This Superpages scraper tutorial shows how to turn a keyword and location search into a CSV of business leads with the UScraper local desktop app. You will import the workflow, change the search target, choose an export path, run the pagination loop, and validate the output before using it for research or outreach planning.
Before you start
Prerequisites and compliance guardrails
You need UScraper installed as a local desktop app, a Superpages keyword and location you are allowed to research, and a folder where the CSV can be written. Start with a narrow test such as one service category and one ZIP code. Do not begin with a nationwide category crawl.
Use the Superpages Scraper for Business Listings as the download path for the workflow JSON. The template page is the source of truth for the importable bundle, while this article explains how to run and check it.
Superpages is a local business directory, so the data can look easy to collect. That does not make every use case acceptable. Review the current Superpages Terms of Use, respect access controls and robots guidance, avoid aggressive repeated runs, and get legal review before selling, republishing, or contacting exported leads.
Treat the CSV as governed business data. Keep the run date, search URL, purpose, and reviewer notes beside the export so a teammate can audit where each row came from.
Workflow map
What the Superpages scraper actually does
The bundled JSON defines a browser automation graph rather than a black-box scraper API. It opens a Superpages search URL for search_terms=supermarket and geo_location_terms=95136, waits for listing cards, exports fields from each result row, checks whether a usable Next link exists, and loops until pagination ends.
| Workflow block | Role in the run | What to check |
|---|---|---|
| Set Window Size | Uses a stable viewport before the page loads | Keep the default unless cards wrap strangely. |
| Navigate | Opens the configured keyword and location search | Replace both URL parameters for your market. |
| Wait for Page Load | Gives Superpages time to render results | Increase only after a failed test run. |
| Wait for Element | Looks for listing card selectors | Verify cards appear before export. |
| Structured Export | Appends one row per result card | Confirm file path, filename, and headers. |
| Element Exists + Click | Follows enabled pagination | Stop if the site shows verification or unusual pages. |
{
"project": {
"name": "Superpages Details Page Scraper Cloud"
},
"blocks": [
{
"title": "Navigate",
"config": {
"url": "https://www.superpages.com/search?search_terms=supermarket&geo_location_terms=95136"
}
},
{
"title": "Structured Export",
"config": {
"rowSelector": ".search-results .result, .organic .result, div.result, article.result",
"fileName": "superpages-listing-scraper.csv",
"includeHeaders": true,
"fileMode": "append"
}
},
{
"title": "Element Exists",
"config": {
"selector": "a.next:not(.disabled):not([aria-disabled=\"true\"]), a[rel=\"next\"]:not(.disabled):not([aria-disabled=\"true\"])"
}
}
]
}
Pick the right lane
UScraper, Octoparse, Apify, or a data scraper API?
Best when an analyst wants a reviewable CSV, local file custody, and editable selectors without standing up scraping infrastructure.
The practical question is not "what is the best Superpages scraper?" for every team. It is whether your current job is a supervised CSV export, a recurring production pipeline, or a purchased data feed. For a first market study, UScraper keeps the workflow visible enough that non-developers can inspect the page and the row side by side.
Runbook
How to scrape Superpages leads to CSV
Import the template
Open the Superpages scraper template, download the hosted JSON, and import it into UScraper.
Edit the search target
In Navigate, replace supermarket and 95136 with your approved keyword and location. Keep the URL structure intact so the result page loads predictably.
Set the export folder
In Structured Export, change the save location. Keep superpages-listing-scraper.csv for the first run so teammates recognize the default output.
Run one page first
Execute a small test, then open the CSV and compare each row against the visible Superpages cards before letting pagination continue.
Scale with the Next loop
When page-one rows look correct, let Element Exists find the enabled Next link, click through, wait for cards, and append the next page.
Validate the Superpages data extraction
Open the CSV next to the browser after the first run. Filter for blank business_name, telephone, address, and website values. Some blanks are normal because not every listing exposes every field, but repeating blanks across a full page usually means a selector or wait needs attention.
| CSV symptom | Likely cause | Fix |
|---|---|---|
| Empty business names | Cards did not render before export | Increase the wait or rerun one page. |
| Missing phone numbers | The listing card lacks a phone or uses a changed selector | Compare against the visible card and adjust only if the value exists. |
| Duplicate businesses | Sponsored units or repeated categories overlap | Dedupe on name plus phone or name plus address. |
| Blank websites | Superpages did not expose an outbound link | Keep the blank or enrich later from the detail URL. |
| Pagination stops early | Next control is disabled, hidden, or changed | Inspect the current page before editing the click selector. |
Do not treat the export as ready just because the file exists. A useful lead CSV needs row-level confidence: business names should match the directory, contact fields should be plausible, and the source detail URL should let another person verify the record.
FAQ
Superpages scraper tutorial FAQ
Superpages listing data may be visible in a browser, but automated collection can still be limited by terms of use, robots rules, anti-abuse controls, privacy law, database rights, and outreach regulations. Review the official terms, avoid bypassing restrictions, and get legal review before commercial lead generation or resale.