negative13 labelsNone

First choiceAlternativeMentionNegative52 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.

“Top Recommendation: Habu (now LiveRamp Clean Room)” DeepSeek V4 Flash · Data clean rooms · paraphrase prompt · first choice

“Recognized for its user-friendly interface and ability to handle multiple partnerships and advanced analytics, ideal for mid-market B2B companies.” Mistral Small · Data clean rooms · direct prompt · alternative

“modern integrations like Habu or InfoSum) that allow partners to query and analyze data directly where it already lives” Gemini 3.5 Flash · Data clean rooms · negative prompt · alternative

“Data Clean Rooms (e.g., Habu, InfoSum) that facilitate privacy-compliant, first-party data collaboration” Gemini 3.5 Flash · DMP · 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.

“What to Avoid as a Mid-Market B2B - LiveRamp / Habu: Enterprise-grade” DeepSeek V4 Flash · Data clean rooms · direct prompt · hard negative

“Only purchase a dedicated independent SaaS DCR (like LiveRamp/Habu) if you have a specific, high-revenue partner usecase lined up” Gemini 3.5 Flash · Data clean rooms · scale prompt · soft negative

Named alongside

The products named in the same answers as Habu, over the 52 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and Habu was named but was not.

ShowHide

ProductSame answerTook the first choice insteadHead to head

InfoSum41 of 522Compare →

Snowflake Data Clean Rooms39 of 528Compare →

AWS Clean Rooms34 of 527Compare →

LiveRamp Clean Room29 of 521Not among the top eight

Google Ads Data Hub25 of 522Compare →

Amazon Marketing Cloud21 of 522Compare →

Databricks Clean Rooms16 of 520Compare →

Decentriq14 of 521Compare →

Meta Advanced Analytics13 of 520Not among the top eight

Optable10 of 524Not 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 Habu. 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 46 of the 52 answers that named Habu and are not a share of its labels.

Domains cited

digitalapplied.com28

decentriq.com23

funnel.io21

guideflow.com20

liveramp.com17

gartner.com15

aiopsschool.com14

aws.amazon.com14

data-axle.com14

us.fitgap.com14

No domain is on file for Habu, so its own site is not marked.

Pages cited

digitalapplied.com/blog/data-clean-rooms-advertising-2026-marketer-decision-guide28

funnel.io/blog/data-clean-rooms21

decentriq.com/article/data-clean-rooms-compared19

guideflow.com/blog/data-clean-room-software18

aiopsschool.com/blog/top-10-data-clean-room-platforms-for-ai-features-pros-cons-comparison13

gartner.com/reviews/market/data-clean-rooms13

liveramp.com/blog/what-to-look-for-in-a-data-clean-room-provider-a-guide13

data-axle.com/resources/blog/data-clean-rooms-explained-marketers11

Pages are listed as the models cited them.

Search and answers

Where Habu stands in Google search beside where it stands in the models' answers.

ShowHide

In search

Google, US estimates

Searches for its name, Google: 2,400 a month (“habu”)
AI search demand for its name, est.: 668 a month
Its own site: No site of its own on file, so no site figures

In answers

This edition

Share of first choices

rank 11 of 100 in data clean rooms

Segment leader

19%

Snowflake Data Clean Rooms

First choices: 2 across its categories
Named in: 52 answers
Its own site cited: No site on file to match

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.

Names read as Habu

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

LiveRamp/Habu 2Habu (LiveRamp) 1Habu (acquired by LiveRamp) 1Habu (by LiveRamp) 1Habu (now LiveRamp Clean Room) 1Habu (now part of LiveRamp) 1

Follow Habu

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.

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 Habu'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 Habu, 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 Habu by email, built from the raw record of the edition. It shows:

where Habu 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 Habu, 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.