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
R

Reward

reward.co

Personal finance and money appsBanking

Money20/20 attendee

Statement period
October 9 to 14, 2026
when the AI assistants were asked
Account no.
2,195 of 2,219
its rank by overall score
Place in its category
30th of 30 personal finance apps
Closing balance

Named in

2of 60 answers

by 2 of 4 assistants

Statement note

What this means for Reward

AI assistants rarely name this personal finance app, appearing in 2 out of 60 answers. Gemini and OpenAI mention it, often alongside Smile.io and LoyaltyLion. Its overall score is 17 out of 100, ranking 2,195th of 2,219. How ready the website is for AI tools could not be measured, as it turned away the automated check.

We asked 15 unbranded questions about its market, so no question mentioned Reward 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
17Overall score
  • Visibility5
  • Citations1
  • Sentiment50
  • Site quality33
  • AI readiness0
Summary of account
Named by AI in
3.3%
2 of 60 answers
Share of mentions
10.0%
of the mentions of it and its 5 peers
AI readiness
n/a
the website turned our check away
Rank in its sector
388 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

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

  1. 01What are effective ways restaurants can leverage engagement platforms to encourage more frequent visits?0/4
  2. 02What features should consumer-facing businesses look for in an engagement solution?0/4
  3. 03How can a retail store use personalized incentives to boost foot traffic?1/4
  4. 04How much should a retail business expect to pay per month for a customer loyalty platform?0/4
  5. 05Does investing in digital loyalty programs actually increase customer retention rates?0/4
  6. 06Why isn't my loyalty program increasing repeat purchases?0/4
  7. 07Are customer engagement platforms worth it for businesses with under 50 employees?0/4
  8. 08Are there affordable loyalty solutions for startups with limited budgets?0/4
  9. 09What are some non-digital ways to build customer loyalty for brick-and-mortar stores?0/4
  10. 10How does a points-based rewards system compare to a tiered loyalty program?0/4
  11. 11What are the best customer loyalty platforms for small retail businesses?0/4
  12. 12Customer loyalty apps versus traditional punch cards—what are the pros and cons?0/4
  13. 13How can you fix common mistakes in implementing a rewards platform for customers?0/4
  14. 14Which engagement strategies work well besides offering points-based incentives?0/4
  15. 15What are alternatives to using a traditional loyalty punch card for customer rewards?1/4
Total namedOpenAI: 1/15Claude: 0/15Perplexity: 0/15Gemini: 1/15All 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

“How can a retail store use personalized incentives to boost foot traffic?”

… Reward customers not just for purchases, but also for visits, engagement, and referrals.

Create different tiers (e.g., Silver, Gold, VIP) with increasing benefits based on spending, purchase frequency, or other actions. This encourages customers to strive for higher statuses and unlock better perks like bonus points, free upgrades, or priority service.

Ensure the rules for these tiers are clear and achievable to maintain a positive customer experience.

Offer Personalized Discounts and Promotions:

Move beyond generic "20% off everything" messages.

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
    Smile.io
    4
  2. 02
    LoyaltyLion
    4
  3. 03
    Yotpo Loyalty & Referrals
    1

Share of mentions

CompanyShare
  1. Smile.io
    40.0%
  2. LoyaltyLion
    25.0%
  3. Yotpo Loyalty & Referrals
    25.0%
  4. Reward
    10.0%
  5. Tango Card
    0.0%
  6. Annex Cloud
    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
    nector.io
    8
  2. 02
    rivo.io
    6
  3. 03
    stampme.com
    6
  4. 04
    zigpoll.com
    5
  5. 05
    growave.io
    5
  6. 06
    shopify.com
    4
  7. 07
    mageloyalty.com
    4
  8. 08
    voucherify.io
    4
  9. 09
    salesforce.com
    3
  10. 10
    openloyalty.io
    3

Reward 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
1/15
OpenAI
1/15
Claude
0/15
Perplexity
0/15
Market comparisonSection 06

How Reward 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
1

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

Sentiment
50

How positively AI describes the company

Site quality
33

How well built the website's own pages are

AI readiness
0

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
17
Ranks 388 of 394. Typical company: 28
Named in answers
3.3%
Ranks 136 of 394. Typical company: 0.0%
AI readiness
0
Ranks 381 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
17
Ranks 30 of 30. Typical company: 29
Named in answers
3.3%
Ranks 16 of 30. Typical company: 4.2%
AI readiness
0
Ranks 30 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. Reward 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.txtPublished
  • 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
25 of 100
  • Markdown negotiationNot met

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

    study: 6.2%
  • llms.txtPartly 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 31 of 100 · 97% of checks could run · checked on October 9, 2026 · reward.co · 2,200 companies scanned

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

AI readinessSection 10

The checks behind the AI readiness score

AI readiness could not be measured. The website turned away our automated check, so none of the 14 checks could run. That reflects the website’s rules for automated visitors, not what the website contains.

Take it with you

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End of statement
All 2,219 companiesHow we measured this
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