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

📧 Quora Email Scraper extracts verified email addresses from Quora profiles and posts—fast, accurate, and easy to use. 🚀 Perfect for B2B lead gen, outreach, and market research. Save time and boost conversion with targeted contact data.

- **URL**: https://apify.com/scraperoka/quora-email-scraper.md
- **Developed by:** [Scraperoka](https://apify.com/scraperoka) (community)
- **Categories:** Lead generation, Automation, Developer tools
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $1.99 / 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/platform/actors/running/actors-in-store#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 🎯

Manually visiting hundreds of profiles to collect emails wastes hours you don’t have. **Quora Email Scraper** automatically collects email contacts from Quora profile bios and posts related to your keywords—so you can build lead lists faster with a Quora email scraper and Quora scraper with email extraction. Ideal for marketers, recruiters, and growth teams working on Quora outreach email lists. In a single run, you can gather thousands of contacts (depending on your filters and limits) without copy-pasting pages one by one.

***

### What You Get: Sample Output

Here’s a sample record from a single run:

```json
{
  "network": "Quora.com",
  "keyword": "marketing",
  "title": "Marketing leader sharing practical growth tactics",
  "description": "I focus on product growth and marketing. You can reach me at sarah@company.com for collaboration.",
  "url": "https://www.quora.com/some-example-profile",
  "email": "sarah@company.com",
  "proxyGroups": ["GOOGLE_SERP", "my-custom-group"]
}
```

| Field | Type | What It Tells You |
|---|---|---|
| `network` | string | Confirms the source network for every record (useful for multi-network pipelines) |
| `keyword` | string | Which keyword triggered the lead discovery, so you can trace intent |
| `title` | string | The result title to help you understand the context behind the email |
| `description` | string | The extracted text snippet where the email was found (great for QA and auditing) |
| `url` | string | The page URL tied to the contact, so you can quickly verify and reference it |
| `email` | string | The email address captured from publicly available Quora content |
| `proxyGroups` | array | The proxy configuration context used during the scrape (helpful for troubleshooting and repeatability) |
| `error_message` | not present in pushed rows | If an email can’t be extracted from the available text, the actor simply pushes fewer (no per-row error field is included in the output) |
| `status` | not present in pushed rows | This actor does not emit a `status` field in pushed records |
| `success` | not present in pushed rows | This actor does not emit a `success` field in pushed records |

Export your dataset as JSON, CSV, or Excel — straight from the Apify dashboard.

***

### Why Quora Email Scraper?

There are a lot of ways to pull data from Quora — here’s what sets **Quora Email Scraper** (including Quora email scraper and Quora email scraping API use cases) apart.

#### Keyword-driven email discovery

You provide `keywords`, and the actor looks for email addresses tied to Quora bios and posts related to those terms. This makes Quora user email finder workflows much more targeted than generic web scraping.

#### Email-domain targeting for better outreach lists

Use `customDomains` (like `@gmail.com`) to focus on the email types you actually want. This improves the relevance of your Quora outreach email list and reduces wasted enrichment work.

#### Built-in resilience for long searches

For larger jobs, the actor includes retries and fallback logic and lets you tune runtime behavior via Apify Run Options (recommended for big keyword runs). That’s especially useful when you’re using this as Quora contact email scraper tool for bulk scraping.

#### Deduplicated email collection with a clear stop rule

The actor keeps a `seen_emails` set so duplicate emails aren’t repeatedly collected within a run. It also stops once `maxEmails` is reached, helping you control time and cost while using Quora email harvesting automation.

***

### Configuring Your Run

Drop this into your `input.json` to get started:

```json
{
  "keywords": ["founder", "marketing"],
  "location": "United States",
  "platform": "Quora",
  "customDomains": ["@gmail.com", "@company.com"],
  "maxEmails": 50,
  "engine": "legacy",
  "proxyConfiguration": {}
}
```

| Parameter | Required | What It Does |
|---|---|---|
| `keywords` | ✅ | A list of keywords to search for on Quora to drive email discovery |
| `location` | ⬜ | Filters results using a location string to narrow where leads come from |
| `platform` | ⬜ | Selects the platform (the only supported value in this actor is `Quora`) |
| `customDomains` | ⬜ | Limits extracted emails to specific domains (e.g. `@gmail.com`) for better targeting |
| `maxEmails` | ⬜ | Maximum number of emails to collect; the actor stops once the limit is reached |
| `engine` | ⬜ | Chooses the scraping engine: `cost-effective` (Cost Effective) or `legacy` (Legacy) |
| `proxyConfiguration` | ⬜ | Configure proxies for this Actor run (Apify Proxy support is available through this field) |
| ↳ `proxyConfiguration` (object) | ⬜ | The proxy configuration object passed to the actor |

***

### Core Capabilities

#### Keyword and domain filtering

Quora Email Scraper helps you focus on what matters by combining `keywords` with `customDomains`. This is what makes this Quora email scraper effective for lead generation and Quora outreach email list building.

#### Structured output written to your dataset in real time

As the actor finds email addresses, it pushes structured records into the Apify dataset. Each record includes the extracted `email`, the `url` context, and the text `description` used to find it—ideal for analysts and data teams.

#### Retries and fallbacks for resilience

The actor is designed to handle situations where pages return empty results or requests fail. It uses retry logic and fallback behavior to improve the chances of collecting Quora profile emails during longer runs.

#### Engine selection for speed vs reliability

You can choose between `engine: "legacy"` and `engine: "cost-effective"`. If you’re running high-volume Quora email harvesting software workflows, engine selection lets you match behavior to your needs.

#### Controlled scaling with a hard email cap

Use `maxEmails` to cap the number of emails the actor will collect. This helps you scale Quora email harvesting automation with predictable run duration while still searching enough pages to find relevant contacts.

***

### Who Gets the Most Out of This

**Growth marketing teams** use Quora Email Scraper to build fresh lists of outreach targets tied to specific topics, then filter by the email domains that fit their CRM workflows. You get context-rich records (title, description, and URL) so your team can move to personalization quickly.

**Sales Development Representatives** use it to turn a list of Quora-relevant interests into a Quora outreach email list with fewer manual steps. Domain filtering via `customDomains` keeps the output aligned with how you qualify prospects.

**Recruiters and staffing teams** benefit when they’re trying to find Quora profile email contacts from publicly available bios and posts connected to role-specific keywords. This makes Quora user email finder work far more efficient than browsing profiles one by one.

**Data analysts and enrichment specialists** like the consistent dataset shape, especially the inclusion of `description` and `url` for auditing. It’s also a practical foundation for downstream deduplication, enrichment, and validation.

**Automation engineers** can integrate Quora email scraping API workflows using Apify runs and dataset exports, then connect results to their existing pipelines (CRM sync, enrichment jobs, and reporting).

***

### Step-by-Step: How to Use It

No coding needed. Here's how to run Quora Email Scraper from start to finish:

1. **Open the actor on Apify** — go to [console.apify.com](https://console.apify.com) and search for Quora Email Scraper.
2. **Enter your inputs** — set `keywords` (required) and optionally `location`, `customDomains`, and `maxEmails`.
3. **Configure proxy settings** — if you use Apify Proxy, set it via `proxyConfiguration` for more reliable scraping at scale.
4. **Choose your engine** — pick `engine` as `legacy` or `cost-effective` depending on your preference for reliability vs cost-effective scraping.
5. **Hit Run and watch the live log** — monitor progress and verify that emails are being collected from publicly available Quora content.
6. **View results in the dataset tab** — each pushed record includes `email`, `url`, and the snippet `description` it was found in.
7. **Export as JSON, CSV, or Excel** — download the dataset directly from the Apify dashboard when the run completes.

The whole process takes under 5 minutes to set up.

***

### Integrations & Export Options

Once your data is collected, Quora Email Scraper plugs directly into your existing workflow.

Export your dataset in the Apify dashboard as **JSON**, **CSV**, or **Excel**, then import it into Sheets, your CRM, or your enrichment tooling. You can also use Apify’s **API access** to pull results programmatically (see Apify API docs at https://apify.com/docs/api).

For automation, you can connect runs to downstream steps using **webhooks** and no-code tools like **Zapier** or **Make**, and you can schedule recurring runs so your Quora email harvesting automation stays up to date. For deeper details, refer to Apify’s integration and automation documentation.

***

### Pricing & Free Trial

Quora Email Scraper runs on the Apify platform, which offers a **free tier** — no credit card required to get started.

In general, you use pay-as-you-go billing based on Apify compute units (CU), so there’s no monthly fee required for lighter use. For teams running heavier workloads, Apify also offers subscription plans—check the Apify pricing page for current options and what fits your scale. Start for free at [apify.com](https://apify.com) and scale when you're ready.

***

### Reliability & Performance

| What We Handle | How |
|---|---|
| Pagination for larger keyword searches | Continues collecting results until `maxEmails` is reached or results appear exhausted |
| Rate limiting / blocked requests | Retries and fallback behavior to improve capture success over longer runs |
| Proxy-based stability | Built-in proxy support for more reliable scraping |
| Deduplication | Avoids collecting the same email repeatedly using `seen_emails` |
| Data freshness and auditing | Output includes `description` and `url` so you can review what produced each email |

**Limitations:** The actor only works with publicly available information on Quora and cannot access login-gated or private content. If a profile doesn’t publish an email in its bios/posts related to your keywords, no email can be extracted.

For enterprise-scale runs, contact us to discuss custom configurations.

***

### Frequently Asked Questions

#### Is there a free plan or trial?

Yes, Apify offers a free tier so you can test Quora Email Scraper before scaling. You can start with a small `maxEmails` value to validate output quality quickly.

#### Do I need to log in to Quora to use this?

No. This actor scrapes emails from publicly available sources on Quora content that relates to your provided keywords.

#### How accurate is the data?

Accuracy depends on what the Quora profile owner publishes in their bios and posts related to your keywords. The actor extracts emails found in the available text and returns the corresponding `description` and `url` for review.

#### How many results can I get per run?

You control the maximum via `maxEmails`. The actor stops once the collected email count reaches your limit, and it may return fewer than the requested cap depending on how many emails are found.

#### How often is the data updated / how fresh is it?

Data freshness depends on when you run the actor. Each run collects whatever publicly available emails are accessible at that moment based on your `keywords` and `customDomains`.

#### Is it legal? Does it comply with GDPR / CCPA?

Quora Email Scraper is designed to use **publicly available data**, but legal compliance (including GDPR/CCPA and platform Terms of Service) is your responsibility. Make sure you handle, store, and use the collected data in a compliant way for your jurisdiction and use case.

#### Can I export results to Google Sheets or Excel?

Yes. You can export the dataset as JSON, CSV, or Excel from the Apify dashboard and then import it into Google Sheets or any spreadsheet tool.

#### Can I run this on a schedule automatically?

Yes. You can schedule actor runs using Apify scheduling features so your Quora email scraper workflow updates on a cadence without manual triggers.

#### Can I access this via API?

Yes. You can access runs and results programmatically using the Apify API (see https://apify.com/docs/api).

#### What happens if the actor hits an error?

If requests fail or results are empty, the actor’s retry and fallback logic aims to continue where possible. If your run still can’t collect more emails, it stops based on the run logic and your `maxEmails` cap.

***

### Need Help or Have a Request?

Got a question about Quora Email Scraper or want a new feature added? Reach out at <dataforleads@gmail.com>. We respond to support requests and feature requests regularly, and we actively maintain this actor based on community feedback. Ideas we often get: webhook notifications on completion and batch-friendly improvements for larger keyword lists.

***

### Disclaimer & Responsible Use

*Quora Email Scraper is the fastest, most reliable way to find email contacts from publicly available Quora bios and posts — start your free run today.*

**publicly available data** only. The actor does not access private accounts, login-gated content, or password-protected pages. You are responsible for complying with GDPR, CCPA, platform Terms of Service, and applicable laws for your use of the data. For data removal requests, contact <dataforleads@gmail.com>. Use responsibly, ethically, and only for lawful purposes.

# Actor input Schema

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

A list of keywords to search for.

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

Location to filter search results.

## `platform` (type: `string`):

Select platform.

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

List of custom email domains

## `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.

## `engine` (type: `string`):

Choose scraping engine. 🚀 Cost Effective (New): Uses residential proxies with async requests for faster, cheaper scraping. 🔧 Legacy: Uses GOOGLE\_SERP proxy with traditional selectors - more reliable but slower and more expensive.

## `proxyConfiguration` (type: `object`):

Configure proxies for this Actor.

## Actor input object example

```json
{
  "keywords": [
    "founder",
    "marketing"
  ],
  "location": "",
  "platform": "Quora",
  "customDomains": [
    "@gmail.com"
  ],
  "maxEmails": 20,
  "engine": "legacy"
}
```

# 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": [
        "founder",
        "marketing"
    ],
    "location": "",
    "customDomains": [
        "@gmail.com"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("scraperoka/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": [
        "founder",
        "marketing",
    ],
    "location": "",
    "customDomains": ["@gmail.com"],
}

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

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,scraperoka/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/tuYrMGQLOyq9iczDH/builds/HF8iutjPmppzm9cfH/openapi.json