Identity resolution
Asked as “identity resolution platform”, and as “customer identity matching service”, on behalf of a mid-market B2B software company. 48 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 nine 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.
Head to head
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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18Accepted challengerEndorsed leader
0%First-choice share → · lines at 30% share and 25% negative30%
Key
01Hightouch15%
Hightouch15%02LiveRamp10%
LiveRamp10%03Segment8%
Segment8%04Tealium8%
Tealium8%05CustomerLabs 1PD Ops6%
CustomerLabs 1PD Ops6%06Prospeo4%
Prospeo4%07Demandbase4%
Demandbase4%08Amperity4%
Amperity4%09HubSpot Breeze Intelligence2%
HubSpot Breeze Intelligence2%10FullContact0%
FullContact0%11RB2B0%
RB2B0%12ZoomInfo0%
ZoomInfo0%13Salesforce Data Cloud0%
Salesforce Data Cloud0%14Acxiom0%
Acxiom0%15mParticle0%
mParticle0%16Adobe Real-Time CDP0%
Adobe Real-Time CDP0%17TransUnion0%
TransUnion0%18Experian0%
Experian0%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.
LiveRamp47%
21 of 45 labels negative · 9 of 6 models · 9 hard negative
“**1. LiveRamp (formerly Acxiom)** - **Why avoid**: The UK's Open Rights Group filed formal ICO complaints in February 2024 alleging unlawful processing” Mistral Small, negative prompt
Amperity43%
12 of 28 labels negative · 8 of 6 models · 6 hard negative
“Enterprise identity layers** like LiveRamp, Adobe, Salesforce, or Amperity unless the cost of identity errors is very high” Perplexity Sonar, budget prompt
Experian40%
6 of 15 labels negative · 5 of 6 models · 4 hard negative
“Experian — Repeated data breaches, regulatory action from the CFPB, and poor consumer complaint resolution.” DeepSeek V4 Flash, negative prompt
Persona100%
5 of 5 labels negative · 5 of 6 models · 4 hard negative
“Frequent technical breakdowns lock users out of accounts; avoid if reliability is critical.” Grok 4.1 Fast, 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. 187 links across 78 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.
8 answers · 14 citations · 3 models
vendor site · Guideflow6 answers · 7 citations · 2 models
vendor site · DirectMail.io6 answers · 6 citations · 2 models
vendor site · Prospeo6 answers · 6 citations · 1 model
5 answers · 10 citations · 1 model
vendor site · Hightouch5 answers · 8 citations · 2 models
vendor site · TrustRadius5 answers · 7 citations · 2 models
5 answers · 5 citations · 1 model
5 answers · 5 citations · 2 models
4 answers · 6 citations · 1 model
vendor site · SourceForge4 answers · 4 citations · 2 models
vendor site · Tilores4 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.
6 answers · 2 models
6 answers · 2 models
6 answers · 1 model
5 answers · 1 model
5 answers · 2 models
5 answers · 1 model
4 answers · 3 models
4 answers · 2 models
4 answers · 2 models
3 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 identity resolution platform for a mid-market B2B company?”Paraphrase“Which customer identity matching service would you recommend to a mid-sized B2B company?”Comparative“What are the top identity resolution platforms and how do they differ?”Budget-constrained“What is the best identity resolution platform for a company with a limited budget?”Scale-constrained“We are a 500 person company evaluating an identity resolution platform. What should we look at?”Negative“Which identity resolution platforms 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
Adobe read as Adobe Real-Time CDP
HubSpot (Identity Analytics) read as HubSpot Breeze Intelligence
Oracle read as Oracle Unity
Salesforce read as Salesforce Data Cloud
Salesforce (Einstein Identity) read as Salesforce Data Cloud
Unresolved, counted raw
6Degrees
Acquia Customer Data Platform
Adobe's Real-Time Customer Data Platform
Amazon Connect Customer Profiles / Identity Resolution
Authentik
Avast
Blue90
Clearbit Breeze
Drawbridge
Epsilon CORE ID
Epsilon PeopleCloud / COREid
Experian Identity Graph
Eyeota
Google
Google PAIR
Identity Digital
Keycloak
LiveRamp RampID
Lotame Panorama ID
Matchbook AI
Narrative
Optimizely Data Platform
Oracle Data Cloud
Ory
SnowcatCloud
Stirista
Unified ID 2.0/UID2
Worldcoin (Tools for Humanity)
Yoti
Zitadel
login.gov
Discontinued, still offered
No shut-down product was recommended here.