1. What area of Outscraper do you need help with?
   • A) Google Maps scraping — search and extract business data (names, addresses, phones, ratings, hours, websites, categories)
   • B) Business Catalog — instant business database lookups by location, category, rating (pre-built database, not scraping)
   • C) Reviews extraction — Google Maps reviews, Yelp, Tripadvisor, G2, Trustpilot, Glassdoor, Capterra, App Store, Google Play
   • D) Email & contact scraping — extract emails and contact info from websites or domains
   • E) Lead enrichment — find emails, phones, social profiles for companies (Contacts & Leads)
   • F) Company insights — firmographic data, tech stack, social profiles
   • G) Email validation — verify email deliverability (valid/invalid/risky)
   • H) Amazon scraping — product data and customer reviews
   • I) Search scraping — Google Search (organic, ads, snippets, PAA), Google News
   • J) Geocoding — address validation, coordinate lookup, reverse geocoding
   • K) Integrations / API — REST API, webhooks, SDKs, Zapier, n8n, Pipedream
   • L) Account / Billing — pricing tiers, usage, free tier
   • M) Something else — describe it
2. What's your role?
   • A) Sales / business development
   • B) Marketing / growth
   • C) Developer / engineer
   • D) Data analyst / researcher
   • E) Agency / freelancer
   • F) Other
3. What are you trying to accomplish? (describe your specific goal or question)

• General prospect list strategy / building target lists ->

  /sales-prospect-list

• Cross-platform data enrichment strategy ->

  /sales-enrich

• Email deliverability / verification strategy (not Outscraper-specific) ->

  /sales-deliverability

• Connecting Outscraper to CRM or other tools via middleware ->

  /sales-integration

• Apollo.io-specific questions ->

  /sales-apollo

• Hunter-specific questions ->

  /sales-hunter

• Prospeo-specific questions ->

  /sales-prospeo

• Seamless.AI-specific questions ->

  /sales-seamless

• Tomba-specific questions ->

  /sales-tomba

• What it does: Scrape business data from Google Maps — names, addresses, phone numbers, ratings, review counts, business hours, websites, categories, place IDs, coordinates, photos count, and more
• Search methods: Search by query (e.g., "restaurants in Austin, TX"), by place IDs, or by Google Maps URLs
• Query format: Category + location works best (e.g., "dentists, San Francisco, CA"). Supports multiple queries per request
• Volume: Up to 500 results per query. For larger volumes, split into more specific queries (by neighborhood, zip code, etc.)
• Filters: Filter by business status (open/closed), rating thresholds, review count minimums
• Output fields: name, full_address, city, state, zip, country, phone, website, rating, reviews_count, latitude, longitude, place_id, google_maps_url, business_hours, categories, verified, owner_title, price_range, and many more
• Deduplication: Outscraper automatically deduplicates results within a request

• What it does: Extract reviews for specific businesses from Google Maps — author name, rating, review text, date, review ID, likes count, owner reply text and date
• Input: Pass place IDs, business names, or Google Maps URLs to specify which businesses to scrape reviews from
• Sort options: most_relevant, newest, highest_rating, lowest_rating
• Filtering: Set a cutoff date to only get reviews after a specific date, or set a reviews_limit per place to cap the number of reviews extracted
• Review replies: Captures owner/business reply text and reply date when present
• Volume: Can extract thousands of reviews per business — use reviews_limit to control volume and cost

• What it does: Extract photo URLs and metadata for Google Maps businesses
• Use cases: Competitive analysis, visual auditing, local SEO research

• What it does: Get route and traffic data between locations via Google Maps
• Use cases: Territory planning, delivery route optimization, travel time estimation

• What it does: Scrape Google Search results — organic listings, paid ads, featured snippets, People Also Ask (PAA), knowledge panels, local pack results
• UULE support: Pass UULE codes for location-specific results (simulate searching from any location without being there)
• Output: title, link, snippet, position, domain for organic results; question/answer pairs for PAA; ad copy and URLs for paid results
• Pagination: Control number of results pages to scrape

• What it does: Scrape Google News search results — headlines, sources, dates, links
• Use cases: Media monitoring, competitor news tracking, industry trend research

• What it does: Pre-built database of millions of businesses — instant results without scraping. Query by location, category, rating, and dozens of other filters. Two tiers: free and paid
• Free tier (

  POST /businesses-free

  ): API key auth (

  X-API-KEY

  ), max 50 results per page, 1,000 total results. Good for testing and lightweight apps
• Paid tier (

  POST /businesses

  ): OAuth2 auth (authorization code flow, scope

  businesses.read

  ), higher limits. Full access to all fields and enrichments
• Base URL:

  https://api.outscraper.com

  (different from the scraping API)
• Filters:

  country_code

  ,

  states

  ,

  cities

  ,

  counties

  ,

  postal_codes

  ,

  name

  (with

  name_exclude

  ),

  types

  /

  ignore_types

  ,

  rating

  (e.g.

  "4.5+"

  ),

  reviews

  (e.g.

  "100+"

  ),

  has_website

  ,

  has_phone

  ,

  domain

  ,

  phone

  ,

  business_statuses

  ,

  area_service

  ,

  verified

  ,

  geo_filters

  (circle/polygon/bounding box),

  attributes

  (e.g.

  wheelchair_accessible

  ,

  takes_reservations

  ),

  located_os_id

  ,

  broad_match

  ,

  business_only

• Enrichments:

  contacts_n_leads

  (with

  contacts_per_company

  and

  emails_per_contact

  sub-params) and

  company_insights

  (revenue, employee count, industry, social profiles)
• Pagination: Cursor-based — response includes

  next_cursor

  and

  has_more

  . Pass

  cursor

  in the next request. Limit 1–50 results per page
• Field selection: Pass a

  fields

  array to return only specific fields (e.g.

  ["name", "phone", "website", "city", "rating"]

  )
• Response fields: name, phone, website, rating, reviews, subtypes, business_status, city, state, postal_code, country_code, time_zone, working_hours, photo, photos_count, menu_link, location_link, reviews_link, plus_code, verified, about (detailed attributes)
• Use cases: Build lead lists instantly without waiting for scraping jobs, filter businesses by precise criteria, enrich with contacts and company insights in a single request

• What it does: Scrape email addresses and contact information from websites or domains
• Input: Pass website URLs or domain names
• Output: Extracted email addresses, phone numbers, social media links found on the target websites
• Use cases: Building contact lists from company websites, lead generation from industry directories

• What it does: Find emails, phone numbers, and social profiles for companies — up to 3 contacts per company
• Input: Company names, domains, or LinkedIn URLs
• Output: Contact name, title, email, phone, LinkedIn profile, and other social profiles
• Volume: Returns up to 3 contacts per company

• What it does: Enrich company data with firmographic information — industry, employee count, revenue range, tech stack, social profiles, founding year
• Input: Company names or domains
• Output: Comprehensive company profile including firmographics, technology stack, social media profiles
• Use cases: Account research, ICP matching, competitive intelligence

• What it does: Verify email deliverability — returns valid, invalid, or risky status
• Checks: MX record validation, SMTP verification, disposable email detection, catch-all detection
• Use cases: Clean email lists before outreach, reduce bounce rates, protect sender reputation

• What it does: Whitepages-based phone number lookup — returns name, address, carrier, line type
• Input: Phone numbers
• Output: Owner name, address, carrier, line type (mobile/landline/VoIP)

• Products: Scrape Amazon product data — title, price, rating, review count, ASIN, seller info, product features
• Reviews: Extract Amazon customer reviews — author, rating, title, text, date, verified purchase status
• Use cases: Competitor product research, pricing intelligence, customer sentiment analysis

• Yelp: Search businesses and extract reviews (Yelp search + Yelp reviews endpoints)
• Tripadvisor: Extract reviews from Tripadvisor listings
• G2: Extract software reviews from G2 profiles
• Trustpilot: Search Trustpilot business profiles and extract reviews (separate search and reviews endpoints)
• Glassdoor: Extract company reviews from Glassdoor
• Capterra: Extract software reviews from Capterra
• Apple App Store: Extract app reviews
• Google Play: Extract app reviews
• Use cases: Competitive intelligence, reputation monitoring, customer sentiment analysis, social proof gathering

• What it does: Extract comments from YouTube videos — author, text, date, likes, reply count
• Use cases: Audience research, sentiment analysis, content strategy

• Geocoding: Convert addresses to coordinates (latitude/longitude)
• Reverse geocoding: Convert coordinates to addresses
• Use cases: Address validation, location data enrichment, territory mapping

• SimilarWeb: Get website traffic estimates — monthly visits, traffic sources, geography, top pages
• Company Website Finder: Find company websites from company names
• Yellow Pages Search: Scrape business listings from Yellow Pages
• Trustpilot Search: Search and enrich Trustpilot business profiles
• Whitepages: Phone and address lookup via Whitepages data

• Base URL (scraping):

  https://api.app.outscraper.com

  (primary), failover:

  https://api.app.outscraper.cloud

  ,

  https://api.outscraper.net

• Base URL (catalog):

  https://api.outscraper.com

  — used by Business Catalog endpoints only
• Authentication (scraping):

  X-API-KEY: {your_api_key}

  header on all scraping requests
• Authentication (catalog): API key for the free endpoint (

  X-API-KEY

  header); OAuth2 authorization code flow for the paid endpoint (authorization URL:

  https://api.outscraper.com/auth/oauth/authorize

  , token URL:

  https://api.outscraper.com/auth/oauth/token

  , scope:

  businesses.read

  )
• Rate limits: ~20 QPS soft limit (scalable on request for high-volume accounts)
• Batching: Up to 25 queries per request array — pass multiple queries in a single API call to reduce overhead
• Async pattern: Most endpoints return immediately with a request ID. Poll

  GET /requests/{id}

  for results, or use the

  webhook

  parameter to receive a POST callback when the task completes
• Key endpoints:

  • POST /businesses

    — Business Catalog lookup (paid, OAuth2) — instant database, not scraping

  • POST /businesses-free

    — Business Catalog lookup (free, API key) — max 1,000 results

  • GET /google-maps-search

    or

    POST /google-maps-search

    — Search Google Maps for businesses

  • GET /maps/reviews-v3

    — Extract Google Maps reviews

  • GET /maps/photos-v3

    — Extract Google Maps photos

  • GET /maps/directions

    — Get directions and traffic data

  • GET /google-search-v3

    — Scrape Google Search results

  • GET /google-search-news

    — Scrape Google News results

  • GET /emails-and-contacts

    — Scrape emails and contacts from websites

  • GET /contacts-and-leads

    — Find contacts for companies

  • GET /company-insights

    — Enrich company data

  • GET /email-validator

    — Validate email addresses

  • GET /phones-enricher

    — Phone enrichment (Whitepages)

  • GET /amazon/products-v2

    — Scrape Amazon products

  • GET /amazon/reviews

    — Scrape Amazon reviews

  • GET /yelp-search

    — Search Yelp businesses

  • GET /yelp/reviews

    — Extract Yelp reviews

  • GET /tripadvisor/reviews

    — Extract Tripadvisor reviews

  • GET /trustpilot

    — Search Trustpilot businesses

  • GET /trustpilot/reviews

    — Extract Trustpilot reviews

  • GET /glassdoor/reviews

    — Extract Glassdoor reviews

  • GET /capterra-reviews

    — Extract Capterra reviews

  • GET /google-play/reviews

    — Extract Google Play reviews

  • GET /appstore/reviews

    — Extract Apple App Store reviews

  • GET /g2/reviews

    — Extract G2 reviews

  • GET /youtube-comments

    — Extract YouTube comments

  • GET /geocoding

    — Geocode addresses

  • GET /reverse-geocoding

    — Reverse geocode coordinates

  • GET /whitepages-phones

    — Whitepages phone lookup

  • GET /whitepages-addresses

    — Whitepages address lookup

  • GET /similarweb

    — Get SimilarWeb traffic data

  • GET /company-website-finder

    — Find company websites

  • GET /yellowpages-search

    — Search Yellow Pages

  • GET /tasks

    — List UI tasks

  • GET /requests

    — Request history and results polling
• SDKs: Python (

  pip install outscraper

  ), PHP, Node.js, Ruby, Go, Java
• Docs: outscraper.com/docs

• Pay-as-you-go model — no monthly subscriptions, pay only for what you use
• Different modules have different per-record costs (Google Maps, reviews, email validation, etc. may vary)
• Tiers reset every 30 days
• Free tier is generous enough for testing and small projects

1. Scraping Google Maps businesses for a target market:
   1. Define your search queries — use "category, location" format (e.g., "dentists, Austin, TX" or "plumbers, 90210")
   2. For large areas, split by neighborhood or zip code to stay under the 500-result-per-query cap and get more comprehensive coverage
   3. Call

      GET /google-maps-search

      with your query array (up to 25 queries per request)
   4. Set

      limit

      parameter to control how many results per query (default 20, max 500)
   5. Results include name, address, phone, website, rating, review count, hours, categories, and place_id
   6. Use place_ids from results to follow up with reviews extraction or photos extraction
   7. Deduplicate across queries if your search areas overlap — Outscraper deduplicates within a request but not across separate requests
2. Extracting and analyzing Google Maps reviews:
   1. Get place_ids for target businesses (either from a previous Google Maps search or by looking them up manually)
   2. Call

      GET /maps/reviews-v3

      with place_ids, set

      sort

      (newest, most_relevant, highest_rating, lowest_rating)
   3. Use

      cutoff

      parameter to only get reviews after a specific date — useful for ongoing monitoring
   4. Set

      reviewsLimit

      to cap reviews per place (controls cost for businesses with thousands of reviews)
   5. Response includes author, rating, text, date, likes, and owner reply data
   6. For sentiment analysis, export reviews and analyze trends in ratings over time, common keywords, and response patterns
3. Building a lead list with emails and contacts:
   1. Start with Google Maps search to find businesses in your target market — extract business names, websites, and domains
   2. Pass the extracted domains to

      GET /emails-and-contacts

      to scrape email addresses from company websites
   3. For deeper enrichment, use

      GET /contacts-and-leads

      with company names or domains to find up to 3 contacts per company with names, titles, emails, and phone numbers
   4. Validate all collected emails using

      GET /email-validator

      before outreach — remove invalid and risky addresses
   5. Enrich company data with

      GET /company-insights

      for firmographics, tech stack, and social profiles to prioritize leads by ICP fit
   6. Export the combined dataset for import into your CRM or outreach tool
4. Setting up webhook callbacks for async results:
   1. Most Outscraper endpoints process asynchronously — they return a request ID immediately
   2. Instead of polling

      GET /requests/{id}

      , add the

      webhook

      parameter with your callback URL
   3. When the task completes, Outscraper POSTs the results to your webhook URL
   4. Your webhook endpoint should return a 200 status quickly — process the data asynchronously on your side
   5. For integration with Zapier, use the "Task Finished" trigger to kick off downstream workflows
5. Building a lead list from the Business Catalog:
   1. Choose your tier: use

      POST /businesses-free

      (API key) for testing or small lists up to 1,000 results, or

      POST /businesses

      (OAuth2) for full production access
   2. Define filters: set

      country_code

      ,

      states

      /

      cities

      /

      postal_codes

      for geography,

      types

      for business category (e.g.

      ["restaurant", "cafe"]

      ),

      rating

      (e.g.

      "4.0+"

      ),

      has_website: true

      ,

      has_phone: true

      to ensure contactable businesses
   3. Add enrichments in the same request:

      contacts_n_leads

      with

      contacts_per_company

      and

      emails_per_contact

      to get decision-maker emails, plus

      company_insights

      for firmographics
   4. Use

      fields

      array to return only the columns you need — reduces response size and speeds up processing
   5. Paginate with

      cursor

      — each response includes

      next_cursor

      and

      has_more

      . Loop until

      has_more

      is false
   6. Results are instant (no async polling needed) — the catalog is a pre-built database, not a scraping job
   7. Validate enriched emails via

      GET /email-validator

      on the scraping API before outreach
6. Using the Python SDK:
   1. Install:

      pip install outscraper

   2. Initialize:

      from outscraper import ApiClient; client = ApiClient(api_key='YOUR_KEY')

   3. Google Maps search:

      results = client.google_maps_search('restaurants, NYC', limit=100)

   4. Reviews:

      reviews = client.google_maps_reviews('place_id_here', reviews_limit=50, sort='newest')

   5. Email validation:

      results = client.emails_validator(['email@example.com'])

   6. All SDK methods support batching — pass lists of queries for efficient processing

Best-effort from research — review these, especially items about plan-gated features and integration gotchas that may be outdated.

1. Google Maps queries are capped at 500 results per query — you won't get every business in a broad search. If you search "restaurants, New York" you will get at most 500 results, not all restaurants in New York. To get comprehensive coverage, break queries into smaller geographic areas (zip codes, neighborhoods, boroughs) and deduplicate results across requests.
2. Async results require polling or webhooks — don't expect instant results from the API. Most endpoints return a request ID immediately. You must either poll

   GET /requests/{id}

   until the status is complete, or use the

   webhook

   parameter to receive results via callback. The Python SDK handles polling automatically, but raw API users need to implement this themselves.
3. Email validation and contact enrichment are separate modules with separate costs — don't assume emails from Contacts & Leads are pre-validated. The

   /contacts-and-leads

   endpoint finds emails but does not verify deliverability. Always run found emails through

   /email-validator

   before outreach to avoid bounces and protect your sender reputation.
4. Rate limits are soft at ~20 QPS but batching is the real throughput lever — use the 25-query batch limit. Instead of sending 25 individual requests, batch them into a single request with an array of up to 25 queries. This is more efficient and avoids hitting rate limits. For sustained high-volume usage, contact Outscraper to increase your QPS limit.
5. Review scraping costs scale with volume — set reviewsLimit to control spend. A single business may have tens of thousands of reviews. Without a

   reviewsLimit

   parameter, you could extract (and pay for) all of them. Always set a sensible limit unless you specifically need the full review history.

• /sales-prospect-list

  — Build and refine prospect lists using data from Outscraper and other sources

• /sales-enrich

  — Cross-platform data enrichment strategy (combine Outscraper with other enrichment tools)

• /sales-deliverability

  — Email deliverability and verification strategy (beyond Outscraper's email validation)

• /sales-integration

  — Connect Outscraper to CRM, automation, or other tools

• /sales-do

  — Not sure which skill to use? The router matches any sales objective to the right skill. Install:

  npx skills add sales-skills/sales --skills sales-do

1. Designs a query strategy: break DFW into specific cities and zip codes to maximize coverage beyond the 500-per-query limit — e.g., "HVAC, Dallas, TX", "HVAC, Fort Worth, TX", "HVAC, Arlington, TX", "HVAC, Plano, TX", "HVAC, Irving, TX", etc.
2. Calls

   GET /google-maps-search

   with batched queries (up to 25 per request),

   limit=500

   per query
3. Results include company name, full address, phone, website, Google rating, review count, business hours, and categories
4. Deduplicates results across queries using place_id as the unique key (same business may appear in overlapping geographic searches)
5. Follows up with

   GET /emails-and-contacts

   on extracted websites to find email addresses for outreach
6. Validates collected emails via

   GET /email-validator

   to remove invalid addresses before loading into CRM Result: User has a comprehensive, deduplicated list of HVAC companies across DFW with verified contact info, ratings, and review counts — ready for CRM import and sales outreach

1. Identifies place_ids for each competitor on Google Maps (from a search or manual lookup)
2. Sets up review extraction across three platforms:

   GET /maps/reviews-v3

   for Google Maps reviews,

   GET /yelp/reviews

   for Yelp reviews,

   GET /trustpilot/reviews

   for Trustpilot reviews
3. Uses

   sort=newest

   and

   cutoff

   date parameter to only pull recent reviews (e.g., last 90 days), controlling both relevance and cost
4. Sets

   reviewsLimit=100

   per business per platform to keep volumes manageable
5. Exports results as CSV for analysis — recommends looking at rating distribution over time, common complaint themes, and response rate/quality
6. Suggests setting up a recurring extraction (monthly or weekly) using Zapier or a cron job calling the API to track sentiment trends over time Result: User has a structured dataset of recent competitor reviews across three platforms, enabling competitive intelligence on customer satisfaction, common pain points, and areas of opportunity

1. Takes the 200 domains and batches them into requests of 25 each for

   GET /company-insights

   — 8 batched API calls total
2. Company Insights returns: industry, employee count range, revenue range, tech stack, social profiles, founding year, and headquarters location
3. Follows up with

   GET /contacts-and-leads

   using the same domains — returns up to 3 contacts per company with names, titles, emails, phones, and LinkedIn profiles
4. Prioritizes contacts by title relevance (e.g., VP Sales, Director of Operations, CTO depending on the user's target persona)
5. Validates all discovered emails via

   GET /email-validator

   — flags invalid and risky addresses for removal
6. Combines company firmographics and contact data into a single enriched dataset, ready for CRM import or outreach tool ingestion Result: User has 200 accounts enriched with firmographic data and up to 600 verified decision-maker contacts — filtered by ICP criteria and ready for personalized outreach