Index › Vendors › IntentData.io · September 2026 Edition

1 category · Named, not ranked

IntentData.io

5Judge labels

0First choices

4Negative labels

3 of 12Models named it

1Category

September 2026 Edition. Every number here is derived from the raw labels under vendor table v2026-09-16.3, every buyer segment counted.

Standing

2 labels, too few to rank

A product needs 10 labels in a category before a share or quadrant is stated. IntentData.io was named 2 times in Intent data, where Bombora led with 35%. The labels and the evidence are below, counted exactly.

By buyer segmentRead the same way at every buyer size.

Small business48 of 58

under the label threshold

Mid-market61 of 62

under the label threshold

Enterprise39 of 39

under the label threshold

In intent data · each standing computed within its segment · bars are 0 to 100 · the accent bar is the product's own best reading

Standing by category

Every category where a model named IntentData.io 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
B2B intent data providers	Sales	0%	61 of 62	100%	2	under 10 labels · led by Bombora at 35%

Movement

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

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

Direct0 labelsNone

Paraphrase0 labelsNone

Comparative1 labelNone

Budget-constrained0 labelsNone

Scale-constrained0 labelsNone

Negative4 labelsNone

First choiceAlternativeMentionNegative5 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.

No positive label carried a quote.

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.

“Avoid for critical campaigns unless you can thoroughly vet each underlying data source” Mistral Small · Intent data · negative prompt · hard negative

“have inherently variable and hard-to-verify quality” DeepSeek V4 Flash · Intent data · negative prompt · soft negative

Named alongside

The products named in the same answers as IntentData.io, over the 5 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and IntentData.io was named but was not.

ProductSame answerTook the first choice insteadHead to head

Bombora4 of 50Not in the top three

Datarade4 of 50Not in the top three

Demandbase4 of 50Not in the top three

G2 Buyer Intent4 of 50Not in the top three

6sense3 of 51Not in the top three

Cognism3 of 50Not in the top three

TechTarget Priority Engine3 of 50Not in the top three

TrustRadius3 of 50Not in the top three

ZoomInfo3 of 50Not in the top three

Apollo.io2 of 50Not 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 IntentData.io. 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 1 of the 5 answers that named IntentData.io and are not a share of its labels.

Domains cited

ai-ark.com1

autobound.ai1

default.com1

getuntitled.ai1

influ2.com1

lemlist.com1

martal.ca1

onfire.ai1

oppora.ai1

outboundsalespro.com1

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

Pages cited

ai-ark.com/blog/b2b-intent-data-providers1

autobound.ai/blog/top-15-intent-data-providers-compared-20261

default.com/post/b2b-intent-data-providers1

getuntitled.ai/blog/10-best-buyer-intent-data-providers1

influ2.com/blog/intent-data-providers1

lemlist.com/blog/7-best-b2b-intent-data-providers-for-outbound1

martal.ca/intent-data-providers-lb1

onfire.ai/blog/top-b2b-intent-data-providers1

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 IntentData.io'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 IntentData.io, 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 the vendor's own domain 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.