Nextdoor Local Business & Recommendations Scraper

Scrape Nextdoor local business recommendations, neighborhood posts, and community data. Extract verified neighbor endorsements, vote counts, and business mentions. Essential for hyper-local market research and lead generation. Built by John Rippy (https://www.linkedin.com/in/johnrippy/ | https://johnrippy.link/).

Features

• Business Recommendations: Scrape recommended businesses with neighbor endorsements
• Neighborhood Posts: Extract posts mentioning businesses or services
• Category Filtering: Filter by home services, restaurants, automotive, etc.
• Comment Extraction: Optionally scrape comments and replies
• Vote Counts: Get upvote/thanks metrics for social proof
• Multi-Neighborhood: Scrape multiple neighborhoods in one run

Quick Start

{
  "url": "https://example.com",
  "maxResults": 100
}

Demo Mode

Set demoMode: true to test with sample data (no charges). When you're ready for real results, set demoMode: false or omit it.

{
  "demoMode": true,
  ...
}

Input Parameters

Parameter	Type	Description
scrapeType	string	Type of content: recommendations, posts, businesses, events
neighborhoods	array	List of neighborhood URLs or slugs to scrape
searchQuery	string	Search term for finding specific businesses/posts
category	string	Business category filter
maxResults	number	Maximum items to scrape (default: 100)
includeComments	boolean	Extract comments/replies (default: false)
includeVotes	boolean	Extract vote counts (default: true)
minRecommendations	number	Minimum recommendation count filter
dateRange	string	Filter by date: all, today, week, month, year
proxyConfiguration	object	Proxy settings
demoMode	boolean	Return sample data for testing

Output Format

Business Recommendation Output

{
  "businessName": "Mike's Plumbing",
  "category": "Plumbers",
  "recommendationCount": 47,
  "latestRecommendation": {
    "author": "Sarah M.",
    "neighborhood": "Coral Gables",
    "text": "Mike fixed our water heater same day. Fair prices and very professional!",
    "date": "2024-12-15",
    "upvotes": 12
  },
  "mentions": [
    {
      "postType": "recommendation",
      "text": "Looking for a good plumber? Mike's Plumbing is amazing!",
      "author": "John D.",
      "neighborhood": "Coconut Grove",
      "date": "2024-12-10",
      "upvotes": 8,
      "comments": 3
    }
  ],
  "neighborhoods": ["Coral Gables", "Coconut Grove", "South Miami"],
  "phone": "(305) 555-1234",
  "website": "https://mikesplumbing.com",
  "scrapedAt": "2024-12-21T10:30:00.000Z"
}

Neighborhood Post Output

{
  "postType": "recommendation_request",
  "title": "Need a reliable electrician",
  "content": "Looking for an electrician to install a ceiling fan. Any recommendations?",
  "author": "Maria G.",
  "neighborhood": "Miami Beach",
  "date": "2024-12-20",
  "upvotes": 5,
  "commentCount": 12,
  "comments": [
    {
      "author": "Tom H.",
      "text": "I highly recommend Spark Electric. They did great work at my place.",
      "date": "2024-12-20",
      "upvotes": 3
    }
  ],
  "businessMentions": ["Spark Electric", "A1 Electrical"],
  "scrapedAt": "2024-12-21T10:30:00.000Z"
}

Pricing

This actor uses pay-per-event billing: This actor uses pay-per-event pricing:

Event	Description	Price
apify-actor-start	Base cost per run	$0.15
item_scraped	Per recommendation/post scraped	$0.008
comment_scraped	Per comment extracted	$0.003

Example costs:

• 100 recommendations with 5 comments each: $0.15 + (100 × $0.008) + (500 × $0.003) = $2.45
• 50 posts, no comments: $0.15 + (50 × $0.008) = $0.55

Use Cases

• Lead Generation: Find businesses being recommended by locals
• Competitor Research: See which competitors get mentioned and why
• Market Research: Understand local sentiment and preferences
• Reputation Monitoring: Track mentions of your business
• Local SEO: Discover citation and partnership opportunities
• Content Ideas: Find trending local topics and concerns

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Built by John Rippy | Actor Arsenal