# Walmart Email Scraper - Keyword & Location Targeting (`scrapido/walmart-email-scraper`) Actor

🏬 Walmart Email Scraper extracts marketplace seller and supplier emails by keyword and location. 🔓 Custom domain filters plus decoding and dedup. 📤 Export Walmart leads to CSV, JSON or Excel for retail vendor outreach.

- **URL**: https://apify.com/scrapido/walmart-email-scraper.md
- **Developed by:** [Scrapido](https://apify.com/scrapido) (community)
- **Categories:** Lead generation, E-commerce, Automation
- **Stats:** 2 total users, 1 monthly users, 0.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $2.50 / 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.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
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.
Actors are written with capital "A".

## 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.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

### Walmart Email Scraper

**Walmart Email Scraper** is an Apify actor that automates extracting public email addresses and basic profile context from Walmart, helping you solve the biggest pain point in lead research: time-consuming manual contact hunting. If you’re a marketer, recruiter, or data team building a **Walmart lead generation** list, this **Walmart email extractor** accelerates scale and improves ROI—fast.

***

### What is Walmart Email Scraper? 🔍

**Walmart Email Scraper** is an automated web scraping tool on Apify designed to extract email addresses from Walmart based on your inputs. It works as a **Walmart contact scraper** that pulls public contact emails plus profile context, so you don’t waste hours doing manual research. A **Walmart email scraper** is built for people who need volume, consistency, and structure—especially marketers, recruiters, sales teams, and analysts who want **Walmart lead generation** outcomes without spreadsheet chaos. With Walmart Email Scraper, you can generate export-ready results for thousands of contacts in minutes, then segment them for outreach, enrichment, or analysis.

***

### What Data Does a Walmart Email Scraper Collect? 📊

This **Walmart email scraper** collects contact emails and supporting profile details from Walmart listings discovered using your keywords and filters. The dataset also stores discovery context so you can trace why a record appeared in your results.

| Data Category | Fields Extracted | Description |
|---|---|---|
| Contact | `email` | Public email address associated with the result |
| Identity | `title` | Profile name, business title, or role shown in the result |
| Context | `description` | Profile bio or summary text (as provided in the source) |
| Discovery | `keyword` | The keyword that surfaced this record in your run |
| Navigation | `url` | Link to the Walmart page for reference |
| Location | `location` | Profile-listed location text (when available) |

***

### What Do Results from a Walmart Email Scraper Look Like? 👀

Each result is a structured JSON record saved to your Apify dataset. Here's a real example:

```json
{
  "keyword": "manager",
  "title": "Alex Rivera",
  "description": "Creative Director at Studio Co. | Available for freelance",
  "url": "https://walmart.com/alexrivera",
  "email": "alex@studioco.com",
  "location": "Los Angeles, CA"
}
```

Your dataset is stored in Apify’s Dataset tab and can be exported as JSON (default) and CSV via Apify Console.

***

#### Core Features: Walmart Email Scraper ⚡

| Feature | Benefit |
|---|---|
| ✅ Keyword-driven targeting | Use keywords to focus your Walmart email scraper on the audience you care about |
| ✅ Location filter | Add a `location` filter when you need region-specific results |
| ✅ Custom email domain filtering | Use `customDomains` to restrict emails to domains like `@gmail.com`, `@yahoo.com`, or your preferred list |
| ✅ Configurable result cap | Control runtime and cost using `maxEmails` (the scraper stops once the limit is reached) |
| ✅ Proxy support | Built-in proxy support helps keep scraping stable for larger batches |
| ✅ Real-time dataset saving | Results are pushed incrementally to the dataset as they’re found |
| ✅ Structured dataset output | Clean records with consistent fields for CRM import and analysis |
| ✅ Works on publicly available data | Collects email addresses and profile context from publicly available sources |

***

### Getting Started with Walmart Email Scraper 🚀

1. **Open Apify Store** — Go to [apify.com/store](https://apify.com/store) and search **Walmart Email Scraper**
2. **Click Try for Free** — Sign in or create a free Apify account
3. **Open the Input Tab** — Configure your scraping parameters
4. **Add Keywords** — Enter keywords (e.g., roles like `manager`, `founder`) that describe your target contacts
5. **Set Optional Filters** — Add `location` and/or `customDomains` to narrow results
6. **Cap Your Results** — Use `maxEmails` to limit how many emails you want to collect
7. **Click Start** — Launch the run and monitor logs
8. **Access Your Data** — Open the Dataset tab and export your results as needed

First results typically start appearing quickly, and the run can scale depending on your keyword coverage and `maxEmails`.

***

### Ways to Use Walmart Email Scraper 💡

- 🎯 **B2B Lead Generation** — Build a Walmart email list for outreach and prospecting
- 📣 **Email Marketing** — Source Walmart contact emails for campaigns and drip sequences
- 🔬 **Market Research** — Analyze which roles or business titles surface more contact information
- 📊 **CRM Enrichment** — Add extracted emails and profile context to your existing pipelines
- ⚙️ **Data Pipelines** — Automate regular Walmart contact discovery for ongoing research

***

#### Input Parameters — Walmart Email Scraper

Below is the actor input your run will accept.

```json
{
  "keywords": ["manager", "founder"],
  "location": "",
  "customDomains": ["@gmail.com", "@yahoo.com"],
  "maxEmails": 20
}
```

| Parameter | Type | Required | Default | Description |
|---|---|---|---|---|
| `keywords` | Array | ✅ Yes | — | Keywords used to find relevant Walmart results (e.g., job titles like `manager`, `founder`) |
| `location` | String | No | `""` | Optional location text to filter results |
| `customDomains` | Array | No | `["@gmail.com","@yahoo.com"]` | Restrict results to emails that match these domains |
| `maxEmails` | Integer | No | `20` | Maximum number of emails to collect; helps control run time and scraping cost |

***

#### Output Parameters — Walmart Email Scraper

The dataset fields below are saved in the order defined by the actor’s Dataset view.

```json
{
  "keyword": "manager",
  "title": "Alex Rivera",
  "description": "Creative Director at Studio Co. | Available for freelance",
  "url": "https://walmart.com/alexrivera",
  "email": "alex@studioco.com"
}
```

| Field | Label | Format | Description |
|---|---|---|---|
| `keyword` | Keyword | text | The keyword that was used to discover this result |
| `title` | Title | text | The title or name shown for the matched profile |
| `description` | Description | text | Profile description text (bio/summary as available) |
| `url` | Url | link | Direct link to the Walmart page for this record |
| `email` | Email | text | Extracted public email address |

***

### Why Choose This Walmart Email Scraper? 🏆

Compared with generic approaches, **Walmart email scraper** runs are built for structured lead generation with practical controls. Walmart Email Scraper focuses on email harvesting from publicly available sources, offers `maxEmails` to control spend, and saves records directly into a dataset for easy export. You also get proxy support for more reliable scraping at scale. If you need help or have a custom requirement, reach out via <scrapidocontact@gmail.com>.

***

### How Many Results Can You Scrape? 📈

Use `maxEmails` to set a cap from 1 up to 10,000. Actual volume depends on how many Walmart results match your keywords and how many of those include public emails that fit your `customDomains`. Runs can collect fewer than your cap if fewer matching emails are available. Results are stored in Apify’s dataset so you can export anytime after the run completes.

***

### Legal Guidelines for Scraping Walmart ⚖️

Walmart Email Scraper collects information only from **publicly available sources**. It does not access private pages or authenticated content. You’re responsible for complying with applicable laws and regulations (including GDPR/CCPA where relevant), platform terms, and rules around email outreach and spam. Use the extracted data for legitimate business purposes only. For data-removal requests, contact <scrapidocontact@gmail.com>.

***

### FAQ — Walmart Email Scraper ❓

#### How does the Walmart Email Scraper identify data?

The actor uses your provided `keywords` (optionally filtered by `location` and `customDomains`) to discover relevant Walmart pages, then extracts email addresses and associated profile context from publicly available content.

#### What Walmart profile types can I scrape?

You can scrape public Walmart profiles or pages that expose contact information openly. If a record doesn’t include a public email that matches your `customDomains`, it won’t appear as an email result.

#### How did the Walmart Email Scraper perform in our tests?

Performance depends on your keyword set, how many matching pages exist, and how consistently emails are published on those pages. In practice, narrower keywords and well-chosen domains often yield higher conversion to usable email contacts.

#### Why scrape Walmart for contacts?

Walmart hosts many business listings and pages where contact details may be published publicly. Automating discovery and extraction helps you build a Walmart lead generation list without spending days on manual research.

#### How much does the Walmart Email Scraper cost?

Apify usage is pay-per-result. You can control your spending by setting `maxEmails`—the run stops once the limit is reached (so you can cap ROI tightly before exporting).

#### How does the Walmart Email Scraper help my business?

It turns keyword research into a clean, dataset-based output of Walmart contact emails plus helpful context fields (`title`, `description`, and `url`) so you can enrich CRMs, power outreach campaigns, or support analysis.

#### What challenges should I expect when using the Walmart Email Scraper?

Not every page will have a publicly listed email, and results vary by niche, keyword specificity, and which email domains you request. If output seems low, broaden keywords, add related terms, or expand `customDomains`.

#### How do I choose a high-performing Walmart Email Scraper?

Choose runs that combine: targeted keywords, domain filtering via `customDomains`, a cost-controlled `maxEmails` cap, and stable scraping with proxy support—so your Walmart email scraper behaves reliably at scale.

***

### Conclusion 🏁

The **Walmart Email Scraper** is a fast, structured way to extract Walmart contact emails from publicly available sources. Whether you’re building a lead list, enriching your CRM, or launching targeted outreach, you can start with controlled inputs and export results from Apify right away.

***

### 🆘 Support & Feedback

Have a question or feature request for the Walmart Email Scraper?

- ✨ **Custom Solutions & Feature Requests:** Contact our team
- 📧 **Email:** <scrapidocontact@gmail.com>

### Multiple Email Types

**Email Types** replaces the old single Audience Type choice: select as many
kinds of mailbox as you want and the run chases all of them together.

| Type | What it matches |
| --- | --- |
| Personal / free webmail | Gmail, Outlook, Yahoo, iCloud, AOL, Proton, ... |
| Business / corporate | Company domains - free webmail and institutions excluded |
| Education (.edu / .ac) | `.edu`, `.ac.uk`, `.edu.au`, `.ac.in` and other academic suffixes |
| Government (.gov / .mil) | `.gov`, `.mil`, `.gov.uk`, `.gc.ca`, ... |
| Non-profit (.org) | `.org`, `.ngo`, `.org.uk`, ... |

Each selected type contributes its own Google dork patterns *and* its own domain
test, so a result is only kept if it genuinely belongs to the type that found
it. Every row carries an `emailType` field recording which one that was.

Suffixes are matched as real domain suffixes, so `cs.mit.edu` counts as
Education while `notedu.com` does not.

Setting **Custom Email Domains** still overrides everything: an explicit domain
list is a manual override and replaces the type-driven patterns. The legacy
`audienceType` value is still accepted, so saved inputs keep working.

# Actor input Schema

## `keywords` (type: `array`):

A list of keywords or queries to search for.

## `audienceType` (type: `string`):

Business Emails runs contextual discovery patterns tuned for company contact pages ("email us at", "contact@", careers, bookings, ...) and filters out consumer webmail domains. Consumer Emails instead searches gmail.com, yahoo.com, outlook.com, hotmail.com and icloud.com directly.

## `maxEmails` (type: `integer`):

Maximum number of emails to collect. The scraper will stop once this limit is reached. Setting a higher limit allows for more potential results but doesn't guarantee reaching that number. This helps save costs by controlling scraping time.

## `customDomains` (type: `array`):

Optional manual override — provide specific email domains to search for (e.g. @hubspot.com) instead of using Audience Type. Leave empty to use Audience Type.

## `emailTypes` (type: `array`):

Which kinds of mailbox to hunt for. Pick as many as you like - each type contributes its own set of Google search patterns and its own domain filter, and every result records the type it was found as. Personal = free webmail (Gmail, Outlook, Yahoo, iCloud). Business = company domains, excluding free webmail and institutions. Education = .edu / .ac.uk and friends. Government = .gov / .mil. Non-profit = .org.

## Actor input object example

```json
{
  "keywords": [
    "manager",
    "founder"
  ],
  "audienceType": "Consumer Emails",
  "maxEmails": 20,
  "customDomains": [],
  "emailTypes": [
    "Personal",
    "Business"
  ]
}
```

# Actor output Schema

## `dataset` (type: `string`):

No description

# 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 '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "keywords": [
        "manager",
        "founder"
    ],
    "customDomains": [],
    "emailTypes": [
        "Personal",
        "Business"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("scrapido/walmart-email-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 '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "keywords": [
        "manager",
        "founder",
    ],
    "customDomains": [],
    "emailTypes": [
        "Personal",
        "Business",
    ],
}

# Run the Actor and wait for it to finish
run = client.actor("scrapido/walmart-email-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": [
    "manager",
    "founder"
  ],
  "customDomains": [],
  "emailTypes": [
    "Personal",
    "Business"
  ]
}' |
apify call scrapido/walmart-email-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,scrapido/walmart-email-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 <APIFY_API_TOKEN>` 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/j9vSRYwUdMR2sH0JQ/builds/T3vpBwiwGtZy5Y7Pn/openapi.json