# Dasoertliche Email Scraper (`email_scraper/dasoertliche-email-scraper`) Actor

Dasoertliche Email Scraper extracts publicly indexed email addresses from Dasoertliche using targeted keywords, location filters, custom email domains, and exclusion terms. Build structured contact datasets for business research, lead discovery, and contact analysis.

- **URL**: https://apify.com/email\_scraper/dasoertliche-email-scraper.md
- **Developed by:** [Email Scraper](https://apify.com/email_scraper) (community)
- **Stats:** 2 total users, 1 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

### Dasoertliche Email Scraper

Dasoertliche Email Scraper is an Apify Actor designed to extract publicly indexed email addresses associated with Dasoertliche search results using targeted keywords and email-domain filters. It returns structured contact records containing the search keyword, result title, description, URL, and matching email address.

You can provide multiple search terms, optionally narrow the search by country, state, or city, and specify the email domains you want to find, such as `@gmail.com`, `@yahoo.com`, or `@outlook.com`. An exclusion filter is also available when you want to skip descriptions containing particular words or phrases.

The Actor is useful for business research, contact discovery, market research, dataset creation, and other workflows that require structured Dasoertliche contact information.

### What Is the Dasoertliche Email Scraper?

The Dasoertliche Email Scraper searches for Dasoertliche pages relevant to your keywords and looks for email addresses matching the configured domain suffixes. Results are collected into an Apify dataset in a consistent table structure.

The workflow is straightforward:

- **Input:** Search keywords, optional location, email-domain suffixes, an email target, and optional exclusion terms.
- **Search:** The Actor searches for relevant publicly indexed Dasoertliche results based on those settings.
- **Filtering:** Results can be narrowed by location, email domain, and exclusion terms.
- **Output:** Matching email addresses are returned with their associated keyword, title, description, and URL.

Multiple keywords and multiple email domains can be supplied in one run, making the Actor suitable for broader contact research.

### Key Features

| Feature                      | Description                                                              | User Benefit                                                                 |
| ---------------------------- | ------------------------------------------------------------------------ | ---------------------------------------------------------------------------- |
| Keyword-based search         | Search Dasoertliche using one or multiple keywords or queries.           | Target specific businesses, industries, services, or topics.                 |
| Multiple keywords            | Provide a list of search terms in one run.                               | Expand research coverage without separate runs.                              |
| Location filtering           | Optionally specify a country, state, or city.                            | Focus results on a geographic area.                                          |
| Custom email domains         | Search for specific email-domain suffixes.                               | Target Gmail, Yahoo, Outlook, company domains, and other configured domains. |
| Per-combination email target | Set a maximum number of emails for each keyword + domain combination.    | Control the depth of each search combination.                                |
| Exclusion filtering          | Skip descriptions containing configured words or phrases.                | Reduce unwanted matches in the resulting dataset.                            |
| Duplicate prevention         | Previously collected email addresses are not added again during the run. | Keep the resulting email collection cleaner.                                 |
| Structured dataset           | Results contain keyword, title, description, URL, and email.             | Make collected contact data easier to review and process.                    |
| Incremental results          | Matching records are added to the dataset during processing.             | Results become available as the run progresses.                              |

### What Data Can You Extract?

The Dasoertliche Email Scraper returns five user-facing fields for each collected result.

The data is centered on the relationship between a search keyword, a Dasoertliche result, and a matching email address.

The available information includes:

- **Keyword** — The keyword or query that produced the result.
- **Title** — The title associated with the indexed search result.
- **Description** — The available search-result description containing the matching contact information.
- **URL** — The URL associated with the result.
- **Email** — The extracted email address matching one of your configured domain suffixes.

This structure provides both the contact address and contextual information about where the address was found.

### Why Use This Actor?

Finding contact information manually can require repeatedly searching different business terms, locations, and email domains. The Dasoertliche Email Scraper turns those repetitive searches into a configurable Actor run.

You can combine several targeted keywords with several email domains. This allows you to organize searches around different business categories, professional terms, services, or geographic targets.

The structured dataset also makes the resulting information easier to review than collecting individual search results manually.

The Actor can be particularly useful when your research requires a combination of:

- Dasoertliche business discovery
- Keyword-based contact research
- Email-domain targeting
- Geographic search refinement
- Structured contact datasets
- Repeatable search workflows

### Benefits

The Dasoertliche Email Scraper provides several practical benefits for contact and business research.

- **Automated collection** — Reduce repetitive manual searching across Dasoertliche-related queries.
- **Flexible targeting** — Combine different keywords with different email-domain suffixes.
- **Geographic refinement** — Add a location when your research is focused on a particular area.
- **Structured records** — Keep contact information together with its title, description, URL, and keyword.
- **Exclusion controls** — Avoid collecting emails from descriptions containing unwanted terms.
- **Scalable keyword research** — Process multiple search terms within one Actor run.
- **Dataset creation** — Build structured contact datasets for later review and analysis.
- **Duplicate reduction** — The Actor avoids adding the same email address more than once during collection.

### How to Use the Dasoertliche Email Scraper

A typical run requires only a few configuration steps.

1. Enter one or more keywords in the `keywords` field.
2. Optionally enter a country, state, or city in `location`.
3. Add the email domains you want to search for in `customDomains`.
4. Set `maxEmails` according to the desired collection target.
5. Optionally add words or phrases to `excludeWords`.
6. Start the Actor.
7. Review the resulting dataset containing the collected email records.

For initial testing, use a small number of keywords and a modest email target. Once the results match your research needs, you can broaden the search with additional keywords, domains, or locations.

### Input

The Actor accepts a JSON object with one required field and four configurable fields.

The `keywords` field is required. The other fields are optional and use their documented defaults when not provided.

#### Input Fields

| Field           | Type             | Required | Default                         | Description                                                                                   |
| --------------- | ---------------- | -------- | ------------------------------- | --------------------------------------------------------------------------------------------- |
| `keywords`      | Array of strings | Yes      | `["Unternehmen", "Restaurant"]` | Keywords or search queries to use for finding relevant Dasoertliche results.                  |
| `location`      | String           | No       | `""`                            | Optional country, state, or city used to narrow the search.                                   |
| `customDomains` | Array of strings | No       | `["@gmail.com"]`                | Email-domain suffixes to search for.                                                          |
| `maxEmails`     | Integer          | No       | `5`                             | Maximum target per keyword + domain combination. Valid range is 1–10,000 in the Actor schema. |
| `excludeWords`  | Array of strings | No       | `[]`                            | Words or phrases that cause matching descriptions to be skipped.                              |

The `keywords` array can contain multiple specific searches. More focused phrases can help distinguish different types of businesses or professionals.

The `location` field can be left empty when you do not want to apply a geographic filter.

The `customDomains` field controls which email suffixes the Actor searches for. For example, you can provide `@gmail.com`, `@yahoo.com`, `@outlook.com`, or another domain suffix.

The `maxEmails` value applies independently to each keyword + domain combination. For example, three keywords and two domains create six keyword/domain combinations, with the configured target applied separately to each combination.

For free users, the Actor applies a maximum collection limit of 100 emails. The input schema itself permits `maxEmails` values from 1 through 10,000.

The `excludeWords` filter is case-insensitive. A single word is matched as a whole word, while a phrase is matched as a phrase. When a description matches an exclusion term, the entire result description is skipped for email extraction.

### Input Example

```json
{
  "keywords": [
    "Restaurant",
    "Restaurant Besitzer",
    "Hotel",
    "Unternehmen"
  ],
  "location": "Berlin",
  "customDomains": [
    "@gmail.com",
    "@yahoo.com",
    "@outlook.com"
  ],
  "maxEmails": 10,
  "excludeWords": [
    "crypto",
    "onlyfans"
  ]
}
```

This example searches several business-related terms in Berlin and checks for three email-domain suffixes while excluding descriptions containing the specified terms.

### Output

The Actor stores collected results in the **Dasoertliche Emails Dataset**.

Each result contains five user-facing fields. The records are designed to preserve enough search context to understand the source of each email address.

| Field         | Description                                                                                        |
| ------------- | -------------------------------------------------------------------------------------------------- |
| `keyword`     | The keyword or query associated with the collected result.                                         |
| `title`       | The title of the Dasoertliche search result.                                                       |
| `description` | The available description or snippet associated with the result.                                   |
| `url`         | The URL associated with the search result.                                                         |
| `email`       | The email address extracted from the result description that matches the configured domain suffix. |

The `email` field is the primary contact value, while `keyword`, `title`, `description`, and `url` provide context for the result.

The Actor also prevents duplicate email addresses from being added repeatedly during collection, so the dataset is focused on unique email values.

### Output Example

```json
{
  "keyword": "Restaurant",
  "title": "Example Restaurant",
  "description": "Example Restaurant in Berlin ... contact@example.com ...",
  "url": "https://www.dasoertliche.de/...",
  "email": "contact@example.com"
}
```

The exact title, description, URL, and email values depend on the publicly indexed search results available for your selected keywords, locations, and email domains.

### Use Cases

The Dasoertliche Email Scraper can support several research and data-collection workflows.

- **Business research** — Find contact information associated with businesses matching specific search terms.
- **Local market research** — Use the location field to focus research on cities, states, or countries.
- **Lead research** — Identify publicly indexed email addresses connected to relevant business searches.
- **Industry research** — Search multiple industry-specific keywords to create targeted datasets.
- **Contact discovery** — Search for matching email domains across relevant Dasoertliche results.
- **Market segmentation** — Separate searches by business type, service, location, or keyword.
- **Dataset creation** — Build structured email datasets for analysis and research.
- **Competitive research** — Collect publicly indexed contact information associated with selected business categories.
- **Business intelligence workflows** — Use keyword, title, description, URL, and email together as research context.
- **Automation workflows** — Run repeatable searches without manually checking individual search results.

The Actor is intended for structured research and collection of publicly indexed information rather than guaranteeing that every business or search result contains an email address.

### Competitive Advantages

Several configuration features make the Actor adaptable to different contact-research requirements.

First, the keyword array allows you to organize multiple searches in one run. Instead of relying on a single broad term, you can use more specific combinations such as business categories, professional roles, or service-related phrases.

Second, custom email domains let you decide which email suffixes matter to your research. This is useful when you want to focus on a particular type of address.

Third, the optional location field provides geographic targeting without requiring a separate Actor configuration for every area.

Finally, exclusion terms provide another layer of control when particular descriptions should not contribute email addresses to the dataset.

### Advantages

The main practical advantages include:

- Multiple keyword searches in a single run.
- Multiple configurable email-domain suffixes.
- Optional geographic filtering.
- Configurable email collection targets.
- User-defined exclusion terms.
- Structured output with contextual search information.
- Duplicate email prevention.
- Incremental dataset results.

These capabilities allow the same Actor to support both narrow research tasks and broader keyword-based contact collection.

### Limitations

There are several important considerations when using the Actor.

- Results depend on publicly indexed information available through the search process.
- A keyword may produce fewer emails than the configured target.
- A requested `maxEmails` value is a target limit, not a guarantee that that many addresses exist.
- Narrow keywords or locations can produce sparse results.
- Exclusion terms can intentionally remove otherwise matching results.
- Only email addresses matching the configured domain suffixes are collected.
- Free users are subject to a 100-email collection ceiling applied by the Actor.
- Search availability and indexed descriptions can vary, so some searches may return partial or empty results.

For these reasons, a smaller result count does not necessarily indicate an input error. It may simply mean that fewer matching publicly indexed email addresses were available.

### Pros and Cons

| Pros                            | Cons                                                    |
| ------------------------------- | ------------------------------------------------------- |
| Supports multiple keywords      | Narrow searches may return few results                  |
| Supports multiple email domains | Only configured email-domain suffixes are collected     |
| Optional location targeting     | Results depend on publicly indexed information          |
| Exclusion filtering             | Exclusion terms can remove matching descriptions        |
| Structured dataset output       | A configured target does not guarantee that many emails |
| Duplicate email prevention      | Free users have a 100-email collection ceiling          |

### Comparison With Alternative Approaches

| Capability               | Dasoertliche Email Scraper     | Manual / Typical Alternative                      |
| ------------------------ | ------------------------------ | ------------------------------------------------- |
| Keyword-based searching  | Supported                      | Usually performed manually                        |
| Multiple keywords        | Supported                      | Requires repeated searches or manual organization |
| Email-domain targeting   | Supported                      | Often requires checking results individually      |
| Location filtering       | Supported                      | Can be applied manually during research           |
| Exclusion terms          | Supported                      | Usually handled manually                          |
| Structured output        | Dataset fields for each result | May require manual collection and formatting      |
| Duplicate prevention     | Supported during collection    | Often requires manual cleanup                     |
| Repeatable configuration | Supported through Actor input  | Usually requires repeated manual setup            |

This comparison describes workflow differences rather than claiming that one approach is universally better.

### Best Practices

For better-controlled research runs, consider the following practices:

- Use several specific keywords instead of relying only on one broad term.
- Combine related search phrases when researching different business categories.
- Add a location when geographic targeting is important.
- Use several relevant email domains when broader contact coverage is required.
- Start with a smaller `maxEmails` value to validate your search strategy.
- Use `excludeWords` only for terms you genuinely want to remove.
- Review sample results before increasing the scope of a run.
- If results are sparse, broaden the keywords or remove an unnecessarily restrictive location.
- Use company-specific email domains when those domains are relevant to your research.
- Remember that `maxEmails` controls the collection target; it does not guarantee the availability of matching addresses.

### Troubleshooting

#### Invalid Input

Check that `keywords` is provided as an array of strings. Verify that `customDomains` and `excludeWords` are also supplied as arrays when you use them.

For `maxEmails`, use an integer between 1 and 10,000 according to the input schema.

#### Empty Results

Try broader or more specific keywords depending on the research objective. If a location is specified, temporarily remove it to determine whether the geographic filter is restricting the search.

You can also review the email-domain configuration. If only one uncommon domain is selected, fewer matching addresses may be available.

#### Partial Results

Partial results can occur when the available indexed information does not contain enough matching email addresses to reach the configured target. The Actor may also encounter fewer useful results for a particular keyword or domain.

#### Missing Fields

The available title, description, and URL information depends on the corresponding indexed search result. Review the returned record and consider broadening the search terms if the dataset does not contain enough useful context.

#### Excluded Results

If an expected result is missing, check `excludeWords`. Any configured exclusion term that matches a description causes that description to be skipped for email extraction.

#### Free-User Limit

If you are using the free tier, the Actor applies a maximum of 100 collected emails. A higher requested target can therefore be reduced by the Actor's free-tier restriction.

### Frequently Asked Questions

#### What does the Dasoertliche Email Scraper do?

The Dasoertliche Email Scraper searches for publicly indexed Dasoertliche results using your keywords and extracts email addresses that match your configured email-domain suffixes.

#### What data does the Actor return?

Each dataset record contains `keyword`, `title`, `description`, `url`, and `email`.

#### Can I use multiple keywords?

Yes. The `keywords` field accepts an array of search terms or queries. Using several specific terms can broaden your research coverage.

#### Can I search a specific city or country?

Yes. The optional `location` field accepts a country, state, or city and can be used to narrow the search.

#### Can I search multiple email domains?

Yes. The `customDomains` field accepts an array of email-domain suffixes. The default is `@gmail.com`.

#### How does `maxEmails` work?

The configured target is applied independently to each keyword + domain combination. It is a target for each combination, not a guarantee that the requested number of addresses will be available.

#### Can I exclude certain results?

Yes. Add words or phrases to `excludeWords`. Matching is case-insensitive, and descriptions containing an exclusion term are skipped for email extraction.

#### Does the Actor guarantee the requested number of emails?

No. `maxEmails` controls the desired collection target, but the Actor can only collect matching email addresses that are available in the relevant indexed results.

#### Why did I receive fewer emails than expected?

The search may be too narrow, the selected location may restrict results, the configured email domain may have limited matches, or the available indexed results may not contain enough matching addresses.

#### Can I use the Actor for automated research workflows?

Yes. The Actor accepts structured configuration and produces a structured Apify dataset, making it suitable for repeatable data-collection and research workflows.

#### What should I do before a large run?

Start with a small test using a few targeted keywords, one or more relevant email domains, and a modest `maxEmails` value. Review the resulting records before expanding the search.

### NLP Keywords

- Dasoertliche email extraction
- Dasoertliche contact data
- Dasoertliche business search
- Dasoertliche email addresses
- Dasoertliche leads
- German business directory
- business email discovery
- email contact extraction
- keyword-based email search
- public contact information
- structured contact data
- business directory data
- local business research
- location-based business search
- email domain filtering
- contact dataset creation
- business lead research
- search result extraction
- Dasoertliche profiles
- email research automation

### Related Keywords

- Dasoertliche email scraper
- Dasoertliche contact scraper
- Dasoertliche business scraper
- Dasoertliche email extractor
- Dasoertliche lead scraper
- Dasoertliche data extraction
- Dasoertliche business email finder
- Dasoertliche email finder
- German business email scraper
- German directory email scraper
- business directory email extraction
- local business email finder
- business contact data scraper
- public business email extraction
- keyword email scraper Germany
- location-based email scraper
- business lead data extraction
- email domain scraper
- German business contact research
- Dasoertliche contact data extraction

### Final Overview

Dasoertliche Email Scraper provides a configurable way to search publicly indexed Dasoertliche information for email addresses associated with targeted keywords and selected email domains.

You can combine multiple keywords, optional geographic targeting, custom email-domain suffixes, collection targets, and exclusion terms to shape the research process. The resulting dataset keeps each email together with its keyword, title, description, and URL.

For the most useful results, begin with specific but sufficiently broad search terms, test your configuration with a small target, and expand the keyword, domain, or location scope when additional coverage is needed.

The Actor is designed around a simple input-to-dataset workflow, making it suitable for structured contact research, business discovery, market research, and dataset creation based on publicly indexed Dasoertliche information.

*Contact me:* <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": [
    "Unternehmen",
    "Restaurant"
  ],
  "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": [
        "Unternehmen",
        "Restaurant"
    ],
    "location": "",
    "customDomains": [
        "@gmail.com"
    ],
    "excludeWords": []
};

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

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

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,email_scraper/dasoertliche-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/jIXVa8OafGAbaMJB8/builds/AYJAtYLrgahjt4QWx/openapi.json