Every category where a model named WinPure Clean & Match 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	0%	28 of 104	17%	6	under 10 labels · led by Insycle at 34%

Movement

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

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

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

Paraphrase10 labelsNone

Comparative2 labelsNone

Budget-constrained2 labelsNone

Scale-constrained0 labelsNone

Negative3 labelsNone

First choiceAlternativeMentionNegative18 labels in all, every segment counted; 0 of the 0 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.

“If budget is tight and you just need periodic cleanup, WinPure's one-time license is cost-effective.” Kimi K2 · CRM data quality · paraphrase prompt · alternative

“good fit for small and midsize teams that need dependable cleanup without a heavy implementation” Claude Haiku 4.5 · CRM data quality · paraphrase prompt · alternative

“Best for: Mid-market companies needing multi-source matching” MiniMax M2.5 · CRM data quality · 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.

“Better suited for occasional batch cleanups rather than continuous automation.” Qwen 3.7 Flash · CRM data quality · paraphrase prompt · soft negative

Named alongside

The products named in the same answers as WinPure Clean & Match, over the 18 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and WinPure Clean & Match was named but was not.

ProductSame answerTook the first choice insteadHead to head

Cleanlist12 of 185Not in the top three

Insycle11 of 187Not in the top three

DemandTools10 of 181Not in the top three

LeadAngel8 of 181Not in the top three

ZoomInfo Operations6 of 182Not in the top three

Openprise5 of 180Not in the top three

Dedupely4 of 181Not in the top three

Apollo.io4 of 180Not in the top three

ZoomInfo4 of 180Not in the top three

Informatica3 of 181Not 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 WinPure Clean & Match. 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 7 of the 18 answers that named WinPure Clean & Match and are not a share of its labels.

Domains cited

clearout.io7

cognism.com5

cleanlist.ai4

integrate.io4

leadangel.com4

pipeline.zoominfo.com4

digi-texx.com3

findymail.com3

fundraiseinsider.com3

g2.com3

Forty of the forty domain citations in answers naming WinPure Clean & Match came from somebody else's page.

Pages cited

clearout.io/blog/crm-data-cleaning-solutions7

cleanlist.ai/blog/2026-03-27-data-quality-tools4

integrate.io/blog/top-10-data-cleansing-tools4

pipeline.zoominfo.com/operations/data-cleansing-software4

cleanlist.ai/blog/2026-05-12-best-database-cleaning-software3

cognism.com/blog/data-quality-software3

digi-texx.com/techblog/crm-data-cleaning-solutions3

fundraiseinsider.com/blog/crm-data-cleanup-services-solutions3

Pages are listed as the models cited 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 WinPure Clean & Match'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 WinPure Clean & Match, 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 winpure.com 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.