Basic methods for finding stores with a specific merchant

[Student]

Below, I'll describe 5 key methods to help you find online stores that use specific payment processors without manually searching through websites through Google. Each method includes step-by-step instructions, examples, advantages, disadvantages, and educational aspects. I'll focus on international stores (US, EU, Asia, excluding Russia) and popular processors such as Stripe, PayPal, Square, Adyen, and Braintree. The methods will be based on official sources, aggregators, and analysis tools available in 2025.

1. Using official directories and showcases of payment processors​

Why it works: Payment processors publish lists of their clients (stores and companies) to demonstrate successful integrations. This is a reliable source, as the data is provided by the processor itself.

Steps:

1. Go to the processor's official website and find the "Customers", "Case Studies", "Gallery" or "Showcase" sections.
2. Filter by region (e.g. "USA", "Europe", "Asia-Pacific") or industry (e-commerce, SaaS, retail).
3. Explore case studies to find stores and their websites. Links to stores or integration examples are often provided.
4. For international searches, exclude local processors (for example, Yandex.Pay) and focus on global ones (Stripe, PayPal).

Examples:

• Stripe (stripe.com/customers or stripe.com/gallery):
  • Shopify (Canada/global, e-commerce platform): Uses Stripe for payment processing and financial services (Stripe Treasury). Example store: shopify.com/partners links to thousands of stores.
  • Instacart (US/Canada, delivery): Stripe for payments to stores and couriers.
  • Patreon (US, content): Stripe for creator subscriptions.
  • Notion (US, productivity): Stripe for premium plans.
  • Filters: Select "E-commerce" or "Global" on Stripe to find stores in the US/EU.
• PayPal (paypal.com/business/customer-stories):
  • Etsy (US/EU, handmade): PayPal for purchase protection.
  • eBay (global, marketplace): PayPal as the primary processor for sellers.
  • Search: Use the "Find a Store" section on paypal.com or partner platforms (WooCommerce, BigCommerce).
• Square (squareup.com/us/en/customer-stories):
  • Kyra's Bake Shop (USA, Oregon, small business): Square for online baked goods sales.
  • Focus on small businesses in the USA, Canada, Australia.
• Adyen (adyen.com/customers):
  • Spotify (Sweden/global, music): Adyen for subscriptions.
  • ASOS (UK, fashion): Adyen for global transactions.

Advantages:

• Accuracy: Data from the processors themselves, 100% reliable.
• Educational value: Case studies explain how stores use a processor (e.g. Stripe for subscriptions or PayPal for secure transactions).
• Regional Coverage: Easy to find stores in US, EU, Asia.

Flaws:

• Limited to large or well-known brands.
• Not all processors (e.g. Braintree) publish complete lists.

Educational aspect:

• Technologies: Explore processor APIs (e.g. Stripe API for custom checkouts).
• Business Analysis: Analyze why major brands choose a particular processor (e.g. Adyen for multi-currency).
• Practice: Try finding 5 stores on stripe.com/customers and compare their integrations (subscriptions vs. one-time payments).

2. Use international price aggregators and shopping platforms​

Why it works: Aggregators index millions of stores and often provide filters by payment method or display processors in checkout details.

Steps:

1. Choose an international aggregator (not a local one, for example, not Yandex.Market).
2. Enter your query: "[product] accept [processor]" (for example, "laptops accept PayPal").
3. Use filters by region (USA, UK, EU) or payment method, if available.
4. If there is no filter, check the store pages (processor icons in the footer or on the payment page).

Examples of aggregators:

• Bing Shopping (shopping.bing.com):
  • Query: "sneakers accept PayPal site:.com -site:.ru".
  • Results: Zappos (US, shoes), ASOS (UK, fashion), Foot Locker (US, sports).
  • Filters: Select a region (North America, Europe) or category (Fashion, Electronics).
• PriceGrabber (pricegrabber.com):
  • Focus: USA, filter "PayPal accepted".
  • Example: Best Buy (USA, electronics) with PayPal in checkout.
• Shopzilla (shopzilla.com):
  • Query: "Stripe powered stores electronics".
  • Results: Indie stores on Shopify (US/EU), often with Stripe.
• eBay or Amazon:
  • Filter: "Sellers accepting PayPal" or "Stripe via Shopify Payments".
  • Example: Small sellers on eBay (US/EU) with PayPal.

Advantages:

• Scale: Access to thousands of stores.
• Practicality: Compare prices, reviews and payment methods.
• Real time: Data is updated daily.

Flaws:

• Not all stores clearly indicate the processor.
• Less coverage for niche processors (eg Adyen).

Educational aspect:

• Marketing: Analyze how processors affect conversion (for example, PayPal increases trust by 20-30% according to research).
• UX/UI: Study how stores display processors (footer icons, custom forms).
• Practice: Compare 3 aggregators (Bing Shopping, PriceGrabber, Shopzilla) by the number of stores found for Stripe.

3. Alternative search engines with advanced operators​

Why it works: Engines like DuckDuckGo and Bing scan website footers (which often say "Powered by Stripe") or checkout pages, which list processors.

Steps:

1. Use DuckDuckGo (duckduckgo.com) or Bing (bing.com).
2. Enter your query with operators:
   • "intitle:thenline store [processor]" (например, "intitle:thenline store Stripe").
   • "accept [processor] site:.com -site:.ru" (for the USA, excluding the Russian Federation).
   • "powered by [processor] ecommerce" (например, "powered by Stripe ecommerce").
3. Check the results, focusing on international domains (.com, .co.uk, .eu).
4. For accuracy, add the category: "fashion stores accept PayPal".

Examples:

• DuckDuckGo: "online stores accept Stripe site:.com -site:.ru".
  • Results: Gumroad (US, digital goods), Teespring (globally, merch).
• Bing: "ecommerce sites using PayPal internationally -site:.ru".
  • Results: Udemy (US/global, education), Threadless (US, merch).
• Startpage (startpage.com): Google proxy with anonymity, the query "Stripe powered stores fashion" will find stores on Shopify (e.g. Allbirds, USA).

Advantages:

• Flexibility: Operators allow you to narrow your search.
• Privacy: DuckDuckGo and Startpage do not track your searches.
• Availability: Free and fast.

Flaws:

• Results may be "noisy" (filtering required).
• Requires skills in working with operators.

Educational aspect:

• Informational search: Operators like "site:" or "intitle:" teach you how to perform a specific search.
• Analysis: Compare DuckDuckGo and Bing results by relevance.
• Practice: Create 5 queries to search for PayPal stores and test them.

4. Social networks and professional communities​

Why it works: Users and businesses share store lists, recommendations, and case studies in real time on platforms like X (Twitter), Reddit, and forums.

Steps:

1. On X (twitter.com):
   • Search: "[processor] stores list" or "#[processor]Merchants" (e.g. #StripeMerchants).
   • Follow processor accounts (@Stripe, @@paypal ).
2. On Reddit:
   • Subreddits: r/ecommerce, r/smallbusiness, r/fintech.
   • Query: "List of online stores using Stripe in USA" or "PayPal shops Europe".
3. On forums:
   • Sites like Quora or Stack Overflow (e-commerce sections).
   • Query: "What stores use Adyen for payments?".

Examples:

• X: Tweets from @Stripe mentioning stores, such as Figma (US, design) or Deliveroo (EU, delivery).
• Reddit: In r/ecommerce, posts about Stripe stores, such as Patreon (US) or Substack (US, content).
• Quora: Answers to questions like "Which European stores use Adyen?" with examples (Spotify, Zalando).

Advantages:

• Relevance: Real reviews and lists from users.
• Community: Opportunity to ask clarifying questions.
• Diversity: Finds include niche shops.

Flaws:

• Subjectivity: Requires data verification.
• Not systematized: Need to search manually.

Educational aspect:

• Communications: Teaches how to interact with professional communities.
• Critical Thinking: Requires filtering out unreliable sources.
• Practice: Find a Reddit thread about Stripe and analyze the stores mentioned.

5. Web Analysis Tools (for Advanced Users)​

Why it works: Services like BuiltWith or SimilarTech scan website technologies, including payment processors, and provide domain lists.

Steps:

1. Sign up at BuiltWith.com, SimilarTech.com, or Wappalyzer.com.
2. Enter a processor (e.g. "Stripe") into the technology search.
3. Filter by:
   • Category: "E-commerce".
   • Region: "USA", "Europe", "Asia-Pacific".
   • Business type: "Online Store".
4. Export the list of domains and check them manually (visit the sites, examine the footer or checkout).
5. Alternative: Install the WhatRuns Chrome extension to analyze technologies on specific websites.

Examples:

• BuiltWith:
  • Search: "Stripe E-commerce USA".
  • Results: Notion (US, productivity), Figma (global, design), Glossier (US, cosmetics).
• SimilarTech:
  • Search: "PayPal Online Stores Europe".
  • Results: Zalando (Germany, fashion), Boohoo (UK, fashion).
• WhatRuns:
  • Visit a website (like allbirds.com) and you'll see "Stripe" in the technology stack.

Advantages:

• Scale: Access millions of websites.
• Accuracy: Data is based on code scanning.
• Flexibility: Filters by region and industry.

Flaws:

• Requires a subscription for full access (free limits available).
• Ethical for public data only.

Educational aspect:

• Web Analysis: Teaches you how to understand the technology stack of websites.
• Programming: You can write a script to parse BuiltWith data through their API.
• Practice: Find 10 stores on BuiltWith with Stripe and compare their industries.

Recommendations for the application of methods​

1. Combine approaches:
   • Start with official directories (e.g. stripe.com/customers) to be on the safe side.
   • Use aggregators (Bing Shopping) for volume.
   • Check social media (Reddit, X) for niche finds.
   • For in-depth analysis, use BuiltWith.
2. Ethical use:
   • Use data to study technology, marketing, or cybersecurity.
   • Do not use for fraud, spam or other illegal activities.
   • Check that the data is from public sources.
3. Practical steps for learning:
   • Select a processor (e.g. PayPal).
   • Find 5 stores using each method (directories, aggregators, search, social networks, BuiltWith).
   • Analyze: Which industries (fashion, electronics, SaaS)? Which regions? How does the processor affect UX?
4. Automation tools:
   • For advanced users: Write a Python script using the BuiltWith or SimilarTech APIs to collect bulk data.
   • Example: requests.get("https://api.builtwith.com/v21/api.json?key=YOUR_KEY&lookup=stripe").

Specific store examples (2025)​

Processor	Shop	Region	Industry	Why does it use a processor?
Stripe	Glossier	USA	Cosmetics	Quick checkout, subscriptions
PayPal	ASOS	UK/EU	Fashion	Purchase protection, multi-currency
Adyen	Spotify	Globally	Music	Global subscriptions
Square	Blue Bottle Coffee	USA	Food/drinks	Small business, online orders
Braintree	Uber	Globally	Transport	Custom payments