Data enrichment
Asked as “B2B data enrichment tool”, and as “lead and account enrichment service”, on behalf of a mid-market B2B software company. 20 first choices recorded across the direct, paraphrase, budget and scale prompts, six models each.
Standing · first-choice share
65%
Clear leader
65Apollo.io25Clay05Cognism05others
65% of first choices, clear leader.
The 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 rateLabelsQuadrantSince September 2026
04
HubSpot Breeze Intelligence5%19%26accepted challengernewNew since September 2026: not ranked then, 5% now.
HubSpot Breeze Intelligence5%19%26accepted challengernewNew since September 2026: not ranked then, 5% now.The floor is 12 points of share, measured: how far the models move a leader on their own when the same questions are asked twice with nothing changed. A larger change is movement; a smaller one can't be told apart from repeat variation, and both are shown. Each index measures its own floor from its own repeat, over its own categories, so the floor differs from one index to the next. How the floor is measured
Bars are the share of first choices, 0 to 100Every product with at least 10 labels here. Every product name links to its product page.
All six head-to-head pages: the top four products, each against each
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 →
01
02
0304
05
06Accepted challengerEndorsed leader
0%First-choice share → · lines at 30% share and 25% negative80%
Key
01Apollo.io65%
Apollo.io65%02Clay25%
Clay25%03Cognism5%
Cognism5%04HubSpot Breeze Intelligence5%
HubSpot Breeze Intelligence5%05Lusha0%
Lusha0%06ZoomInfo0%
ZoomInfo0%What they warned about
Two of six models held their first choice under the paraphrase. Claude Opus 5, GPT-6 Astra, GPT-5.6 Sol and Gemini 3.1 Pro changed. 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.
ZoomInfo52%
14 of 27 labels negative · 6 of 6 models · 4 hard negative
“ZoomInfo — the clearest documented pattern... often renews contracts against the wishes of its customers, threatens litigation to enforce renewals” Claude Opus 5, negative prompt
Apollo.io18%
6 of 33 labels negative · 5 of 6 models
“This isn't a reason to avoid Apollo — it's a reason not to use it as your sole source for EMEA/APAC or for mobile numbers.” Claude Opus 5, negative prompt
Seamless.AI80%
4 of 5 labels negative · 4 of 6 models · 3 hard negative
“multiple BBB complaints and Trustpilot reviews document customers locked into additional 12-month terms after missing the cancellation deadline” Claude Opus 5, negative prompt
Lusha24%
5 of 21 labels negative · 4 of 6 models · 1 hard negative
“Italy's data protection authority fined Lusha Systems Inc. €2 million ... The authority also ordered deletion and imposed a processing ban” Claude Opus 5, negative prompt
What they cite
Six of the six models returned a source list in this edition: six return the pages they cited.
Sites the answers cite
31 of 36 answers in this category came back with a source list, from 6 of 6 models: citations where the model returns them, or the search results it consulted. 556 links across 207 sites, every framing counted. Ranked by the number of answers carrying the site or page. None of the 36 answers across every segment cited this index's own page for the category.
vendor site · Zapier15 answers · 15 citations · 4 models
vendor site · Cleanlist14 answers · 31 citations · 4 models
vendor site · Salesmotion14 answers · 19 citations · 4 models
vendor site · Demandbase13 answers · 14 citations · 3 models
vendor site · ZoomInfo11 answers · 19 citations · 3 models
vendor site · Apollo.io11 answers · 12 citations · 4 models
vendor site · SMARTe11 answers · 12 citations · 4 models
vendor site · Amplemarket11 answers · 11 citations · 4 models
vendor site · Salesgenie11 answers · 11 citations · 3 models
vendor site · Cognism10 answers · 18 citations · 4 models
vendor site · Snov.io10 answers · 10 citations · 3 models
vendor site · Clay9 answers · 13 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.
15 answers · 4 models
14 answers · 4 models
12 answers · 3 models
11 answers · 3 models
11 answers · 4 models
10 answers · 4 models
10 answers · 3 models
8 answers · 3 models
7 answers · 2 models
7 answers · 2 models
Search against answers
Each company's standing in the answers beside its site's footprint in Google search, one row a site: the products the models named on it with their shares, and the share they add up to; monthly searches on Google, and DataForSEO's estimate of AI search demand (modeled from search signals, directional, not a count of queries to any assistant), for the most-searched of the company's and its products' names (the name is in each row's hover text); estimated monthly organic visits to the site; and its best position in Google's top ten for “b2b data enrichment tool”, “best b2b data enrichment tool”. US estimates from DataForSEO and Google's Ads Transparency Center. A small company's site, or a mid-sized company's site for its flagship, is marked company; a product on a large parent's site (Google, Microsoft) has no site figures. A column with no figures for this category is left out, and an empty cell means none were seen, not none exist. Two measurements side by side: neither is read as the cause of the other.
| Company and products | Share | Own site cited | Name searches, Google | AI search demand, est. | Organic visits | Paid search a month, est. | Google ads, last 30 days |
|---|---|---|---|---|---|---|---|
| Apollo.io apollo.io | 65% | 1010 | 33,100 | 396 | 111,608 | 94 | |
| Clay clay.com | 25% | 287 | 135,000 | 168,089 | 294,056 | 11 | |
| Cognism cognism.com | 5% | 349 | 3,600 | 68 | 48,685 | 15 | |
| HubSpot parent site HubSpot Breeze Intelligence 5% | 5% | 202 | 368,000 | 9,776 | |||
| Lusha lusha.com | 0% | 280 | 12,100 | 893 | 52,570 | $11 | 57 |
| People Data Labs peopledatalabs.com | 0% | 40 | 3,600 | 70 | 2,093 | $1,962 | 101 |
| Hunter hunter.io | 0% | 79 | 201,000 | 280,275 | 152,782 | 6 | |
| Snov.io snov.io | 0% | 56 | 3,600 | 71 | 46,528 | 3 | |
| BetterContact bettercontact.rocks | 0% | 8 | |||||
| Prospeo prospeo.io | 0% | 134 | 2,400 | 19 | 403,704 | 14 |
Google's top ten for the two searches hold 17 sites; 5 of them are among the sites the models cited here (demandbase.com, salesgenie.com, salesmotion.io, smarte.pro, zapier.com). The first result for “b2b data enrichment tool” is zapier.com.
How 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.ShowHide
How 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.
ShowHideModelDirect“What is the best B2B data enrichment tool for a mid-market B2B software company?”Paraphrase“Which lead and account enrichment service would you recommend to a mid-sized B2B software company?”Comparative“What are the top B2B data enrichment tools and how do they differ?”Budget-constrained“What is the best B2B data enrichment tool for a company with a limited budget?”Scale-constrained“We are a 500 person company evaluating a B2B data enrichment tool. What should we look at?”Negative“Which B2B data enrichment tools should I avoid or be cautious about?”
Claude Opus 5Apollo.ioagainst: ZoomInfoClayChangedagainst: Apollo.io, HubSpot Breeze Intelligence, ZoomInfono first choiceagainst: LushaApollo.ioagainst: 6sense, Amplemarket, Clay, Demandbase, ZoomInfono first choiceagainst: Clayagainst: Apollo.io, HubSpot Breeze Intelligence, Lusha, Seamless.AI, ZoomInfo
Two alternatives
Clay, HubSpot Breeze IntelligenceThree alternatives
BetterContact, Cognism, HubSpot Breeze IntelligenceFive alternatives
Apollo.io, Clay, Cognism, HubSpot Breeze Intelligence, ZoomInfoFive alternatives
Findymail, FullEnrich, Hunter, Lusha, ProspeoClaude Opus 4.8Apollo.ioagainst: ZoomInfoApollo.ioHeldagainst: ZoomInfoApollo.io, ZoomInfoApollo.ioagainst: Cognism, ZoomInfono first choicenothing named
Three alternatives
Clay, Cognism, HubSpot Breeze IntelligenceTwo alternatives
Cognism, HubSpot Breeze IntelligenceThree alternatives
Cognism, HubSpot Breeze Intelligence, LushaThree alternatives
HubSpot Breeze Intelligence, Lusha, Snov.ioGPT-6 AstraClayApollo.ioChangedApollo.ioagainst: HubSpot Breeze IntelligenceApollo.ioagainst: Clayno first choiceagainst: Apollo.io, Clay, HubSpot Breeze Intelligence, Lusha, Seamless.AI, ZoomInfo
Four alternatives
Apollo.io, Cognism, HubSpot Breeze Intelligence, ZoomInfoThree alternatives
Clay, Cognism, HubSpot Breeze IntelligenceSix alternatives
Clay, Cognism, Dun & Bradstreet, HubSpot Breeze Intelligence, People Data Labs, ZoomInfoOne alternative
HunterFive alternatives
Apollo.io, Clay, Cognism, HubSpot Breeze Intelligence, People Data LabsGPT-5.6 SolApollo.ioClayChangedagainst: ZoomInfoClayApollo.ioagainst: Clayno first choiceagainst: Apollo.io, Clay, FullEnrich, Kaspr, Lusha, Seamless.AI, ZoomInfo
Four alternatives
Clay, Cognism, People Data Labs, ZoomInfoFour alternatives
Apollo.io, Cognism, HubSpot Breeze Intelligence, People Data LabsEight alternatives
Apollo.io, Cognism, Crunchbase, FullEnrich, HubSpot Breeze Intelligence, Lusha, People Data Labs, ZoomInfoTwo alternatives
BetterContact, HunterGemini 3.1 ProHubSpot Breeze IntelligenceClayChangedagainst: ZoomInfono first choiceApollo.io, Clayagainst: Cognism, HubSpot Breeze Intelligence, ZoomInfoCognismagainst: Apollo.io, Seamless.AI, ZoomInfo
Five alternatives
6sense, Apollo.io, Cognism, HG Insights, ZoomInfoThree alternatives
Apollo.io, Cognism, HubSpot Breeze IntelligenceSix alternatives
6sense, Apollo.io, Clay, Cognism, HubSpot Breeze Intelligence, ZoomInfoThree alternatives
Dropcontact, Hunter, Snov.ioFive alternatives
Apollo.io, Dealfront, Echobot, HubSpot Breeze Intelligence, ZoomInfoPerplexity Sonar ProApollo.ioApollo.ioHeldno first choiceApollo.iono first choiceagainst: Apollo.io, Cognism, Crunchbase, Dealfront, Lusha, ZoomInfo
Four alternatives
Clay, Cognism, HubSpot Breeze Intelligence, UpLeadThree alternatives
Amplemarket, Demandbase, ZoomInfoSeven alternatives
Apollo.io, Clay, Cognism, HubSpot Breeze Intelligence, Lusha, Snov.io, ZoomInfoThree alternatives
Datanyze, Lusha, Snov.ioBold is the first choiceAlternatives are counted; the count opens them.What the answer argued against
The record
One row per call: the version string exactly as returned, whether the model searched, sources cited, and latency.
Thirty-six rows: every prompt, every model, every answer.
| Prompt | Model | Version string | Time (UTC) | Searched | Sources | Latency |
|---|---|---|---|---|---|---|
| Direct recommendation | Claude Opus 5 | claude-opus-5 | 2026-09-09 20:29 | yes | 21 | 56 s |
| Direct recommendation | Claude Opus 4.8 | claude-opus-4-8 | 2026-09-09 20:30 | yes | 38 | 48 s |
| Direct recommendation | GPT-6 Astra | gpt-6-astra | 2026-09-09 20:32 | yes | 5 | 38 s |
| Direct recommendation | GPT-5.6 Sol | gpt-5.6-sol | 2026-09-09 20:34 | yes | 3 | 44 s |
| Direct recommendation | Gemini 3.1 Pro | gemini-3.1-pro-preview | 2026-09-10 17:30 | no | 0 | 24 s |
| Direct recommendation | Perplexity Sonar Pro | sonar-pro | 2026-09-09 20:31 | yes | 20 | 5 s |
| Paraphrase | Claude Opus 5 | claude-opus-5 | 2026-09-09 20:36 | yes | 22 | 62 s |
| Paraphrase | Claude Opus 4.8 | claude-opus-4-8 | 2026-09-09 20:37 | no | 0 | 18 s |
| Paraphrase | GPT-6 Astra | gpt-6-astra | 2026-09-09 20:39 | yes | 5 | 25 s |
| Paraphrase | GPT-5.6 Sol | gpt-5.6-sol | 2026-09-09 20:40 | yes | 7 | 51 s |
| Paraphrase | Gemini 3.1 Pro | gemini-3.1-pro-preview | 2026-09-10 18:40 | yes | 13 | 70 s |
| Paraphrase | Perplexity Sonar Pro | sonar-pro | 2026-09-10 00:36 | yes | 20 | 5 s |
| Comparative | Claude Opus 5 | claude-opus-5 | 2026-09-09 20:43 | yes | 31 | 50 s |
| Comparative | Claude Opus 4.8 | claude-opus-4-8 | 2026-09-09 20:51 | yes | 29 | 59 s |
| Comparative | GPT-6 Astra | gpt-6-astra | 2026-09-09 20:54 | yes | 9 | 74 s |
| Comparative | GPT-5.6 Sol | gpt-5.6-sol | 2026-09-09 20:57 | yes | 12 | 63 s |
| Comparative | Gemini 3.1 Pro | gemini-3.1-pro-preview | 2026-09-10 18:42 | yes | 11 | 41 s |
| Comparative | Perplexity Sonar Pro | sonar-pro | 2026-09-09 20:52 | yes | 20 | 12 s |
| Budget constrained | Claude Opus 5 | claude-opus-5 | 2026-09-09 20:59 | yes | 35 | 45 s |
| Budget constrained | Claude Opus 4.8 | claude-opus-4-8 | 2026-09-09 21:00 | yes | 30 | 49 s |
| Budget constrained | GPT-6 Astra | gpt-6-astra | 2026-09-10 00:37 | yes | 4 | 24 s |
| Budget constrained | GPT-5.6 Sol | gpt-5.6-sol | 2026-09-09 21:02 | yes | 4 | 17 s |
| Budget constrained | Gemini 3.1 Pro | gemini-3.1-pro-preview | 2026-09-10 18:44 | no | 0 | 62 s |
| Budget constrained | Perplexity Sonar Pro | sonar-pro | 2026-09-09 21:01 | yes | 20 | 10 s |
| Scale constrained | Claude Opus 5 | claude-opus-5 | 2026-09-09 21:04 | yes | 37 | 76 s |
| Scale constrained | Claude Opus 4.8 | claude-opus-4-8 | 2026-09-09 21:05 | no | 0 | 27 s |
| Scale constrained | GPT-6 Astra | gpt-6-astra | 2026-09-09 21:07 | yes | 6 | 39 s |
| Scale constrained | GPT-5.6 Sol | gpt-5.6-sol | 2026-09-09 21:09 | yes | 4 | 51 s |
| Scale constrained | Gemini 3.1 Pro | gemini-3.1-pro-preview | 2026-09-10 18:45 | no | 0 | 26 s |
| Scale constrained | Perplexity Sonar Pro | sonar-pro | 2026-09-09 21:06 | yes | 20 | 6 s |
| Negative framing | Claude Opus 5 | claude-opus-5 | 2026-09-09 21:12 | yes | 45 | 82 s |
| Negative framing | Claude Opus 4.8 | claude-opus-4-8 | 2026-09-09 21:18 | yes | 40 | 57 s |
| Negative framing | GPT-6 Astra | gpt-6-astra | 2026-09-09 21:20 | yes | 6 | 51 s |
| Negative framing | GPT-5.6 Sol | gpt-5.6-sol | 2026-09-09 21:23 | yes | 9 | 66 s |
| Negative framing | Gemini 3.1 Pro | gemini-3.1-pro-preview | 2026-09-10 18:47 | yes | 10 | 31 s |
| Negative framing | Perplexity Sonar Pro | sonar-pro | 2026-09-09 21:18 | yes | 20 | 7 s |
Normalization in this category
Every judgment call made between the raw labels and the numbers above, listed so it is visible and reversible.
ShowHide
Category-scoped readings
None. Every name in this category resolved on its own.
Unresolved, counted raw
None awaiting human review.
Discontinued, still offered
No shut-down product was recommended here.