# Yahoo Email Scraper (`email_scraper/yahoo-email-scraper`) Actor

Yahoo Email Scraper extracts publicly indexed email addresses from Yahoo Japan search results using targeted keywords, locations, and custom email domains. Build structured lead lists with deduplication, exclusions, and per-keyword/domain result targets.

- **URL**: https://apify.com/email_scraper/yahoo-email-scraper.md
- **Developed by:** [Email Scraper](https://apify.com/email_scraper) (community)
- **Stats:** 77 total users, 76 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $1.49 / 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

### 🔹 Yahoo Email Scraper – Overview

Yahoo Email Scraper is an Apify Actor built to turn targeted search keywords into a structured list of publicly indexed email contacts associated with Yahoo Japan pages. It is designed for lead research, prospect discovery, market research, directory building, and other workflows where you need contact data from public Yahoo-related results.

Yahoo Email Scraper accepts keywords, an optional location, email-domain suffixes, a maximum email target, and optional exclusions. It searches for matching public results, checks visible result descriptions for email addresses that match the selected domains, and stores unique email records in an Apify dataset.

> **💡 Key Features**
>
> - Keyword-driven Yahoo email discovery
> - Optional country, state, or city filtering
> - Multiple email-domain suffixes in one run
> - Per keyword + domain collection targets
> - Exclude-word filtering for result descriptions
> - Duplicate email suppression
> - Incremental dataset output
> - Resume support after an interrupted run
> - Structured lead records with keyword, title, description, URL, and email

Yahoo Email Scraper is useful when you want to guide contact discovery with specific search intent. For example, `Fitness Coach`, `Fitness Trainer`, `Online Fitness Coach`, and `Fitness Influencer` can explore different result patterns than one generic term.

The easiest Yahoo Email Scraper workflow is simple: enter targeted keywords, optionally add a location and domain suffixes, choose a maximum target, and run it. Results appear incrementally in the dataset.

### 🔍 Yahoo Email Scraper – Key Features

Yahoo Email Scraper combines flexible targeting with structured output controls. Its inputs are intentionally simple, so you can start with a small test and expand coverage when the search terms produce useful public results.

#### 🎯 Keyword-based Yahoo email extraction

The required `keywords` field accepts a list of search terms or queries. Multiple specific phrases are recommended because they can uncover different businesses, professionals, roles, or topics associated with publicly indexed Yahoo pages.

A strong keyword plan mixes broad terms with role, service, industry, or niche variations. For example: `Japanese business`, `Japanese company`, `manufacturer`, and `supplier`.

#### 🌍 Optional location targeting

The `location` field lets you narrow the search by a country, state, or city. Leaving it blank removes the geographic filter and allows broader discovery.

Location targeting is useful for a defined market. Adding a city can sharpen a service search; removing the location can broaden sparse results.

#### 📧 Multiple email domains

The `customDomains` field accepts multiple domain suffixes such as `@gmail.com`, `@yahoo.com`, or `@outlook.com`. The Actor checks extracted text against the domains you provide.

This makes Yahoo Email Scraper adaptable to different prospecting strategies. You can focus on consumer-style addresses, business-domain addresses, or several providers in one run.

#### 🔢 Per-keyword + domain targets

`maxEmails` controls how many emails the Actor aims to collect for each keyword and domain combination. This is not a single run-wide target.

For example, with 3 keywords, 2 email domains, and a limit of 20, the Actor works through 6 keyword-domain combinations and can target up to 20 emails for each combination, subject to publicly discoverable results and duplicate filtering.

#### 🚫 Exclude-word filtering

The `excludeWords` field can remove unwanted result snippets before email extraction. If a supplied word or phrase appears in a profile description snippet, that snippet is skipped.

Single words are matched case-insensitively as whole words, while phrases are matched case-insensitively within the text. Leaving the list empty keeps all otherwise eligible snippets.

#### ♻️ Deduplication and resume support

Yahoo Email Scraper tracks emails already seen and avoids adding the same email more than once. It also persists progress during the run, helping it resume from its saved position after an interruption.

This is especially useful for larger keyword and domain matrices where a run may need to process many combinations.

### 📊 Yahoo Email Scraper – What Data You Can Extract

Each collected lead is stored as a structured dataset record. Public result information is kept together with the extracted email so you can understand which keyword produced the lead and where the information came from.

> **📦 Output / Data Fields**
>
> | Field         | Description                                               |
> | ------------- | --------------------------------------------------------- |
> | `network`     | Network label stored with the result                      |
> | `keyword`     | Keyword used for the search combination                   |
> | `title`       | Title of the matching result                              |
> | `description` | Description or visible snippet associated with the result |
> | `url`         | URL of the matching result                                |
> | `email`       | Unique email address extracted from the result text       |

The Yahoo Email Scraper dataset view is organized for lead review and displays the key research fields as a table, including the keyword, title, description, URL, and email.

#### 🧾 Yahoo Email Scraper sample output

```json
{
  "network": "Yahoo.com",
  "keyword": "Japanese business",
  "title": "Example Company",
  "description": "Business profile text with contact example@gmail.com",
  "url": "https://example.com/profile",
  "email": "example@gmail.com"
}
```

The example above shows the output structure. Actual values depend entirely on the public results found for your keywords, domains, location, and exclusion settings. Yahoo Email Scraper does not guarantee that every keyword will produce an email or that the requested target will always be reached.

> **📌 Important:** An email address is included only when it can be extracted from eligible public result text and matches one of your selected domain suffixes. Yahoo Email Scraper does not invent missing contact information.

### ⚙️ Yahoo Email Scraper – How to Use It

Running Yahoo Email Scraper requires only a few input decisions. Start narrow enough to understand result quality, then expand coverage when needed.

#### 1️⃣ Add targeted keywords for Yahoo Email Scraper

Enter one or more search terms in `keywords`. Specific combinations generally provide clearer intent than a single broad term.

Examples:

```text
Fitness Coach
Fitness Trainer
Online Fitness Coach
Japanese business
Manufacturer
Supplier
```

Use phrases that describe the people, businesses, services, products, or niches you are researching with Yahoo Email Scraper.

#### 2️⃣ Add a location when needed

Enter a country, state, or city in `location`. Keep it blank when you want to search without geographic narrowing.

```text
Japan
Tokyo
Osaka
```

A location can improve focus, but an overly narrow location may reduce the number of eligible public results.

#### 3️⃣ Select email domains

Use `customDomains` to define the email suffixes you care about.

```json
[
  "@gmail.com",
  "@yahoo.com",
  "@outlook.com"
]
```

Adding more domains expands the keyword-domain combinations processed by the Actor.

#### 4️⃣ Set the email target

`maxEmails` accepts values from 1 to 10,000, with a default of 5. The target applies independently to each keyword + domain combination.

Smaller targets are useful for quick validation. Higher targets are useful when you need deeper exploration and the search space contains enough public results.

#### 5️⃣ Add exclusions when necessary

Use `excludeWords` to remove snippets containing terms you do not want.

```json
[
  "crypto",
  "onlyfans"
]
```

This can help narrow the output to more relevant lead contexts.

#### 6️⃣ Start the run and review the dataset

After a Yahoo Email Scraper run begins, results are pushed incrementally into the dataset. Review the keyword, title, description, URL, and email fields to validate relevance before using the data in another workflow.

### 🔎 How to scrape emails from Yahoo by keyword

The practical way to use Yahoo Email Scraper is to treat keyword selection as the main targeting layer. Instead of relying on one broad query, create a small group of closely related search phrases that describe the same market from different angles.

For example, a local services research project could use `plumber`, `plumbing company`, `commercial plumber`, and `emergency plumber`. A professional research project could combine a role with an industry or service.

> **🔍 Search Strategy Tip**
>
> - Start with 3–5 closely related keywords
> - Use specific roles, services, products, or industries
> - Add a location only when geography matters
> - Test 1–3 relevant email domains first
> - Broaden terms when results are sparse
> - Remove the location filter when geographic targeting is too restrictive

When a Yahoo Email Scraper run reaches fewer emails than expected, the input configuration is usually the first place to improve. Broader keywords, additional relevant domains, or a wider location can increase coverage without changing the core workflow.

### 🧩 Can you use Yahoo Email Scraper for B2B lead research?

Yes. Yahoo Email Scraper can support B2B lead research when the relevant contact email addresses are present in public result descriptions and match the domains you selected.

Useful keyword patterns include company types, industries, services, professional roles, suppliers, manufacturers, agencies, and local business categories. You can combine these with a geographic term for market-specific research.

For B2B workflows, company-domain suffixes can also be relevant, such as `@company.com`.

Keep in mind that Yahoo Email Scraper only returns what is publicly discoverable through eligible result text. It should be treated as a public-data discovery tool, not as a guarantee that every company or professional has a visible email address.

### 🚀 Yahoo Email Scraper – Use Cases

> **🗂️ Use Cases**
>
> - B2B prospect discovery
> - Company and supplier research
> - Local business lead research
> - Niche market research
> - Professional contact discovery
> - Email list building from public sources
> - Competitive and industry research
> - Search-driven lead enrichment
> - Keyword-based prospect segmentation

You can start with one niche and a few keywords, validate the records, and then expand the keyword-domain combinations.

Because each row preserves the originating keyword, results can be grouped later by search intent.

### 📝 Yahoo Email Scraper – Input

The required input is `keywords`. The other fields are optional, with defaults defined by the Actor.

> **⚙️ Input Configuration**
>
> | Field           | Type    | Default                            | Purpose                                 |
> | --------------- | ------- | ---------------------------------- | --------------------------------------- |
> | `keywords`      | Array   | `["Japanese business", "company"]` | Search keywords or queries              |
> | `location`      | String  | `""`                               | Optional country, state, or city        |
> | `customDomains` | Array   | `["@gmail.com"]`                   | Email suffixes to collect               |
> | `maxEmails`     | Integer | `5`                                | Target per keyword + domain combination |
> | `excludeWords`  | Array   | `[]`                               | Terms that exclude matching snippets    |

#### 📄 Yahoo Email Scraper sample input

```json
{
  "keywords": [
    "Fitness Coach",
    "Fitness Trainer",
    "Online Fitness Coach"
  ],
  "location": "Japan",
  "customDomains": [
    "@gmail.com",
    "@yahoo.com"
  ],
  "maxEmails": 20,
  "excludeWords": [
    "crypto"
  ]
}
```

Yahoo Email Scraper accepts `maxEmails` from 1 through 10,000. Free users are limited to a maximum of 100 collected emails by the implementation, while paid users do not have that result-limit restriction.

### 📦 Yahoo Email Scraper – Output

Yahoo Email Scraper stores structured records in an Apify dataset. The stored records include the network label, originating keyword, result title, description, URL, and extracted email.

The dataset view provides a convenient tabular representation for reviewing the collected leads and their source context.

### 💰 Yahoo Email Scraper – Pricing

Yahoo Email Scraper's configuration does not publish a fixed monetary price in the supplied files, so no invented price is included here.

> **💳 Pricing Behavior**
>
> - `maxEmails` determines the requested result target.
> - Free users have a 100-email maximum applied by the Actor.
> - Paid users are not subject to that free-tier result ceiling.
> - The target is applied per keyword + domain combination.
> - A higher target does not guarantee that enough public emails exist.

For Yahoo Email Scraper, use the smallest target that is sufficient for your research objective, then increase it when the search produces enough relevant public data.

### 🛠️ Yahoo Email Scraper – Tips and Best Practices

> **✅ Tips**
>
> - Prefer several specific keywords over one very broad keyword.
> - Mix role names, business types, services, and industry terms.
> - Add a location for regional prospecting; remove it when coverage is too small.
> - Add multiple relevant email domains to expand discovery.
> - Use exclusions to remove unwanted categories from snippets.
> - Start with a small `maxEmails` value to test relevance.
> - Expect fewer results when the public indexed data is sparse.
> - For broad runs, use an appropriate run timeout in Apify Run options; the configured default is 3600 seconds.

The Actor stops a keyword-domain search when available results become unproductive, result pages remain empty, or repeated retrieval failures occur.

With Yahoo Email Scraper, result quality depends heavily on your search inputs. Better keywords can be more useful than simply raising the email target.

### ❓ Yahoo Email Scraper – Frequently Asked Questions

#### 🔹 What is Yahoo Email Scraper?

Yahoo Email Scraper is an Apify Actor that discovers email addresses from publicly indexed Yahoo-related result pages using user-defined keywords and optional filters.

#### 🔹 What keywords should I use for Yahoo Email Scraper when building a lead list?

Use specific phrases describing the people, businesses, industries, services, or products you want to research. Multiple related terms are recommended because each keyword creates its own search path.

#### 🔹 Can Yahoo Email Scraper search Yahoo emails by country or city?

Yes. Enter a country, state, or city in the `location` field. Leave it empty when you want broader geographic coverage.

#### 🔹 Can Yahoo Email Scraper collect Gmail and Yahoo addresses together?

Yes. Add multiple suffixes in `customDomains`, such as `@gmail.com`, `@yahoo.com`, and `@outlook.com`. Each keyword-domain combination is processed independently.

#### 🔹 How does the maxEmails limit work?

The limit applies per keyword + domain combination. With 2 keywords, 3 domains, and `maxEmails` set to 10, the Actor can target up to 10 addresses for each of the 6 combinations, subject to available public results and duplicate filtering.

#### 🔹 Why did Yahoo Email Scraper return fewer emails than requested?

A Yahoo Email Scraper target is not a guarantee. The Actor stops when available results become unproductive or when other stopping conditions are reached. Broader keywords, more relevant domains, or a wider location can improve coverage.

#### 🔹 Does the Actor remove duplicate email addresses?

Yes. Yahoo Email Scraper tracks previously seen emails and avoids storing the same email address more than once.

#### 🔹 What happens when I use excludeWords?

Any result description containing a matching excluded word or phrase is skipped, so emails found in that snippet are not collected.

#### 🔹 What data does Yahoo Email Scraper output?

Collected records contain `network`, `keyword`, `title`, `description`, `url`, and `email`. The dataset view highlights the principal lead fields for convenient review.

#### 🔹 Is the Yahoo Email Scraper output guaranteed to contain valid business contacts?

No. The Actor extracts emails that are publicly present in eligible result text. You should validate and review leads before using them for outreach or other downstream purposes.

### 📞 Yahoo Email Scraper – Support

Yahoo Email Scraper is designed to provide a straightforward keyword-to-email workflow for public lead discovery. Start with focused search phrases, validate the initial output, and expand your keyword, location, and domain settings according to the quality and volume of results.

- contact me by email :  <alphascraper69@gmail.com>

# Actor input Schema

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

A list of keywords or queries to search for.

## `location` (type: `string`):

Optional country, state or city used to narrow the search. Leave it empty to search without a geographic filter.

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

List of custom email domains

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

How many addresses each search keyword + domain suffix combination may collect before the finder moves on to the next one. This is a per-combination target, not a run-wide total: with 3 keyword and 2 Domains and a limit of 20, the run works through all 6 combinations and aims for up to 20 addresses in each, so up to 120 overall. Lower values finish sooner and cost less; higher values dig deeper but never guarantee a fuller result, since the run can only find what is publicly listed.

## `excludeWords` (type: `array`):

Words or phrases you do not want to see.

## Actor input object example

```json
{
  "keywords": [
    "Japanese business",
    "company"
  ],
  "location": "",
  "customDomains": [
    "@gmail.com"
  ],
  "maxEmails": 5,
  "excludeWords": []
}
```

# 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": [
        "Japanese business",
        "company"
    ],
    "location": "",
    "customDomains": [
        "@gmail.com"
    ],
    "excludeWords": []
};

// Run the Actor and wait for it to finish
const run = await client.actor("email_scraper/yahoo-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": [
        "Japanese business",
        "company",
    ],
    "location": "",
    "customDomains": ["@gmail.com"],
    "excludeWords": [],
}

# Run the Actor and wait for it to finish
run = client.actor("email_scraper/yahoo-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": [
    "Japanese business",
    "company"
  ],
  "location": "",
  "customDomains": [
    "@gmail.com"
  ],
  "excludeWords": []
}' |
apify call email_scraper/yahoo-email-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,email_scraper/yahoo-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/OA5H9cYZ5HUl4UAtu/builds/UROuMS0ieEaK2OQ5q/openapi.json