We extract local business listings, neighborhood recommendation counts, service categories, and local deals from Nextdoor's public directories. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake on your cadence.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Business Profiles objects from nextdoor.com. All fields typed and schema-versioned.
"business_id": "84920183", "name": "Apex Plumbing & Heating", "category": "Home Services > Plumbers", "recommendation_count": 142, "neighborhood_name": "Downtown Heights", "claim_status": true, "phone": "+1-555-019-2834", "website": "https://apexplumbing.example.com"
| # | business_id | name | category | recommendation_count | address | phone |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Local Deals objects from nextdoor.com. All fields typed and schema-versioned.
"deal_id": "D-99281", "deal_title": "20% Off Spring AC Tune-Up", "business_name": "CoolBreeze HVAC", "discount_value": "20%", "expiration_date": "2024-05-31", "neighborhood_reach": 14, "terms": "Valid for new customers only. Cannot be combined with other offers.", "deal_url": "https://nextdoor.com/pages/coolbreeze-hvac/deals/99281"
| # | deal_id | deal_title | business_name | business_id | discount_value | expiration_date |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Recommendations objects from nextdoor.com. All fields typed and schema-versioned.
"recommendation_id": "R-1029384", "business_id": "84920183", "neighborhood": "Maplewood Estates", "author_first_name": "Sarah", "recommendation_text": "Fixed our water heater on a Sunday. Highly professional.", "date_posted": "2023-11-14", "helpful_votes": 12, "reply_count": 0
| # | recommendation_id | business_id | neighborhood | author_first_name | recommendation_text | date_posted |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Public Agencies objects from nextdoor.com. All fields typed and schema-versioned.
"agency_id": "A-4829", "agency_name": "City of Austin Police Department", "jurisdiction": "Austin, TX", "subscriber_count": 142950, "post_count": 842, "website": "https://austintexas.gov/department/police", "category": "Law Enforcement", "profile_url": "https://nextdoor.com/agency/city-of-austin-police-department/"
| # | agency_id | agency_name | jurisdiction | subscriber_count | post_count | website |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Service Categories objects from nextdoor.com. All fields typed and schema-versioned.
"category_id": "C-104", "category_name": "Landscaping", "parent_category": "Home & Garden", "total_businesses": 1240, "top_neighborhood": "Oak Creek", "average_recommendations": 24.5, "trending_status": true, "url_slug": "/find-neighborhood/tx/austin/landscaping"
| # | category_id | category_name | parent_category | total_businesses | top_neighborhood | average_recommendations |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Nextdoor scraper maps the hyper-local graph: business listings, neighborhood recommendations, agency directories, and local deals — with geographic proxy routing and anti-bot circumvention built in.
Extract profiles, service categories, contact info, and website links from Nextdoor's public local business directory.
Track local sentiment and visibility by extracting recommendation volumes and helpful vote metrics across service areas.
Monitor promotions, discount values, expiration dates, and neighborhood reach for local business offers.
Extract subscriber counts, jurisdiction coverage, and public profile metadata for local government and law enforcement agencies.
Route requests through zip-code targeted residential proxies to access hyper-local directory variations.
Traverse parent-child service categories to build comprehensive lists of providers in specific verticals.
Identify unclaimed local business profiles to generate highly targeted leads for local marketing agencies.
Extract structured open/close times, business descriptions, and physical addresses normalised for your database.
Run one-off bulk exports of specific zip codes or configure continuous pipelines at weekly cadences with change-detection diffing.
Brief in. Clean data out.
Provide zip codes, city names, or service categories. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, geo-targeted proxy rotation, and API interception for nextdoor.com.
Schema validation, null-rate checks, and sample coverage reviews before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Nextdoor strictly gates content by location and login state. Here's how we extract public directory data reliably without triggering blocks.
Nextdoor alters directory visibility based on the request's geographic origin. Our infrastructure routes requests through ISP-grade residential proxies matching the target zip code, ensuring complete local coverage.
Nextdoor's frontend relies heavily on GraphQL queries. Rather than parsing complex DOM structures, we intercept these API responses directly, yielding cleaner data and reducing pipeline fragility.
Business pages and review modules are lazy-loaded via JavaScript. We deploy Playwright browser instances to trigger these network requests and hydrate the page before extraction.
For large business directories, we maintain a hash index of last-seen values per listing. Subsequent runs only push diffs — reducing compute cost and downstream processing load.
Every run emits structured logs to our observability stack. We alert on null-rate spikes, block rates, schema drift, and coverage drops — responding before data delivery is impacted.
Marketing agencies track business listings and claim statuses to audit local search presence for SMB clients.
B2B service providers identify unclaimed profiles or highly recommended local businesses for targeted outreach.
Franchises analyse service category density and recommendation volumes to identify underserved neighborhoods.
Home service companies monitor competitor deals, pricing strategies, and neighborhood reach within their service areas.
Researchers and civic tech platforms track public agency engagement and subscriber growth across jurisdictions.
Corporate brands audit their local franchisee profiles for brand compliance, correct operating hours, and local sentiment.
"Nextdoor maps the hyper-local economy better than any other platform — but extracting that neighborhood-level data requires precise geographic proxy routing."
Most teams fail at Nextdoor scraping because they ignore the platform's strict geographic IP filtering and complex GraphQL backend. DataFlirt manages the residential proxy routing, API interception, and schema normalisation so your engineers can focus on the analysis — not the infrastructure.
Everything supported by our nextdoor.com scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
Scrapy handles crawl orchestration, deduplication, and retry logic. Playwright manages JavaScript rendering and API interception for Nextdoor's frontend.
We maintain pools of residential ISP proxies with zip-code level targeting capabilities to bypass location-based directory restrictions.
Pipelines run on AWS Lambda (burst) and ECS (sustained). Airflow handles scheduling, dependency management, and SLA alerting. All state stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About nextdoor.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from Nextdoor's public directories (businesses, agencies, local deals) is generally permissible. DataFlirt strictly targets public, non-authenticated data. We do not extract private neighborhood feeds, bypass address verification, or violate user privacy.
No. Accessing private neighborhood feeds requires verified resident login and physical address verification. DataFlirt exclusively extracts data from Nextdoor's public-facing business and agency directories.
We utilise zip-code targeted residential ISP proxies to route requests through the specific geographic areas required to view hyper-local directory variations.
We extract business name, category, recommendation count, address, phone number, website, claimed status, operating hours, and public local deals associated with the profile.
Directory extractions typically run on weekly or monthly cadences depending on volume. Sub-daily tracking is available for targeted lists of specific business profiles or local deals.
Our minimum engagement covers defined city or zip-code lists with weekly delivery. For nationwide directory mapping, we price based on volume and delivery frequency.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off directory dump for specific zip codes or a continuous feed of local business recommendations — we scope, build, and operate the pipeline. Tell us what you need.
