See who sends traffic to any website or checkout page
Every site that sends visitors to any domain or checkout page, with monthly visits, share and change. Find a competitor's affiliates and partners.
Every website has a short list of other sites that send it most of its visitors: the affiliates that review it, the partners that link to it, the directories and communities where people find it. For a competitor, that list is a ready-made plan of where to show up. For a checkout page, it is a list of who is selling. Lovely Router returns it for any domain in one API call: every referring site in the report, ranked by visits over the last six months, with each one's visits month by month, for $0.06 per site you look up.
Hand it to your AI agent
Copy this prompt into Claude Code, Cursor, Codex or any coding agent. It tells the agent where the docs are and how to use your API key.
See who sends traffic to any website or checkout page. Use the Lovely Router data tools: each returns JSON and is billed per result.
- Docs (read first): https://lovelyrouter.com/docs/tools/find.md and https://lovelyrouter.com/docs/tools/run.md
- Plan first: POST https://lovelyrouter.com/v1/tools/suggest with `{"task": "<my task in plain words>"}` (free). It returns the tools to run in order, each with an example `input`, the `input_required` fields, an estimated cost and a ready-made `run` request. Replace the example values with my task's; if a field is unclear, read the tool with GET https://lovelyrouter.com/v1/tools/<id>. To browse instead, POST https://lovelyrouter.com/v1/tools/discover searches the catalog.
- Show me the plan and its estimated cost (`total_est_cost_usd`) before running anything large.
- Run: POST https://lovelyrouter.com/v1/tools/<id>/run with `{"input": {...}, "max_results": N}`. A 200 has the finished run with `items`; a 202 means it is still running, so poll the `poll` path until `status` is `succeeded`, `failed`, `timed_out` or `stopped`.
- Only delivered results are billed. Keep max_results small on the first run, check the output, then scale up.
- If you support MCP, connect https://lovelyrouter.com/mcp instead (Streamable HTTP, same key; https://lovelyrouter.com/docs/tools/mcp.md) and use suggest_tools, get_tool and run_tool.
- Auth: read my API key from the LOVELY_API_KEY environment variable and send it as `Authorization: Bearer $LOVELY_API_KEY`. Never print or commit the key. If it is not set, ask me to create one at https://lovelyrouter.com/app/keys.
- Billing is prepaid: every call is charged to my balance, so test with a small request before running anything large.
- Every docs page is plain Markdown; the full index is https://lovelyrouter.com/llms.txt.
My task: <the inputs (links, keywords or accounts) and how many results you need>What you can find out
Look up a rival's domain and read down the list: the review sites, newsletters, marketplaces and partners that send it people. Each one is a site you can pitch, advertise on or partner with.
Hosted checkout pages have their own domains, such as checkout.stripe.com or a store's Gumroad or Lemon Squeezy checkout. The sites sending visitors there are the sites asking people to pay, ranked by how many they send.
Each row carries its visits for every month of the period, a change figure and a flag for new senders, so one run shows who is growing and who is fading. The run's report adds the site's own referral visits per month.
How it works
Pick the domain
A website (
example.com), a subdomain (app.example.com) or a checkout domain. A full URL works too: it is reduced to its host.Run the tool
Send it in
websitetoPOST /v1/tools/site-referrals/run. One run is one site and one call fee; a report can take a few minutes, so poll until it finishes.Read the referrers
The result is every referring site, largest first, 100 per page, each with its visits per month. Sort, filter by category or hand the list to a model to group it.
Look up a site's referrers with one request
Referral traffic sources takes one domain in website:
curl https://lovelyrouter.com/v1/tools/site-referrals/run \
-H "Authorization: Bearer $LOVELY_API_KEY" \
-H "content-type: application/json" \
-d '{"input": {"website": "checkout.stripe.com"}, "max_results": 1}'A run still going after 60 seconds returns 202; Run a tool explains polling and paging. Or skip the code: open the tool page, type a domain and run it from the browser.
What comes back
One row per referring site, largest first. Trimmed to three rows, a report for checkout.stripe.com looks like this:
{
"status": "succeeded",
"results": 1,
"charge_usd": 0.06,
"items": [
{ "domain": "higgsfield.ai", "visits": 9671010, "share_percent": 4.93, "change_percent": -8.5, "is_new": true,
"global_rank": 866, "category": "Computers Electronics and Technology", "period": "2026-04-01..2026-09-30" },
{ "domain": "paypal.com", "visits": 9175641, "share_percent": 4.68, "change_percent": -31.7, "is_new": false,
"global_rank": 71, "category": "Banking Credit and Lending", "period": "2026-04-01..2026-09-30" },
{ "domain": "app.emergent.sh", "visits": 1935343, "share_percent": 0.99, "change_percent": null, "is_new": false,
"global_rank": null, "category": "Games", "period": "2026-04-01..2026-09-30" }
],
"offset": 0,
"next_offset": 100
}| Field | What it means |
|---|---|
domain | The site sending visitors |
visits | Estimated visits it sent over the period |
share_percent | Its share of all referral visits the site received |
change_percent | How its visits changed, in percent (null when there is no earlier figure) |
is_new | True when the sender is new in this period |
global_rank | The sender's global traffic rank (null when unranked) |
category | The sender's site category |
period | The months the report covers |
monthly | Its visits for each month of the period, oldest first (null when the report has no monthly figures for that site) |
Example: tracing where AI products get paid
Cashflowing is one thing you can build on this tool. An AI agent ran site-referrals on 15 checkout pages, from Stripe Checkout to Gumroad, Paddle and Lemon Squeezy, and traced 982M checkout visits to 9,542 websites to show which AI products get paid. The case study explains the method, from choosing the checkouts to merging subdomains into sites.
The same approach works for any market where payments or sign-ups go through a shared domain: app stores, booking engines, ticketing pages, marketplaces.
Recipes
Look up three competitors, keep the sites that appear for two or more, and drop search engines and social networks. What is left are the affiliates, reviewers and directories in your niche. Website contacts finds an email for each.
Look up a checkout or marketplace domain and group the senders by category to see which kinds of sellers send the most buyers.
Sort by change_percent or filter is_new to find the sites that started sending traffic recently, before they show up anywhere else.
Store each month's rows with the date and diff them: a new affiliate or a lost partner shows up as a row that appears or disappears.
See whether a site's traffic comes from a few large senders or many small ones, and whether those senders are real sites in its market.
Prefer plain words? Connect the MCP server and tell Claude Code or Cursor: "Run site-referrals for competitor-a.com, competitor-b.com and competitor-c.com, drop search engines and social networks, and give me a table of the sites that send traffic to at least two of them."
What the numbers are, and what they are not
The figures are Similarweb's modelled estimates, not the site's own analytics, so use them to rank and compare senders rather than as exact counts. They count visits, not sales or revenue: a site that sends many people to a checkout is asking many people to pay, not necessarily getting paid. Very small sites may have few or no measured referrers.
Pair it with other traffic data
Which sites send traffic to any website or checkout page: every referrer over the last six months, ranked by visits, with each one's visits per month, share, change, new senders, rank and category. The run's report adds the site's total referral visits per month.
The websites a domain's visitors go on to, ranked by visits (Similarweb Pro referral report, last six months): visits, share, change, global rank, category and visits per month (monthly). Every destination site in the report; page with offset and limit (100 per page by default).
Estimated traffic for websites from Similarweb: monthly visits, ranks, traffic sources, top countries, engagement.
Crawl websites and extract emails, phone numbers and social profile links. One result = one website (up to 5 of its pages crawled, contacts merged).
Google results pages for a query: organic results (position, title, URL, snippet, date, sitelinks) and related searches. One result = one results page (~10 links).
site-outgoingis the reverse view: the sites a domain's visitors go to next.website-trafficgives a site's total monthly visits, rank, traffic sources and top countries, for up to 50 domains per run.website-contactsfinds emails and social links on the referring sites you want to reach.google-searchshows what a site ranks for in search, the other half of where its visitors come from.
For volume comparisons across a list of competitors, see competitor website traffic benchmarking.
What you pay
$0.06 per site you look up, whatever the size of its report: one call returns every referrer in the report, and reading the pages again is free. Starting a run holds that amount and the run settles when it finishes. A run that fails costs nothing.
There is no subscription and no monthly minimum: top up from $5, and one balance pays for data tools, models and the browser agent. Your first top-up is matched up to $5. Pricing lists every tool.
Frequently asked questions
How is this different from a backlink checker?+
A backlink checker lists pages that link to a site. This tool lists the sites that actually send it visitors, ranked by how many. A link nobody clicks doesn't show up here; a partner that sends thousands of visitors a month is near the top.
Can I look up a checkout page, not just a website?+
Yes. Pass the checkout's own domain, such as checkout.stripe.com. Subdomains are looked up as they are, so checkout.stripe.com and stripe.com give different reports.
How far back does the data go?+
Each report covers the last six months, and every row has its visits for each of those months; the period field gives the exact dates. To follow a site further, run it again each month and keep the results.
How accurate are the visit counts?+
They are modelled estimates. They are good for ranking senders and spotting changes, less so for exact counts, and they measure visits, not revenue.
Do I need a Similarweb account?+
No. You send a domain with your Lovely Router API key and get JSON back.
Do I need a subscription?+
No. You add credit to a prepaid balance and each lookup draws it down. A run that fails costs nothing, and nothing renews automatically.
Researching a market more broadly? See lead generation, ad intelligence and the tool catalog.