# Walmart Email and Phone Number Scraper (`neuro-scraper/walmart-email-and-phone-number-scraper`) Actor Walmart Email and Phone Number Scraper SD - Walmart Email and Phone Number Scraper is a lead generation tool that extracts leads with public contact emails and phone numbers and profile URLs from Walmart by keyword, location, email domain and country - Walmart email and phone number extractor. - **URL**: https://apify.com/neuro-scraper/walmart-email-and-phone-number-scraper.md - **Developed by:** [Neuro Scraper](https://apify.com/neuro-scraper) (community) - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $2.49 / 1,000 results This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event ## What's an Apify Actor? An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md. ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run. For examples already wired to this Actor's own input schema, see the [API](#api) section below. Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`). # README ### Walmart Email and Phone Number Scraper **Walmart Email and Phone Number Scraper** turns a keyword into a contact sheet of emails and phone numbers published on Walmart. Give it search terms and it returns the accounts that publish a way to reach them, with the account name, handle and profile URL beside each contact. It reads only what Walmart and Google already show a signed-out visitor. No login, no cookies, no private or partner API, no browser and no JavaScript rendering. *** ### What the Walmart Email and Phone Number Scraper does The Walmart Email and Phone Number Scraper searches Google with a contact dork rather than a plain keyword: `site:walmart.com seller "@gmail.com" and whatsapp "+44"`. That asks for the pages which already publish a email address or phone number, instead of every page matching a word. Each result block yields the account and the email address or phone number together, in one request. Google no longer prints the target URL on most layouts, so the handle comes from what it does print: the "Walmart - handle" site label, the breadcrumb, or a `Name (@handle)` title. Every row is written to the dataset the moment it is found and logged as it is written, so a run is readable while it is still going. Phone numbers are validated by libphonenumber against the real numbering plan of the country you searched, so order numbers, dates and follower counts cannot reach the dataset. Each number is returned in E.164 form and in the national format its country uses. Addresses are normalised before matching, so `name [at] domain [dot] com`, spaced and full-width forms are all recovered. Placeholders such as `email@`, `yourname@` and `noreply@` are dropped, and so are prose words that only look like an address. *** ### Input reference for the Walmart Email and Phone Number Scraper | Field | Type | Default | Meaning | |---|---|---|---| | `keywords` | array | `seller, marketplace` | Search terms - a niche, job title or industry. | | `location` | string | `""` | Added to every query, e.g. `New York`. | | `customDomains` | array | `@gmail.com`, `@yahoo.com` | Address domains the search asks for, and a filter on what is kept. | | `countries` | array | US, UK, India | Which countries' numbers to look for. Name, ISO code or dial code. Each one multiplies the searches. | | `maxEmails` | integer 1-10000 | `20` | Stop once this many unique contacts are found. | | `expandQueries` | boolean | `true` | Search each keyword in several phrasings. | | `queryModifiers` | array | per platform | Extra words combined with each keyword. | | `maxPagesPerQuery` | integer 1-50 | `30` | Google result pages per query. | | `maxConcurrency` | integer 1-20 | `5` | Queries run in parallel. | | `countryCode` | string | `""` | Two-letter country for the search proxy. | ### Output Every row the Walmart Email and Phone Number Scraper writes: | Field | Meaning | |---|---| | `network` | Platform name | | `keyword` | The keyword that found this row | | `query` | The exact Google query used | | `email` | The public email address found | | `emailDomain` | Domain part of that address | | `possiblyTruncated` | True when Google cut the snippet mid-address | | `phone` | The number in E.164 form, e.g. `+447590574946` | | `phoneNational` | The same number as its country writes it | | `phoneCountry` | ISO country the number belongs to | | `accountName` | Account label as the platform shows it | | `fullName` | Display name where published | | `username` | Handle | | `profileUrl` | Canonical profile URL | | `url` | The page the result pointed at | | `description` | The result snippet, cleaned | | `foundAt` | ISO 8601 UTC timestamp | ```json { "network": "Walmart", "keyword": "seller", "accountName": "examplestudio", "fullName": "Example Studio", "username": "examplestudio", "profileUrl": "https://www.walmart.com/seller/examplestudio", "email": "hello@examplestudio.com", "phone": "+447590574946", "phoneNational": "07590 574946", "phoneCountry": "GB" } ``` ### How to use the Walmart Email and Phone Number Scraper 1. Put your search terms in **Keywords** - the niche, job title or industry you sell to. 2. Add a **Location** if the list should be local. 3. Pick the **Countries** whose numbers you want. Every number is validated against that country's numbering plan. 4. Set **Max results** to cap the run, then start it. 5. Export the dataset as CSV, JSON or Excel, or pull it through the Apify API. ### Use cases **Lead generation.** Build a list of Walmart accounts in one niche that publish a email address or phone number, with the handle and profile URL for context before you write. **Recruiting.** Find people describing themselves with a role keyword and reach them on the contact they chose to publish. **Agency prospecting.** Search a niche and a city, and get a prospect sheet with the account and the contact side by side. **CRM enrichment.** Feed `profileUrl` and `email` and `phone` straight into your CRM; the `keyword` and `query` columns record where each row came from. ### Limitations, stated plainly - Only contacts already published in public Walmart pages indexed by Google. Nothing hidden from a signed-out visitor is reachable, and none is guessed from a name. - Coverage depends on what Google has indexed, so a narrow niche returns fewer rows than a broad one. Raising **Max pages per query** and adding keywords helps. - The free Apify plan caps a run at 20 results. - A number written without its country code can only be validated against the country you searched, so search the countries you actually sell to. ### Pricing Pay per result: you are charged for each row written to the dataset, and nothing for a run that finds nothing. Platform and proxy costs are included in that price. ### Walmart Email and Phone Number Scraper vs manual research Done by hand, one qualified contact takes two to four minutes: find the account, open it, read the page, copy the email or phone number, paste it into a sheet. The Walmart Email and Phone Number Scraper does the same work continuously, with no tab switching and no transcription errors. A hundred records is minutes rather than an afternoon. It also captures what manual research usually skips. The account name, the profile URL and the exact keyword that surfaced the row all land in the same record. That context turns a raw list into a prioritised one. The Walmart Email and Phone Number Scraper lets you sort and filter before a single message is written. ### Using the Walmart Email and Phone Number Scraper in a workflow Most teams run the Walmart Email and Phone Number Scraper on a schedule and treat the dataset as a feed rather than a one-off export. Point a webhook at your own endpoint and each finished run pushes its rows straight into your CRM, with no manual download step. The stable output schema matters here. Because every row from the Walmart Email and Phone Number Scraper has identical keys, your integration never needs to handle a missing field. A common pattern is a nightly keyword run feeding a dedupe step. Another is enrichment: widen the keyword list and let the Walmart Email and Phone Number Scraper fill the gaps in an existing sheet. #### Troubleshooting the Walmart Email and Phone Number Scraper **Few or no rows.** The keyword is probably too broad or too narrow. Ten specific keywords beat one generic one, and adding a location raises the hit rate. **Rows without contacts.** That is normal - most accounts publish none. The Walmart Email and Phone Number Scraper reports only what is genuinely on the page. **The run is slow to start.** Lower the concurrency. The Walmart Email and Phone Number Scraper is querying faster than the proxy pool is comfortable with. **Fewer results than requested.** Google caps one query at roughly 300 results. Query expansion is what reaches past that ceiling, so leave it on. #### How the Walmart Email and Phone Number Scraper handles export and integration Export the Walmart Email and Phone Number Scraper dataset as CSV, JSON, Excel or XML from the Apify console, or pull it through the API. Every field is flat - no nested objects - so the CSV opens cleanly in Excel or Google Sheets without a parsing step. ### Related Actors | Actor | What it collects | |---|---| | [Walmart Email Scraper](https://apify.com/leads-scraper/walmart-email-scraper) | Public contact emails from Walmart | | [Walmart Phone Number Scraper](https://apify.com/neuro-scraper/walmart-phone-number-scraper) | Public phone numbers from Walmart | | [AliExpress Email Scraper](https://apify.com/neuro-scraper/aliexpress-email-scraper) | Public contact emails from AliExpress | | [Allegro Email Scraper](https://apify.com/neuro-scraper/allegro-email-scraper) | Public contact emails from Allegro | | [Amazon Email Scraper](https://apify.com/leads-scraper/amazon-email-scraper) | Public contact emails from Amazon | | [Best Buy Seller Email Scraper](https://apify.com/leads-scraper/best-buy-seller-email-scraper) | Public contact emails from Best Buy | | [BigCommerce Store Email 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No. It reads public search results and public Walmart pages only. #### Where do the emails and phone numbers come from? From the public page the search result points at - the same text any visitor can read. #### Are the numbers real? Every number is checked against its country's numbering plan before it is written, so invalid strings are dropped rather than shipped. #### Can I run it on a schedule? Yes, with Apify Schedules. Progress is saved, so a migrated run continues instead of starting over. **Something is missing or wrong.**\ Email . ### More about the Walmart Email and Phone Number Scraper Because the Walmart Email and Phone Number Scraper reads only pages Google has already indexed, it never needs a login, a cookie jar or an API key from the platform it reads. Run the Walmart Email and Phone Number Scraper with a narrow keyword set first. A short test run shows the yield of a niche before a large run is paid for. Output from the Walmart Email and Phone Number Scraper is flat - no nested objects - so a CSV export opens cleanly in Excel or Google Sheets with no parsing step. Pair the Walmart Email and Phone Number Scraper with Apify Schedules to rebuild a prospect list weekly and catch accounts that published contact details since the last run. Proxy and platform costs are already inside the per-result price of the Walmart Email and Phone Number Scraper, so the figure quoted on the Store page is the figure you pay. Every field the Walmart Email and Phone Number Scraper returns is documented in the output table above, and the schema does not change between runs or between platforms. #### Walmart Email and Phone Number Scraper at a glance Teams that outgrow manual prospecting usually reach for the Walmart Email and Phone Number Scraper first, because it needs no setup beyond a keyword list and a result cap. Concurrency on the Walmart Email and Phone Number Scraper is adjustable, so a run can be tuned for speed on a quiet network or for reliability on a busy one. If a run of the Walmart Email and Phone Number Scraper is interrupted, Apify migrates it and progress resumes rather than restarting from the first query. Agencies commonly schedule the Walmart Email and Phone Number Scraper weekly, then diff each dataset against the last to surface only newly published contacts. Nothing in the Walmart Email and Phone Number Scraper guesses a contact from a name pattern. A value is written only when it appears on the page itself. Because the Walmart Email and Phone Number Scraper shares its output schema with every other scraper in this catalogue, a pipeline built once works across all of them. #### Walmart Email and Phone Number Scraper in practice A first run of the Walmart Email and Phone Number Scraper is the cheapest market research available: it shows how many reachable accounts a niche actually contains before any budget is committed. ### Leave a review If the Walmart Email and Phone Number Scraper saved you time, please leave a star rating and a short review on the Walmart Email and Phone Number Scraper page. Reviews are how other buyers judge whether a tool works, and they tell us which features to build next. If something did not work, email instead - bugs get fixed faster than they get complained about. ### Support Questions, bugs or a custom build: . # Actor input Schema ## `keywords` (type: `array`): Search terms describing the Walmart accounts you want (niche, job title, industry). ## `location` (type: `string`): Optional location phrase added to every query (e.g. "New York"). ## `customDomains` (type: `array`): Only emails ending with one of these domains are collected. With or without the leading @. Each domain is searched separately, so more domains means more results but a longer run - remove some for a faster, narrower search, or add your own (e.g. @company.com). ## `countries` (type: `array`): Which countries' phone numbers to look for. The search asks Google for that country's dial code, and every number found is validated against that country's real numbering plan. Country name, ISO code or dial code all work. Each extra country multiplies the number of searches. ## `maxEmails` (type: `integer`): Stop once this many unique contacts have been collected. ## `maxEmailResults` (type: `integer`): How many of the results should be email addresses. Leave at 0 to split "Max results" evenly between emails and phone numbers. ## `maxPhoneResults` (type: `integer`): How many of the results should be phone numbers. Leave at 0 to split "Max results" evenly. If one type runs out first, the other takes the remaining budget. ## `countryCode` (type: `string`): Two-letter country code for the search proxy (e.g. US, GB, DE). Empty for any. ## `expandQueries` (type: `boolean`): Search each keyword x domain pair with several phrasings. Recommended - Google caps a single query at ~300 results. ## `queryModifiers` (type: `array`): Extra words combined with each keyword when Expand queries is on. Tuned for Walmart. ## `maxPagesPerQuery` (type: `integer`): Google rarely returns more than ~30 pages for one query. ## `maxConcurrency` (type: `integer`): How many queries run in parallel. ## Actor input object example ```json { "keywords": [ "seller", "marketplace" ], "location": "", "customDomains": [ "@gmail.com", "@yahoo.com" ], "countries": [ "United States", "United Kingdom", "India" ], "maxEmails": 20, "maxEmailResults": 0, "maxPhoneResults": 0, "countryCode": "", "expandQueries": true, "queryModifiers": [ "email", "contact", "wholesale", "customer service", "inquiries" ], "maxPagesPerQuery": 30, "maxConcurrency": 5 } ``` # Actor output Schema ## `results` (type: `string`): Records produced by Walmart Email and Phone Number Scraper, stored in the run's default dataset. # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "keywords": [ "seller", "marketplace" ], "location": "", "customDomains": [ "@gmail.com", "@yahoo.com" ], "countries": [ "United States", "United Kingdom", "India" ], "countryCode": "", "queryModifiers": [ "email", "contact", "wholesale", "customer service", "inquiries" ] }; // Run the Actor and wait for it to finish const run = await client.actor("neuro-scraper/walmart-email-and-phone-number-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "keywords": [ "seller", "marketplace", ], "location": "", "customDomains": [ "@gmail.com", "@yahoo.com", ], "countries": [ "United States", "United Kingdom", "India", ], "countryCode": "", "queryModifiers": [ "email", "contact", "wholesale", "customer service", "inquiries", ], } # Run the Actor and wait for it to finish run = client.actor("neuro-scraper/walmart-email-and-phone-number-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}") for item in client.dataset(run.default_dataset_id).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "keywords": [ "seller", "marketplace" ], "location": "", "customDomains": [ "@gmail.com", "@yahoo.com" ], "countries": [ "United States", "United Kingdom", "India" ], "countryCode": "", "queryModifiers": [ "email", "contact", "wholesale", "customer service", "inquiries" ] }' | apify call neuro-scraper/walmart-email-and-phone-number-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "type": "http", "url": "https://mcp.apify.com/?tools=fetch-actor-details,neuro-scraper/walmart-email-and-phone-number-scraper" } } } ``` The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer ` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations). ## OpenAPI specification Download the OpenAPI definition: https://api.apify.com/v2/actors/oSRkaqOM2NCWHBIJn/builds/HegYQp7jcA2heRbNP/openapi.json