# Quora Email Scraper (`email_scraper/quora-email-scraper`) Actor

Quora Email Scraper extracts publicly available email addresses from Quora-related search results using targeted keywords, locations, and custom email domains. Build structured Quora leads with emails, titles, descriptions, and URLs for lead generation, prospect research, and market research.

- **URL**: https://apify.com/email\_scraper/quora-email-scraper.md
- **Developed by:** [Email Scraper](https://apify.com/email_scraper) (community)
- **Categories:**
- **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?

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

### Quora Email Scraper – Overview

**Quora Email Scraper** is an Apify Actor designed to discover publicly listed email addresses associated with Quora search results. It accepts targeted keywords, optional geographic terms, selected email domains, and exclusion words, then returns structured lead information containing the keyword, result title, description, URL, and matching email address.

The **Quora Email Scraper** is useful for lead generation, prospect research, market research, audience discovery, B2B research, influencer research, recruiting research, and other workflows where publicly available Quora-related contact information is relevant.

Rather than relying on a single broad search term, you can provide multiple focused queries such as `fitness coach`, `fitness trainer`, `fitness influencer`, or `online fitness coach`. This gives the **Quora Email Scraper** more search combinations to work with.

> 💡 **What does the Quora Email Scraper do?**
> It searches for Quora-related results using your keywords and optional location, identifies publicly visible email addresses matching your selected email domains, and saves each unique result as structured dataset data.

The easiest workflow is simple: enter your keywords, optionally add a location, choose email domains such as `@gmail.com`, set the maximum number of emails, and run the Actor.

***

### Quora Email Scraper – Key Features

The **Quora Email Scraper** provides configurable search and filtering options while keeping the final dataset easy to analyze.

> 🚀 **Key Features**
>
> - Search Quora-related results by multiple keywords or queries
> - Target countries, states, cities, or other location terms
> - Filter results by email domain suffix
> - Set an email collection target
> - Exclude unwanted words or phrases from profile descriptions
> - Remove duplicate email addresses across the run
> - Store structured lead records in the Apify dataset
> - Continue processing multiple keyword and domain combinations
> - Save progress during execution so interrupted work can resume

The **Quora Email Scraper** is particularly useful when a simple `Quora email search` is too broad. More specific search phrases can help identify more relevant profiles and publicly indexed contact information.

For example, instead of searching only for `manager`, you can use several related terms such as `marketing manager`, `sales manager`, `startup manager`, and `business manager`.

***

### Quora Email Scraper – What Data You Can Extract

The **Quora Email Scraper** returns structured records rather than unorganized text. Each qualifying result can include the search keyword, page title, description snippet, result URL, and matching email address.

> 📦 **Output / Data Fields**
>
> | Field         | Description                                                        |
> | ------------- | ------------------------------------------------------------------ |
> | `keyword`     | The keyword or query used for the search                           |
> | `title`       | Title associated with the search result                            |
> | `description` | Description or snippet associated with the result                  |
> | `url`         | URL of the discovered result                                       |
> | `email`       | Publicly visible email address matching the selected domain filter |

The dataset also identifies the source network as Quora in the underlying result record, while the default dataset view focuses on the primary lead fields above.

The **Quora Email Scraper** only returns an email when it is found in the searchable result content and matches one of your configured domain suffixes. It does not guarantee that every Quora profile has an email address.

> ⚠️ **Important:** The Actor extracts publicly discoverable information. A result target is not a guarantee that the requested number of emails exists. Search availability, indexing, keyword specificity, location filters, and selected domains all affect the final result count.

***

### Quora Email Scraper – How to Use It

Using the **Quora Email Scraper** requires only a few configuration steps.

#### 1. Enter targeted keywords

Add one or more keywords or search queries. Multiple keywords create broader coverage than a single generic term.

Examples:

```text
manager
founder
marketing consultant
fitness coach
real estate agent
software developer
```

A focused keyword strategy is generally more useful for lead discovery than repeatedly using one broad word.

#### 2. Add an optional location

Use the location field to narrow searches to a country, state, city, or other geographic phrase.

Examples:

```text
New York
London
Toronto
California
United States
```

Leave the location empty when geographic targeting is unnecessary.

#### 3. Select email domains

The **Quora Email Scraper** can target specific domain suffixes.

Examples:

```text
@gmail.com
@yahoo.com
@outlook.com
@hotmail.com
@icloud.com
```

You can also specify other domain suffixes when they are relevant to your research.

#### 4. Set the maximum email target

The `maxEmails` setting accepts values from **1 to 10,000**.

The configured target is applied independently during each keyword + domain search combination. For example, with 3 keywords and 2 domains, the Actor processes 6 combinations.

#### 5. Add exclusion words

Use `excludeWords` when certain words or phrases should cause a search-result description to be skipped.

Examples:

```text
crypto
onlyfans
gambling
```

This can help remove irrelevant records based on visible description text.

#### 6. Start the Actor

After configuring your input, start the Actor and review the resulting dataset.

> ✅ **Quick Start**
>
> 1. Add specific keywords.
> 2. Add a location only when needed.
> 3. Select useful email domains.
> 4. Set `maxEmails`.
> 5. Add exclusion terms when appropriate.
> 6. Run the Actor and review the structured dataset.

***

### How to Get More Relevant Quora Email Results

A good **Quora Email Scraper** workflow starts with search intent rather than simply increasing the email limit.

#### Use multiple related keywords

Instead of:

```text
fitness
```

try:

```text
fitness coach
fitness trainer
fitness influencer
online fitness coach
personal trainer
```

This gives the search process more context and can expose different relevant results.

#### Combine job titles and specialties

For B2B prospecting, combine roles with industries or services.

Examples:

```text
marketing manager
startup founder
SaaS founder
real estate broker
ecommerce consultant
SEO consultant
```

#### Choose domains strategically

Selecting multiple relevant email domains can expand coverage. However, more domains also create more search combinations, so use domains that match your actual research goal.

#### Avoid overly narrow filters

A highly specific keyword plus a highly specific location and one email domain may produce very few results.

> 💡 **Tip:** When results are sparse, broaden the keyword set, remove the location filter, or add relevant email domains before assuming the Actor is not working.

***

### Can You Filter Quora Email Results by Location?

Yes. The **Quora Email Scraper** supports an optional `location` input.

You can enter a country, state, city, or similar geographic phrase. The location is used as part of the search targeting rather than as a guaranteed geographic attribute of every returned profile.

For example:

```text
location = New York
```

This can be useful for localized prospect research, regional market research, recruitment research, or audience discovery.

Because the location is a search term, results depend on what information is publicly indexed with that geographic context.

***

### Can the Quora Email Scraper Exclude Certain Profiles?

Yes. The `excludeWords` option lets you provide words or phrases that should cause a result description to be skipped.

Single-word exclusions are treated as whole-word matches, while phrases can match within the description. Matching is case-insensitive.

For example:

```json
{
  "excludeWords": [
    "crypto",
    "onlyfans"
  ]
}
```

If a result description contains one of those terms, the email from that result is not collected.

> 🛡️ **Filtering Note:** Exclusion filtering operates on the visible result description. It does not classify the entire Quora account or guarantee that an excluded topic exists elsewhere on the profile.

***

### Quora Email Scraper – Use Cases

The **Quora Email Scraper** can support several legitimate research and business workflows where publicly available contact information is relevant.

#### Lead generation

Discover publicly visible email addresses associated with searches for founders, managers, consultants, specialists, and other professional audiences.

#### B2B prospect research

Use combinations such as industry + role to build research datasets for sales intelligence or account discovery.

#### Market research

Search topic-specific keywords to identify people and pages connected to a niche or business category.

#### Recruitment research

Target professional terms such as:

```text
software developer
project manager
HR manager
product designer
data analyst
```

#### Influencer and creator research

Search terms related to creators, coaches, educators, experts, and niche personalities where publicly listed contact information appears in searchable content.

#### Audience discovery

Explore who is associated with particular topics, industries, professions, or geographic searches.

> 🎯 **Use-Case Box**
>
> The strongest results usually come from combining a clear audience definition with several related keywords and relevant domain filters.

***

### Input

The **Quora Email Scraper** accepts the following Actor inputs.

| Input           | Type    | Required | Purpose                                              |
| --------------- | ------- | -------: | ---------------------------------------------------- |
| `keywords`      | Array   |      Yes | Keywords or queries used for searching               |
| `location`      | String  |       No | Optional geographic search term                      |
| `customDomains` | Array   |       No | Email domain suffixes to search for                  |
| `maxEmails`     | Integer |       No | Maximum target for each keyword + domain combination |
| `excludeWords`  | Array   |       No | Words or phrases that exclude matching descriptions  |

#### `keywords`

A list of search terms. This is the only required input.

Default:

```json
["manager", "founder"]
```

#### `location`

An optional region or location string.

Default:

```text
""
```

#### `customDomains`

Email domain suffixes to include.

Default:

```json
["@gmail.com"]
```

#### `maxEmails`

Controls how many emails each keyword + domain combination attempts to collect.

Allowed range:

```text
1–10000
```

Default:

```text
5
```

#### `excludeWords`

Optional words or phrases used to skip matching descriptions.

Default:

```json
[]
```

***

### Output

The **Quora Email Scraper** stores results in an Apify dataset using structured records.

A typical record follows this structure:

```json
{
  "keyword": "fitness coach",
  "title": "Example Result",
  "description": "Example publicly indexed description...",
  "url": "https://quora.com/...",
  "email": "example@gmail.com"
}
```

The dataset is presented through a table view with dedicated columns for keyword, title, description, URL, and email.

> 📊 **Structured Output**
>
> The dataset is designed for easy inspection and downstream processing in Apify. Your final result is structured lead data rather than a plain text search dump.

***

### Pricing

The provided Actor configuration does **not** define a fixed monetary price.

The code does define an Actor-level free-run restriction of **up to 100 emails** for free users. Paid users are not subject to that specific Actor-imposed 100-email ceiling.

> 💰 **Pricing Information**
>
> - Free users: maximum 100 emails under the Actor's built-in free-tier restriction.
> - Paid users: the Actor does not apply that 100-email restriction.
> - No fixed dollar price is specified in the supplied Actor configuration.
>
> For the current monetary cost of running the Actor, refer to its live Apify Store pricing information.

The requested `maxEmails` value is still subject to actual search availability. A higher target does not guarantee that the Actor will find that many publicly available emails.

***

### Tips and Best Practices

> 💡 **Best Practices**
>
> - Prefer several highly relevant keywords over one extremely broad query.
> - Use specific job titles, industries, services, or audience descriptions.
> - Leave `location` blank when geographic targeting is unnecessary.
> - Add multiple relevant email domains when broader coverage is required.
> - Use `excludeWords` to remove obviously irrelevant categories.
> - Start with a smaller `maxEmails` target to evaluate result quality.
> - Broaden your search strategy when results are consistently below target.
> - Allow sufficient runtime for large keyword and domain combinations.

The Actor may stop processing a search combination when additional pages stop producing useful new email addresses or when search results become ineffective. This means a requested target should be treated as a maximum goal rather than a promise of availability.

***

### Frequently Asked Questions

#### What is a Quora Email Scraper?

A **Quora Email Scraper** is a tool that searches publicly indexed Quora-related results and extracts email addresses that match configured email domains. This Actor returns structured records containing the keyword, result title, description, URL, and email.

#### How does the Quora Email Scraper find email addresses?

The Actor searches for Quora-related pages based on your keywords, optional location, and selected email domain suffixes. It then identifies matching email addresses in the searchable result descriptions.

#### Can I search Quora emails by keyword?

Yes. Keyword-based searching is the core functionality of the **Quora Email Scraper**. You can provide multiple queries in the `keywords` array.

#### Can I scrape Quora emails by location?

Yes. The optional `location` field allows you to add geographic terms such as a city, state, or country to the search targeting.

#### Can I collect Gmail addresses from Quora?

Yes. `@gmail.com` is the default configured email domain. You can also add other domains through `customDomains`.

#### Can I search for company email addresses?

Yes, when relevant addresses are publicly visible and match the domain suffix you provide. You can configure custom domains for business or organizational research.

#### What is the maximum Quora Email Scraper limit?

The `maxEmails` input supports values from 1 to 10,000 for each keyword + domain combination. Free users are additionally restricted by the Actor's built-in 100-email ceiling.

#### Does the Quora Email Scraper guarantee the requested number of emails?

No. `maxEmails` is a collection target, not a guarantee. The final number depends on publicly indexed results, matching domains, query quality, exclusions, and available data.

#### Can I exclude unwanted Quora email results?

Yes. Use `excludeWords` to skip result descriptions containing specified words or phrases.

#### Can I use multiple keywords and multiple email domains?

Yes. The Actor is specifically designed to process multiple keyword and domain combinations, allowing broader search coverage.

#### What data does the Quora Email Scraper return?

It returns `keyword`, `title`, `description`, `url`, and `email` fields in the dataset. These are the primary fields displayed in the default dataset view.

#### Is the Quora Email Scraper useful for lead generation?

Yes. It can be useful for discovering publicly listed contact information related to professional roles, industries, services, topics, and other audiences represented in searchable Quora content.

#### Why did my Quora Email Scraper run return fewer emails than expected?

The most common reasons are narrow keywords, restrictive locations, limited email domains, exclusion terms, or insufficient publicly indexed email information. Expanding the search strategy can improve coverage, but cannot guarantee additional results.

#### Should I use broad or specific Quora keywords?

Specific keywords are usually more useful for targeted research. A combination of related terms is often preferable to relying on one very broad query.

#### Is the output structured?

Yes. The **Quora Email Scraper** writes structured records to the Apify dataset, making the collected data easier to inspect and process.

***

### Support

For Actor-specific questions, custom modifications, or bespoke scraper requirements, use the contact information provided with the Actor listing.

> 💬 **Need a custom workflow?**
> Contact the Actor developer for a tweak or bespoke build related to your scraping requirements.

**Quora Email Scraper** is intended for discovering publicly available, searchable contact information and turning relevant search results into structured datasets. Use the collected information responsibly and in accordance with applicable laws, platform rules, and privacy requirements.

# 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": [
    "manager",
    "founder"
  ],
  "location": "New york",
  "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": [
        "manager",
        "founder"
    ],
    "location": "New york",
    "customDomains": [
        "@gmail.com"
    ],
    "excludeWords": []
};

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

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

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,email_scraper/quora-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/2paRhdzgYbSVPFbJC/builds/s4lH8OLwMAqYGFmPD/openapi.json