Quora Email Scraper

Quora Email Scraper With Question Engagement Data 🚀📈

Quora Email Scraper With Question Engagement Data finds publicly available email addresses on Quora using your chosen keywords and email-domain filters, and — when you turn on Extract Question Engagement — enriches every matched Quora question with its answer count, view count, and follower count. It's built for content marketing and SEO teams who need to prioritize which high-traffic Quora questions to answer for brand visibility and organic search traffic, as well as anyone who wants a Quora email finder / Quora contact scraper with real engagement signals attached. Every base field from the standard Quora Email Scraper keeps working exactly the same — this is a strict superset, not a replacement.

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See the Data: Sample Output

{
  "network": "Quora.com",
  "keyword": "founder",
  "title": "Example Quora question or post title",
  "description": "Example snippet text that may include an email address like name@gmail.com",
  "url": "https://www.quora.com/Example-Question-Slug",
  "email": "jane.doe@gmail.com",
  "proxyGroups": ["RESIDENTIAL"],
  "answer_count": 12,
  "view_count": 1500,
  "question_followers": 230,
  "status": "success",
  "error_message": null
}

Field	Type	What It Tells You
network	string	The source network the email was associated with (Quora.com).
keyword	string	Which keyword drove the result.
title	string	The title extracted from the underlying search result.
description	string	The text snippet the email was found in.
url	string	The Quora page URL tied to the record.
email	string	The extracted email address.
proxyGroups	array	The proxy group(s) used during scraping.
answer_count	integer / null	New. Number of answers on the matched Quora question (only populated when extractQuestionEngagement is on and a question page's real count could be confirmed; null otherwise).
view_count	integer / null	New. View count shown on the matched Quora question. Same null conditions as answer_count.
question_followers	integer / null	New. Follower count for the matched Quora question. Same null conditions as answer_count.
status	string	success for a normal lead row, or no_results / error on the single uncharged diagnostic row pushed when a run finds nothing or crashes.
error_message	string / null	Populated only on the diagnostic row.

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

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Setting It Up

{
  "keywords": ["founder", "marketing"],
  "location": "",
  "platform": "Quora",
  "customDomains": ["@gmail.com"],
  "maxEmails": 20,
  "engine": "legacy",
  "proxyConfiguration": { "useApifyProxy": true },
  "extractQuestionEngagement": false
}

Parameter	Required	What It Does
keywords	✅	A list of keywords to search for when extracting Quora email results.
location	⬜	Filters the search results by location (leave empty to use no location filter).
platform	⬜	Selects the platform to scrape; the only supported value is Quora.
customDomains	⬜	Limits extracted emails to the domains you specify (for example @gmail.com).
maxEmails	⬜	Stops the run after collecting up to this many emails.
engine	⬜	Chooses the scraping engine mode: cost-effective or legacy.
proxyConfiguration	⬜	Configures proxies for this Actor run.
extractQuestionEngagement	⬜	New. When true, visits each matched Quora question URL and extracts answer_count, view_count, and question_followers. Off by default — enabling it adds one extra page fetch per matched question, so runs take longer.

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What It Does

Keyword-driven Quora email harvesting

You provide keywords, and the actor searches for relevant Quora content that may contain emails in bios and posts related to your topics.

Question engagement enrichment (new in this variant)

Turn on extractQuestionEngagement and, for every matched result whose URL is a genuine Quora question page (not a profile or topic page), the actor makes an additional fetch to that question and extracts its answer_count, view_count, and question_followers using three layered, real-data-only strategies: the question's own QAPage structured data, embedded page-state JSON, and visible rendered counters. Nothing is ever guessed or derived — a metric that can't be confirmed on the real page is left null, never a fabricated number.

Domain filters, maxEmails, and dual scraping engines

Unchanged from the base actor: use customDomains to reduce noise, maxEmails to cap collection and cost, and engine to pick between the async cost-effective mode and the legacy GOOGLE_SERP mode.

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Who Uses the Engagement Data

Content Marketing / SEO Teams — the primary use case this variant is built for. Pull emails tied to your target keywords, then sort the dataset by view_count or answer_count to find which Quora questions already have the most traffic and activity, so you know exactly where a well-placed answer will get the most brand visibility.

Lead Generation Specialists — still get the full base lead list (email, title, description, url), now with a quick relevance signal (question_followers) for judging which threads are worth outreach follow-up.

Researchers & OSINT Workflows — use the engagement counts as a proxy for how much public attention a given question/topic is getting alongside the contact data.

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Reliability & Limitations

What We Handle	How
Proxy support	Configure proxies via proxyConfiguration; choose cost-effective or legacy engine modes.
Collection limits	maxEmails caps how many emails are collected in a run.
Diagnostic visibility	If a run finds zero emails or crashes, an uncharged diagnostic row (status: no_results / error) is pushed so you can see what happened without being billed for it.
Progress persistence	The actor maintains resumable progress state.
Question engagement extraction	Quora's question pages sit behind bot-defense (Cloudflare) protection. When a question page can't be fetched cleanly, answer_count/view_count/question_followers are left null rather than guessed — check the run log for [Engagement] lines to see per-URL fetch outcomes.

This actor collects publicly available data from Quora. It does not access private accounts, login-gated pages, or password-protected content. It's your responsibility to follow GDPR, CCPA, and the platform's Terms of Service when using the scraped data.