Every category where a model named Cleanlist 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
CRM data quality and deduplication	Revenue operations	19%	2 of 104	0%	34	accepted challenger
Data enrichment	GTM data and infrastructure	4%	5 of 56	0%	20	accepted challenger
Email verification	GTM data and infrastructure	0%	27 of 53	0%	1	under 10 labels · led by ZeroBounce at 29%
Identity resolution	GTM data and infrastructure	0%	57 of 151	0%	1	under 10 labels · led by Hightouch at 15%
Sales coaching and training	Sales	0%	64 of 124	0%	1	under 10 labels · led by SalesHood at 27%
Sales enablement and content	Sales	0%	42 of 81	0%	1	under 10 labels · led by Dock at 19%

Movement

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

Model	First choice	Alternative	Mention	Labels
Claude Haiku 4.5	0	2	3	5
GPT-5.4 mini	0	0	0	0
Gemini 3.5 Flash	0	0	0	0
Perplexity Sonar	2	2	0	4
Grok 4.1 Fast	0	6	1	7
Mistral Small	0	5	3	8
DeepSeek V4 Flash	3	2	2	7
Llama 4 Maverick	2	1	4	7
Qwen 3.7 Flash	0	4	1	5
Kimi K2	1	4	1	6
GLM 4.7 FlashX	2	0	0	2
MiniMax M2.5	4	3	0	7

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

Direct24 labels5

Paraphrase29 labels9

Comparative30 labels8not counted in share

Budget-constrained29 labels7

Scale-constrained13 labels2

Negative15 labels7not counted in share

First choiceAlternativeMentionNegative140 labels in all, every segment counted; 23 of the 38 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, I'd start with Cleanlist due to its comprehensive B2B focus, strong deduplication accuracy, and reasonable pricing.” GLM 4.7 FlashX · CRM data quality · paraphrase prompt · first choice

“Cleanlist is the strongest budget pick because it combines cleansing, verified enrichment, and CRM sync with a free tier and a low-cost paid plan” Perplexity Sonar · CRM data quality · budget prompt · first choice

“The best CRM data quality and deduplication tool for a company with a limited budget is Cleanlist, which offers a free tier” Llama 4 Maverick · CRM data quality · budget prompt · first choice

“Cleanlist offers the best value for B2B contact cleaning with 98% dedup accuracy plus verification and enrichment.” MiniMax M2.5 · CRM data quality · comparative 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.

No model argued against it.

Named alongside

The products named in the same answers as Cleanlist, over the 140 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and Cleanlist was named but was not.

ProductSame answerTook the first choice insteadHead to head

Apollo.io78 of 14025Not in the top three

DemandTools64 of 14010Not in the top three

ZoomInfo61 of 1403Not in the top three

Insycle51 of 14020Compare →

Cognism42 of 1401Not in the top three

Clay41 of 1400Not in the top three

HubSpot Breeze Intelligence39 of 1401Not in the top three

Lusha32 of 1400Not in the top three

ZoomInfo Operations27 of 1404Compare →

Cloudingo23 of 1401Not 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 Cleanlist. 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 17 of the 140 answers that named Cleanlist and are not a share of its labels.

Domains cited

cleanlist.aiYour site17

cognism.com11

clearout.io9

findymail.com9

syncgtm.com9

g2.com7

integrate.io7

salesgenie.com7

worldmetrics.org7

pipeline.zoominfo.com6

Seventy-two of the eighty-nine domain citations in answers naming Cleanlist came from somebody else's page.

Pages cited

cleanlist.ai/blog/2026-03-27-data-quality-tools12

clearout.io/blog/crm-data-cleaning-solutions9

cognism.com/blog/data-quality-software9

cleanlist.ai/blog/2026-05-12-best-database-cleaning-software7

findymail.com/blog/crm-data-quality7

integrate.io/blog/top-10-data-cleansing-tools7

salesgenie.com/blog/best-b2b-data-enrichment-tools7

worldmetrics.org/service/crm-data-quality7

Pages are listed as the models cited them.

Names read as Cleanlist

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

Cleanlist.ai 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 Cleanlist'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 Cleanlist, 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 cleanlist.ai 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.