Of 60 answers

The most named companies in the study, and S&P 500 financials, with how many of their 60 AI answers named them.

SWIFT47/60TRANSUNION46/60EXPERIAN42/60COINSTAR41/60NAVY FEDERAL CREDIT UNION41/60ZELLE41/60BLOOMBERG L.P.38/60TRADINGVIEW38/60BANCO POPULAR DE PUERTO RICO37/60PAYPAL37/60VENMO37/60CHEXSYSTEMS33/60EQUIFAX33/60MORNINGSTAR32/60S&P GLOBAL31/60ALPACA MARKETS30/60COINBASE30/60PINWHEEL29/60STRIPE29/60XERO29/60ACORNS28/60AFFIRM28/60PAYFAST (PAYGATE)28/60PAYONEER28/60INTERACTIVE BROKERS26/60CHARLES SCHWAB19/60THE HARTFORD9/60MOODY'S21/60CME GROUP19/60ACCENTURE11/60CHUBB10/60MORGAN STANLEY6/60AMERICAN EXPRESS14/60SYNCHRONY FINANCIAL12/60FACTSET20/60NASDAQ19/60ALLSTATE11/60WELLS FARGO18/60PAYCHEX10/60ARES MANAGEMENT3/60
Rezolve Ai
MethodDemo
Back to the study
AI visibility statementFinance AI Visibility Study 2026Issued October 14, 2026
Account holder

DataLab USA

datalabusa.com

Marketing, communications and recruitment agenciesAdvisers and services

Money20/20 attendee

Statement period
October 9 to 14, 2026
when the AI assistants were asked
Account no.
2,105 of 2,219
its rank by overall score
Place in its category
61st of 64 agencies
Closing balance

Named in

0of 60, its tower is dark

by 0 of 4 assistants

Statement note

What this means for DataLab USA

AI assistants do not name this agency in any of their 60 answers. Its overall score is 22 out of 100, which ranks 2,105th of 2,219, below the overall score for the typical company in its sector. The website passes 2 out of 14 technical checks for AI tool readiness.

We asked 15 unbranded questions about its market, so no question mentioned DataLab USA by name. AI assistants named it in none of the 60 answers. Counting only how often it is named, it ranks 149th of 346 in its sector. The typical advisory or services firm is named in 0.0% of answers.

Named fewer than three times in total. Read this as a sign that AI assistants rarely bring this company up, not as an exact comparison with its peers.

Overall score
22Overall score
  • Visibility0
  • Citations0
  • Sentiment50
  • Site quality67
  • AI readiness14
Summary of account
Named by AI in
0.0%
0 of 60 answers
Share of mentions
0.0%
no answer named it or its 5 peers
AI readiness
2/14
technical checks passed. Typical for its sector: 4
Rank in its sector
332 of 346
by overall score, where the typical advisory or services firm scores 27

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Line itemsSection 01

Every question, and where the company came up

DataLab USA came up on 0 of 15 questions. Open any window to read that answer.

  1. 01Why aren't predictive analytics improving my campaign performance as much as expected?0/4
  2. 02Is it worth investing in advanced data integration services for enterprise marketing strategies?0/4
  3. 03Alternatives to AI-based marketing analytics for data-driven customer targeting?0/4
  4. 04What should enterprises look for in a marketing data analytics partner for measurable outcomes?0/4
  5. 05How can large retail companies use AI-driven analytics to increase customer engagement?0/4
  6. 06What factors influence the price of predictive modeling solutions for marketers?0/4
  7. 07How do predictive modeling solutions help with enterprise customer targeting?0/4
  8. 08AI-powered marketing analytics vs traditional analytics: what's the key difference for ROI?0/4
  9. 09What other strategies exist for campaign optimization without using automated predictive modeling?0/4
  10. 10How much do comprehensive AI-powered marketing analytics services typically cost in the US?0/4
  11. 11Common challenges when integrating multiple data sources into a marketing analytics platform?0/4
  12. 12Are AI-driven marketing analytics platforms cost effective for large organizations?0/4
  13. 13What are practical applications of identity resolution in targeted marketing for enterprises?0/4
  14. 14What are the best AI-powered analytics services for optimizing marketing campaigns in the US?0/4
  15. 15Predictive modeling tools vs manual segmentation for customer acquisition—pros and cons?0/4
Total namedOpenAI: 0/15Claude: 0/15Perplexity: 0/15Gemini: 0/15All assistants: 0/60
named the companyanswered without naming itdid not answer

Columns, left to right: OpenAI, Claude, Perplexity, Gemini. Across the study, on 50% of the questions where a company is named, only one AI assistant names it.

PayeesSection 02

Where the mentions went

The companies these answers named, and how the mentions were split between this company and its peers.

Share of mentions

CompanyShare
  1. DataLab USA
    0.0%
  2. Acxiom
    0.0%
  3. Epsilon
    0.0%
  4. Merkle
    0.0%
  5. Experian Marketing Services
    0.0%
  6. Infutor (a Verisk business)
    0.0%
ReferrersSection 03

Websites the AI used as sources

How many times each website was listed as a source in these answers

  1. 01
    cometly.com
    19
  2. 02
    improvado.io
    18
  3. 03
    thecmo.com
    5
  4. 04
    funnel.io
    4
  5. 05
    netsuite.com
    4
  6. 06
    integrate.io
    4
  7. 07
    diggrowth.com
    3
  8. 08
    insiderone.com
    3
  9. 09
    50pros.com
    3
  10. 10
    hashmeta.ai
    3

DataLab USA is in the study as an agency.

By assistantSection 04

Which AI assistants named the company

Answers naming it, out of answers received

Claude
0/15
Gemini
0/15
OpenAI
0/15
Perplexity
0/15
Market comparisonSection 05

How DataLab USA compares with all 2,219 companies

Every tower is a company in the study, taller for a higher overall score and lit where AI assistants named it. Its own group stays lit. Hover a tower to see it, and click to open it.

What makes up the score

Each part is scored out of 100.

Visibility
0

How often AI assistants name the company, and how that compares with its peers

Citations
0

How often AI uses the company's own website as a source

Sentiment
50

How positively AI describes the company

Site quality
67

How well built the website's own pages are

AI readiness
14

How easily AI tools can read and use the website

Visibility is calculated from the answers on this page. How the score is built.

Against its sectorSection 06

Compared with advisory and services firms

346 companies in this sector. The gold tick on each bar is the typical company.

Overall score
22
Ranks 332 of 346. Typical company: 27
Named in answers
0.0%
Ranks 149 of 346. Typical company: 0.0%
AI readiness
14
Ranks 301 of 346. Typical company: 29
Against its categorySection 07

Compared with agencies

64 companies in this category. The gold tick on each bar is the typical company.

Overall score
22
Ranks 61 of 64. Typical company: 27
Named in answers
0.0%
Ranks 24 of 64. Typical company: 0.0%
AI readiness
14
Ranks 58 of 64. Typical company: 29
AI agentsSection 08

Ready for AI agents

What this website publishes for an AI agent to read, use and pay through, on a scale of six levels.

  1. 0
  2. 1
  3. 2
  4. 3
  5. 4
  6. 5

Level 0: Not yet agent-ready. Agents struggle to find basic information about the site.

To reach level 1:
  • 2 of robots.txt, Sitemap, Link headers
Can an AI agent check out here?

Not by itself. DataLab USA publishes none of the agent payment protocols we look for. An agent would have to click through the website like a person.

Agent payment protocols
  • x402Not present
  • MPPNot present
  • AP2Not present
  • ACPNot present
  • UCPNot present
Interfaces for AI agents
  • MCP Server CardNot present
  • A2A Agent CardNot present
  • Agent SkillsNot present
  • API CatalogNot present
  • llms.txtNot present
  • WebMCPCould not check
Show every check, for your technical team
Discoverability
0 of 100
  • robots.txtNot met

    Publish a valid robots.txt with crawl rules and a Sitemap line.

    study: 86.1%
  • SitemapNot met

    Serve an XML sitemap and reference it from robots.txt.

    study: 87.9%
  • Link headersNot met

    Send Link headers such as rel="api-catalog" or rel="describedby" on the homepage.

    study: 1.5%
  • DNS for AI DiscoveryNot present

    Advertise agent endpoints with SVCB records under _agents.

    study: 4.3%
Content accessibility
0 of 100
  • Markdown negotiationNot met

    Return a markdown version when asked with Accept: text/markdown, for example at the CDN.

    study: 6.2%
  • llms.txtNot met

    Publish an llms.txt with a short summary and the key links.

    study: 31.0%
Bot access control
32 of 100
  • AI bot rulesPartly met

    Add explicit robots.txt groups for the main AI crawlers.

    study: 92.7%
  • Content SignalsNot met

    Add a Content-Signal line for search, ai-input and ai-train to robots.txt.

    study: 2.3%
  • Web Bot AuthNot present

    Only relevant if you run your own agents or crawlers: publish a signing key directory.

    study: 0.3%
APIs, auth and MCP
0 of 100
  • API CatalogNot met

    List public APIs in a linkset at /.well-known/api-catalog.

    study: 1.3%
  • OAuth discoveryNot met

    Publish OpenID Connect or OAuth server metadata under /.well-known.

    study: 6.3%
  • OAuth Protected ResourceNot met

    Serve protected resource metadata at /.well-known/oauth-protected-resource.

    study: 5.3%
  • auth.mdNot met

    Publish an auth.md describing how agents sign in.

    study: 0.2%
  • MCP Server CardNot met

    Offer an MCP server and publish its server card under /.well-known.

    study: 0.8%
  • A2A Agent CardNot met

    Publish an agent card at /.well-known/agent-card.json.

    study: 0.2%
  • Agent SkillsNot met

    Publish a skills index with the main tasks agents can do.

    study: 1.0%
  • WebMCPCould not check

    Register key actions such as search or cart as WebMCP tools.

    study: 0.0%
  • ARD manifestNot met

    Publish an ai-catalog.json listing every agent interface.

    study: 0.2%

Score 7 of 100 · 97% of checks could run · checked on October 9, 2026 · datalabusa.com · 2,200 companies scanned

See how every company did, and how this was measured.

AI readinessSection 09

The checks behind the AI readiness score

2 of 14 passed. This list is for your technical team. The percentage is how many companies in the study pass each check.

These 14 checks ran during the audit and are what the AI readiness part of the overall score counts. The scan above ran later and is stricter on Link headers and Markdown, so a check can pass here and not there.

Show the 14 checks

Discoverability

  • Not metrobots.txt publishedstudy: 85.1%
  • Not metXML sitemapstudy: 79.4%
  • PassedHTTP Link headers (RFC 8288)study: 42.5%

Content Accessibility

  • Not metMarkdown content negotiationstudy: 7.4%
  • Not metllms.txt publishedstudy: 28.1%
  • PassedToken budget (page weight)study: 97.3%

Bot Access Control

  • Not metExplicit AI bot rulesstudy: 11.5%

API / Auth / MCP

  • Not metAPI Catalog (.well-known/api-catalog)study: 1.1%
  • Not metOAuth Authorization Server discoverystudy: 5.2%
  • Not metOAuth Protected Resource discoverystudy: 4.6%
  • Not metMCP Server Cardstudy: 0.2%
  • Not metA2A Agent Cardstudy: 0.0%
  • Not metWebMCP toolsstudy: 0.3%
  • Not metAgent Skills declaredstudy: 0.1%
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End of statement
All 2,219 companiesHow we measured this
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