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.

Back to the study
AI visibility statementFinance AI Visibility Study 2026Issued October 14, 2026
Account holder
Statement period
October 9, 2026
when the AI assistants were asked
Account no.
1,531 of 2,219
its rank by overall score
Closing balance

Named in

0of 56, its tower is dark

by 0 of 4 assistants

Statement note

What this means for Collinson Group

AI assistants do not name Collinson Group in any of their 56 answers to market questions, while the typical company in its sector is named in 1.7% of answers. Its overall score is 26 out of 100, ranking 1,531st of 2,219 studied. The website passes 3 out of 14 technical checks for readiness for AI tools.

We asked 14 unbranded questions about its market, so no question mentioned Collinson Group by name. AI assistants named it in none of the 56 answers. Counting only how often it is named, it ranks 57th of 97 in its sector. The typical insurer is named in 1.7% 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
26Overall score
  • Visibility0
  • Citations0
  • Sentiment50
  • Site quality80
  • AI readiness21
Summary of account
Named by AI in
0.0%
0 of 56 answers
Share of mentions
0.0%
of the mentions of it and its 5 peers
AI readiness
3/14
technical checks passed. Typical for its sector: 3
Rank in its sector
66 of 97
by overall score, where the typical insurer scores 28

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Line itemsSection 01

Every question, and where the company came up

Collinson Group came up on 0 of 14 questions. Open any window to read that answer.

  1. 01Typical pricing models for enterprise customer engagement solutions in the travel market?0/4
  2. 02Travel loyalty programs vs. hospitality rewards programs: which drives more customer engagement?0/4
  3. 03Best solutions for improving customer retention in the hospitality industry?0/4
  4. 04What are some alternatives to traditional loyalty programs for travel and hospitality brands?0/4
  5. 05How do you address low engagement rates in a travel loyalty program?0/4
  6. 06Are enterprise travel loyalty solutions worth the investment for financial institutions?0/4
  7. 07What should I look for when choosing a travel engagement solution for my hotel chain?0/4
  8. 08Examples of customer engagement strategies that work for hospitality groups?0/4
  9. 09How do travel loyalty platforms compare to general customer engagement platforms for banks?0/4
  10. 10What are the best customer loyalty programs for airlines and hotels?0/4
  11. 11Top travel engagement platforms for large enterprises?0/4
  12. 12Common mistakes to avoid when launching a loyalty initiative in the travel sector?0/4
  13. 13Do customer engagement platforms tailored to the travel industry provide better ROI compared to generic options?0/4
  14. 14How can airlines use technology to create more personalized loyalty experiences for frequent travelers?0/4
Total namedOpenAI: 0/14Claude: 0/14Perplexity: 0/14Gemini: 0/14All assistants: 0/56
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.

Transaction detailSection 02

What Perplexity actually said

The company is not named in this answer

Perplexitydid not name the company

“Travel loyalty programs vs. hospitality rewards programs: which drives more customer engagement?”

Hospitality rewards programs generally drive more frequent, property-level engagement, while broader travel loyalty programs often create stronger ecosystem-wide engagement and retention. The winner depends on the behavior being measured.

Objective · Stronger model · Why

Frequent app/site interactions · Hospitality rewards · Hotels can engage guests around bookings, upgrades, check-in, dining, spa, and on-property spending—not just trips.

Direct bookings and repeat stays · Hospitality loyalty · Hotel programs tie benefits directly to free nights, upgrades, …

The AI’s answer as we received it, shortened and not checked for accuracy.

PayeesSection 03

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. Comarch Loyalty Solutions
    100.0%
  2. Collinson Group
    0.0%
  3. Points
    0.0%
  4. Kobie
    0.0%
  5. Ascenda
    0.0%
  6. LoyaltyOne
    0.0%
ReferrersSection 04

Websites the AI used as sources

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

  1. 01
    arrivia.com
    23
  2. 02
    comarch.com
    11
  3. 03
    talon.one
    9
  4. 04
    switchfly.com
    9
  5. 05
    mews.com
    7
  6. 06
    rivo.io
    6
  7. 07
    clevertap.com
    5
  8. 08
    navan.com
    5
  9. 09
    resources.rework.com
    5
  10. 10
    iseatz.com
    4

Collinson Group is in the study as a commercial insurer or broker.

By assistantSection 05

Which AI assistants named the company

Answers naming it, out of answers received

Gemini
0/14
Perplexity
0/14
Claude
0/14
OpenAI
0/14
Market comparisonSection 06

How Collinson Group 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
80

How well built the website's own pages are

AI readiness
21

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 07

Compared with insurers

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

Overall score
26
Ranks 66 of 97. Typical company: 28
Named in answers
0.0%
Ranks 57 of 97. Typical company: 1.7%
AI readiness
21
Ranks 51 of 97. Typical company: 29
Against its categorySection 08

Compared with commercial insurers and brokers

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

Overall score
26
Ranks 21 of 29. Typical company: 27
Named in answers
0.0%
Ranks 20 of 29. Typical company: 1.7%
AI readiness
21
Ranks 12 of 29. Typical company: 21
AI agentsSection 09

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 1: Basic web presence. Two of robots.txt, a sitemap and Link headers are in place.

To reach level 2:
  • Content Signals
Can an AI agent check out here?

Not by itself. Collinson Group 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
77 of 100
  • robots.txtPassed

    A valid robots.txt with crawl rules at the site root.

    study: 86.1%
  • SitemapPassed

    An XML sitemap listing the pages, ideally referenced 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 25 of 100 · 97% of checks could run · checked on October 9, 2026 · www.collinsongroup.com · 2,200 companies scanned

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

AI readinessSection 10

The checks behind the AI readiness score

3 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

  • Passedrobots.txt publishedstudy: 85.1%
  • PassedXML sitemapstudy: 79.4%
  • Not metHTTP 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%
AI crawlersSection 11

What AI crawlers may read (robots.txt)

This website sets no rules for any AI crawler by name, like 86% of the websites whose rules we could read. Every AI crawler follows its general rules.

Training AI

  • GPTBotpartly
  • ClaudeBotpartly
  • Anthropic-AIpartly
  • Google-Extendedpartly
  • Applebot-Extendedpartly
  • Meta-ExternalAgentpartly
  • FacebookBotpartly
  • Bytespiderpartly
  • CCBotpartly
  • Diffbotpartly
  • Omgilibotpartly

AI search

  • OAI-SearchBotpartly
  • Claude-SearchBotpartly
  • PerplexityBotpartly
  • Applebotpartly
  • Amazonbotpartly
  • YouBotpartly

Answering questions

  • ChatGPT-Userpartly
  • Claude-Userpartly
  • Perplexity-Userpartly
  • DuckAssistBotpartly
  • MistralAI-Userpartly

Read from the website’s own rules file (robots.txt). An asterisk marks a crawler the file names. The rest follow its general rules. “Partly” means only some pages are blocked.

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