B2B intent data providers
Asked as “B2B intent data provider”, and as “B2B buyer intent data vendor”, on behalf of a mid-market B2B software company. 52 first choices recorded across the direct, paraphrase, budget and scale prompts, six models each.
01The standing
Share is the count of first choices across the direct, paraphrase, budget and scale prompts, over all six models, for a mid-market B2B software company. Ordered by share.
ProductFirst-choice shareNegative rateLabelsQuadrant
Show the five products at 0%, ordered by negative rate
Bars are the share of first choices, 0 to 100Every product with at least 10 labels here. Every product name links to its vendor page.
Recommended versus criticized
Every product with at least 10 labels here, on both axes. The 30% line names a quadrant, not the verdict above: that one needs more than 40%.
Criticized challengerCriticized default
Negative label rate →
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14Accepted challengerEndorsed leader
0%First-choice share → · lines at 30% share and 25% negative50%
Key
01Bombora35%
Bombora35%02Apollo.io25%
Apollo.io25%03G2 Buyer Intent13%
G2 Buyer Intent13%04Intentsify4%
Intentsify4%05ZoomInfo4%
ZoomInfo4%06Dealfront2%
Dealfront2%07Cognism2%
Cognism2%08RB2B2%
RB2B2%09Lusha2%
Lusha2%10TrustRadius0%
TrustRadius0%11Warmly0%
Warmly0%12TechTarget Priority Engine0%
TechTarget Priority Engine0%13Demandbase0%
Demandbase0%146sense0%
6sense0%02What they warned about
A high negative share on a product with few labels is a warning. A low share on a product with many labels is salience, not sentiment.
6sense57%
28 of 49 labels negative · 11 of 6 models · 8 hard negative
“6sense \u2014 the most consistent buyer's-remorse reports ... "an expensive experiment that fails to deliver measurable results."” DeepSeek V4 Flash, negative prompt
Demandbase41%
19 of 46 labels negative · 10 of 6 models · 3 hard negative
“A Word of Caution: What to Avoid ... they are full Account-Based Marketing (ABM) orchestration suites designed for mature enterprise GTM teams.” Gemini 3.5 Flash, paraphrase prompt
Bombora18%
10 of 56 labels negative · 10 of 6 models · 2 hard negative
“**Avoid:** Enterprise platforms like ... Bombora ($25K-$75K/year)” GLM 4.7 FlashX, budget prompt
ZoomInfo30%
11 of 37 labels negative · 7 of 6 models · 3 hard negative
“here are the B2B intent data providers ... you should approach with caution ... ZoomInfo (Specifically "Streaming Intent") ... High False Positive Rate” Qwen 3.7 Flash, negative prompt
03What they cite
Citations exist only for the models that return a source list: four of the six in this edition.
Sites the answers cite
22 of 72 answers in this category came back with a source list, from 4 of 6 models: citations where the model returns them, or the search results it consulted. 6 of those lists are Google grounding redirects that name no site and are left out of the counts. 207 links across 77 sites, every framing counted. Ranked by the number of answers carrying the site or page. The other 2 models searched through a gateway that returned no source list on this edition.
vendor site · Demandbase10 answers · 16 citations · 3 models
vendor site · Cognism9 answers · 9 citations · 2 models
9 answers · 9 citations · 2 models
vendor site · Autobound7 answers · 8 citations · 2 models
7 answers · 7 citations · 2 models
vendor site · ZenABM7 answers · 7 citations · 3 models
6 answers · 10 citations · 2 models
vendor site · Default6 answers · 6 citations · 2 models
vendor site · Salesmotion6 answers · 6 citations · 2 models
vendor site · HG Insights5 answers · 5 citations · 2 models
vendor site · Saleshandy5 answers · 5 citations · 2 models
vendor site · ZoomInfo4 answers · 4 citations · 2 models
Pages the answers cite
The ten pages named in the most answers, by full address. A page here is one the models returned with a recommendation, not one the index endorses.
9 answers · 2 models
9 answers · 3 models
9 answers · 2 models
7 answers · 2 models
7 answers · 2 models
7 answers · 3 models
6 answers · 2 models
6 answers · 2 models
5 answers · 2 models
4 answers · 2 models
04How they answered
Six framings of the same buying question, each sent to every model in a fresh session with search on. One row per model, so a row shows whether it held its answer under rewording, what it named when cost was the constraint, and what it argued against. Computed from the raw judge labels.
ModelDirect“What is the best B2B intent data provider for a mid-market B2B company?”Paraphrase“Which B2B buyer intent data vendor would you recommend to a mid-sized B2B company?”Comparative“What are the top B2B intent data providers and how do they differ?”Budget-constrained“What is the best B2B intent data provider for a company with a limited budget?”Scale-constrained“We are a 500 person company evaluating a B2B intent data provider. What should we look at?”Negative“Which B2B intent data providers should I avoid or be cautious about?”
Claude Opus 5no first choiceno first choiceno first choiceno first choiceno first choicenothing named
Claude Opus 4.8no first choiceno first choiceno first choiceno first choiceno first choicenothing named
GPT-6 Astrano first choiceno first choiceno first choiceno first choiceno first choicenothing named
GPT-5.6 Solno first choiceno first choiceno first choiceno first choiceno first choicenothing named
Gemini 3.1 Prono first choiceno first choiceno first choiceno first choiceno first choicenothing named
Perplexity Sonar Prono first choiceno first choiceno first choiceno first choiceno first choicenothing named
Bold is the first choiceAlternatives are counted; the count opens them.What the answer argued against
05The record
One row per call: the version string exactly as returned, whether the model searched, sources cited, and latency. Full answer text is in the free responses file. Download the record
Zero rows: every prompt, every model, every answer.
| Prompt | Model | Version string | Time (UTC) | Searched | Sources | Latency |
|---|
Noise floor in this category
Flips between the edition run and its calibration repeat. Six prompts per model is a small sample; the index-wide floor is the number to trust.
Normalization in this category
Every judgment call made between the raw labels and the numbers above, listed so it is visible and reversible.
Category-scoped readings
None. Every name in this category resolved on its own.
Unresolved, counted raw
24/7 Intent
91Springboard
Apollo.io Intent
Artikle.io
G2 Marketing Solutions / G2 intent products
HubSpot lead scoring
Informa
NetLine INTENTIVE
VisiLead
Discontinued, still offered
No shut-down product was recommended here.