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

Rewards Network

rewardsnetwork.com

Personal finance and money appsBanking

Money20/20 attendee

Statement period
October 9 to 14, 2026
when the AI assistants were asked
Account no.
1,040 of 2,219
its rank by overall score
Place in its category
16th of 30 personal finance apps
Closing balance

Named in

2of 60 answers

by 1 of 4 assistants

Statement note

What this means for Rewards Network

AI assistants rarely name this personal finance app, mentioning it in 2 of 60 answers. In those cases, Paytronix and Thanx are also named. The overall score is 28 out of 100, which matches the typical company in its sector, and it ranks 1,040th of 2,219 overall. Its website passes 4 of 14 technical checks for AI tool readiness.

We asked 15 unbranded questions about its market, so no question mentioned Rewards Network by name. AI assistants named it in 2 of the 60 answers. Counting only how often it is named, it ranks 136th of 394 in its sector. The typical banking company 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
28Overall score
  • Visibility5
  • Citations2
  • Sentiment50
  • Site quality80
  • AI readiness29
Summary of account
Named by AI in
3.3%
2 of 60 answers
Share of mentions
8.3%
of the mentions of it and its 5 peers
AI readiness
4/14
technical checks passed. Typical for its sector: 3
Rank in its sector
166 of 394
by overall score, where the typical banking company scores 28

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Line itemsSection 01

Every question, and where the company came up

Rewards Network came up on 2 of 15 questions. Open any window to read that answer.

  1. 01What should you look for when choosing a restaurant-focused loyalty program platform?0/4
  2. 02What are alternatives to restaurant loyalty platforms for increasing guest visits without heavy discounts?0/4
  3. 03Multi-program restaurant loyalty solutions vs single-program platforms: What are the pros and cons?0/4
  4. 04How can a restaurant use a loyalty platform to reach new customers without heavy discounting?0/4
  5. 05Why isn't my restaurant loyalty program increasing guest counts as expected?0/4
  6. 06Are restaurant loyalty marketing services worth the investment for growing customer visits?0/4
  7. 07Best ways to leverage loyalty marketing for attracting repeat full-price diners?1/4
  8. 08Restaurant loyalty platforms vs traditional coupon promotions: Which attracts more full-price guests?0/4
  9. 09Is there a cost-effective loyalty platform option for small, independent restaurants?0/4
  10. 10How can restaurants attract more full-price dining guests using loyalty programs?0/4
  11. 11Common challenges with restaurant marketing platforms and how to overcome them?0/4
  12. 12Which restaurant loyalty platform offers business growth resources for independent operators?0/4
  13. 13How do pricing models for restaurant marketing and loyalty platforms typically work in the US?0/4
  14. 14What are the top platforms for restaurant marketing and loyalty in the US?1/4
  15. 15How do restaurant marketing platforms differ from direct-to-consumer discount apps?0/4
Total namedOpenAI: 0/15Claude: 0/15Perplexity: 0/15Gemini: 2/15All assistants: 2/60
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.

Transaction detailSection 02

What Gemini actually said

An answer that names the company

Gemininamed the company

“What are the top platforms for restaurant marketing and loyalty in the US?”

… Rewards Network is a fintech company that supports restaurants through data-driven marketing, loyalty programs, and flexible funding revenuebase.ai.

Blackbird Labs focuses on loyalty solutions specifically for restaurants revenuebase.ai.

Other notable companies mentioned for loyalty program platforms in the US include:

Restaurant.com

PAR Technology

Wonders

RESY

Loyalty Jugg …

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.

Also named

CompanyTimes named
  1. 01
    Paytronix
    7
  2. 02
    Thanx
    4

Share of mentions

CompanyShare
  1. Paytronix
    33.3%
  2. Punchh (by PAR Technology)
    29.2%
  3. Thanx
    25.0%
  4. Rewards Network
    8.3%
  5. Fishbowl (by Act-On)
    4.2%
  6. LevelUp (by Grubhub)
    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
    paytronix.com
    14
  2. 02
    restolabs.com
    13
  3. 03
    merchants.doordash.com
    10
  4. 04
    loop.fans
    8
  5. 05
    thanx.com
    7
  6. 06
    restaurant.eatapp.co
    6
  7. 07
    stampme.com
    6
  8. 08
    gofoodservice.com
    6
  9. 09
    momos.com
    6
  10. 10
    restroworks.com
    6

Rewards Network is in the study as a personal finance app.

By assistantSection 05

Which AI assistants named the company

Answers naming it, out of answers received

Gemini
2/15
Claude
0/15
OpenAI
0/15
Perplexity
0/15
Market comparisonSection 06

How Rewards Network 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
5

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

Citations
2

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
29

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 banking companies

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

Overall score
28
Ranks 166 of 394. Typical company: 28
Named in answers
3.3%
Ranks 136 of 394. Typical company: 0.0%
AI readiness
29
Ranks 82 of 394. Typical company: 29
Against its categorySection 08

Compared with personal finance apps

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

Overall score
28
Ranks 16 of 30. Typical company: 29
Named in answers
3.3%
Ranks 16 of 30. Typical company: 4.2%
AI readiness
29
Ranks 12 of 30. Typical company: 29
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. Rewards Network 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

The website runs on WooCommerce.

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 AuthCould not check

    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 · 94% of checks could run · checked on October 9, 2026 · www.rewardsnetwork.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

4 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%
  • 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%
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

  • GPTBotallowed
  • ClaudeBotallowed
  • Anthropic-AIallowed
  • Google-Extendedallowed
  • Applebot-Extendedallowed
  • Meta-ExternalAgentallowed
  • FacebookBotallowed
  • Bytespiderallowed
  • CCBotallowed
  • Diffbotallowed
  • Omgilibotallowed

AI search

  • OAI-SearchBotallowed
  • Claude-SearchBotallowed
  • PerplexityBotallowed
  • Applebotallowed
  • Amazonbotallowed
  • YouBotallowed

Answering questions

  • ChatGPT-Userallowed
  • Claude-Userallowed
  • Perplexity-Userallowed
  • DuckAssistBotallowed
  • MistralAI-Userallowed

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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End of statement
All 2,219 companiesHow we measured this
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