Every category where a model named FullEnrich 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
Data enrichment	GTM data and infrastructure	0%	12 of 56	11%	9	under 10 labels · led by Apollo.io at 70%
CRM data quality and deduplication	Revenue operations	0%	96 of 104	100%	1	under 10 labels · led by Insycle at 34%

Movement

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

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

Direct3 labelsNone

Paraphrase1 labelNone

Comparative6 labels1not counted in share

Budget-constrained6 labels1

Scale-constrained0 labelsNone

Negative5 labels1not counted in share

First choiceAlternativeMentionNegative21 labels in all, every segment counted; 1 of the 3 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.

“Choose Clay or FullEnrich if you need the highest possible data accuracy via waterfall logic” Qwen 3.7 Flash · Enrichment · comparative prompt · first choice

“waterfall enrichment tools like BetterContact and FullEnrich offer the lowest cost-per-contact” Claude Haiku 4.5 · Enrichment · comparative prompt · alternative

“Choose FullEnrich or BetterContact if you already have a list of LinkedIn URLs” Gemini 3.5 Flash · Enrichment · budget prompt · alternative

“If you need simple email enrichment only, try FullEnrich at $29/month” GLM 4.7 FlashX · Enrichment · budget 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.

“users cite inaccurate US phone numbers, expensive phone credits, missing contacts/emails, and integration limitations” DeepSeek V4 Flash · Enrichment · negative prompt · soft negative

“Lowest cost but limited scope” Mistral Small · CRM data quality · negative prompt · soft negative

Named alongside

The products named in the same answers as FullEnrich, over the 21 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and FullEnrich was named but was not.

ProductSame answerTook the first choice insteadHead to head

Apollo.io20 of 2110Not in the top three

Lusha17 of 210Not in the top three

ZoomInfo16 of 211Not in the top three

Clay15 of 211Not in the top three

Cognism11 of 210Not in the top three

Amplemarket8 of 212Not in the top three

6sense7 of 210Not in the top three

HubSpot Breeze Intelligence7 of 210Not in the top three

Hunter5 of 211Not in the top three

Demandbase5 of 210Not 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 FullEnrich. 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 3 of the 21 answers that named FullEnrich and are not a share of its labels.

Domains cited

cleanlist.ai2

salesgenie.com2

smarte.pro2

snov.io2

6sense.com1

ai-ark.com1

amplemarket.com1

artisan.co1

autobound.ai1

bookyourdata.com1

Fourteen of the fourteen domain citations in answers naming FullEnrich came from somebody else's page.

Pages cited

cleanlist.ai/blog/15-best-b2b-data-enrichment-providers-in-2025-ranked2

salesgenie.com/blog/best-b2b-data-enrichment-tools2

smarte.pro/blog/b2b-data-enrichment2

snov.io/blog/data-enrichment-tools2

6sense.com/blog/best-b2b-data-enrichment-tools1

ai-ark.com/blog/data-enrichment-tools1

amplemarket.com/blog/best-b2b-data-enrichment-tools1

artisan.co/blog/b2b-data-enrichment-tools1

Pages are listed as the models cited them.

Names read as FullEnrich

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

BetterContact/FullEnrich 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 FullEnrich'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 FullEnrich, 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 fullenrich.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.