We extract business directories, spatial coordinates, categories, and operating hours from Mapquest. 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 Listings objects from mapquest.com. All fields typed and schema-versioned.
"poi_id": "mq_4829104", "business_name": "Downtown Coffee Roasters", "primary_category": "Coffee Shops", "street_address": "400 15th St", "city": "Denver", "state": "CO", "postal_code": "80202", "rating": 4.6, "review_count": 128
| # | poi_id | business_name | primary_category | sub_categories | street_address | city |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Spatial Coordinates objects from mapquest.com. All fields typed and schema-versioned.
"poi_id": "mq_4829104", "latitude": 39.74312, "longitude": -104.99345, "geo_hash": "9xj65w", "routing_lat": 39.7431, "routing_lng": -104.9934, "accuracy_level": "rooftop"
| # | poi_id | latitude | longitude | geo_hash | display_lat | display_lng |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Operating Hours objects from mapquest.com. All fields typed and schema-versioned.
"poi_id": "mq_4829104", "timezone": "America/Denver", "monday_hours": "06:00-18:00", "saturday_hours": "07:00-17:00", "sunday_hours": "closed", "is_24_7": false
| # | poi_id | timezone | monday_hours | tuesday_hours | wednesday_hours | thursday_hours |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Local Search objects from mapquest.com. All fields typed and schema-versioned.
"search_keyword": "coffee", "bounding_box": "39.75,-105.00,39.73,-104.98", "rank_position": 3, "poi_id": "mq_4829104", "distance_miles": 0.4, "sponsored_listing": false
| # | search_keyword | bounding_box | rank_position | poi_id | business_name | distance_miles |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Routing Metadata objects from mapquest.com. All fields typed and schema-versioned.
"origin_poi": "mq_11203", "destination_poi": "mq_4829104", "total_distance_miles": 4.2, "total_duration_mins": 14, "has_tolls": false, "route_type": "fastest"
| # | origin_poi | destination_poi | total_distance_miles | total_duration_mins | has_tolls | has_highways |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Mapquest scraper bypasses visual tile rendering to extract the underlying structured JSON payloads, delivering clean POI data, coordinates, and business directories without the overhead of map image processing.
Extract business names, addresses, phone numbers, and categories for millions of locations across North America.
Capture rooftop-level latitude and longitude pairs, routing coordinates, and geohashes for exact spatial mapping.
Mapquest uses a deep category taxonomy. We extract primary and secondary categories to segment local business datasets.
Extract standard weekly operating hours, timezone data, and 24-hour status flags for retail and dining locations.
Parse raw addresses into structured components: street number, street name, city, state, and postal code.
We use tight bounding box matrices to sweep geographic areas, bypassing standard pagination limits to capture dense urban clusters.
Extract distance, estimated travel time, and toll requirements between POI pairs for logistics modelling.
Capture aggregate review scores and total review counts displayed on Mapquest business listings.
Run one-off state-wide exports or configure continuous pipelines to track new business openings and closures.
Brief in. Clean data out.
Provide bounding boxes, zip codes, or category keywords. We design the extraction schema together.
We configure Scrapy crawlers, spatial grid generation, and proxy rotation for mapquest.com.
Schema validation, coordinate accuracy checks, and deduplication before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Extracting spatial data requires specialized traversal strategies. Here is how we build resilient mapping pipelines.
Map search endpoints typically limit results to 50 or 100 items per request. To extract complete datasets for a city, we generate a matrix of tight bounding boxes, querying each sector individually to ensure zero data loss in dense commercial zones.
Rendering visual map tiles is computationally expensive and unnecessary for data extraction. Our crawlers intercept the underlying XHR requests, extracting clean JSON payloads directly from Mapquest's backend APIs.
Mapping services aggressively rate-limit repetitive spatial queries from data centre IPs. We distribute requests across a large pool of US-based residential proxies, maintaining high concurrency without triggering geographic IP bans.
Raw POI data often contains inconsistent address formatting. Our pipeline normalises street types, state abbreviations, and postal codes into a strict schema, ensuring the data is immediately usable in your warehouse.
Because bounding boxes overlap slightly to ensure complete coverage, duplicate POIs are inevitable at the edges. We maintain a hash index based on POI IDs and exact coordinates to deduplicate records before delivery.
Marketing agencies track local search rankings, business visibility, and category dominance across specific postal codes.
Real estate analysts map competitor density, category saturation, and commercial clustering to identify optimal locations for new retail stores.
Delivery fleets extract distance matrices and coordinate pairs to optimise last-mile routing algorithms.
Sales teams build targeted outreach lists by extracting business contact details within specific industries and geographic radii.
Data scientists correlate POI density with demographic datasets to build predictive models for urban development.
Niche industry portals enrich their own databases with verified addresses, coordinates, and operating hours from Mapquest listings.
"Mapquest remains a highly structured repository of North American business locations and routing metadata, but extracting it requires spatial grid traversal."
Scraping map infrastructure requires more than simple pagination. We deploy tight bounding box matrices to bypass search density limits, capturing complete local business datasets without missing dense urban clusters. DataFlirt handles the spatial geometry and proxy rotation so your team can focus on the analysis.
Everything supported by our mapquest.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 high-concurrency XHR interception, spatial grid generation, and automated retries. We bypass visual tile rendering entirely to focus on structured JSON extraction.
We maintain pools of residential ISP proxies across US regions. Rotation happens per-request to prevent rate-limiting on high-volume geographic sweeps.
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 mapquest.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available business directories and POI data is generally permissible under applicable law. DataFlirt targets only public, non-authenticated business listings and coordinates. We do not extract personal data or circumvent authentication walls.
We do not rely on standard pagination. Instead, we generate a matrix of tight geographic bounding boxes across your target area. By querying these micro-sectors individually, we ensure the result count per box stays under the limit, capturing 100% of the underlying POIs.
Yes. We can filter extraction runs by specific search terms or Mapquest category IDs, allowing you to build targeted datasets for coffee shops, hardware stores, or medical clinics without paying for irrelevant data.
Yes. We extract the highest-accuracy latitude and longitude pairs available on the listing, which typically represent rooftop coordinates, alongside display and routing coordinates.
Our bounding box strategy intentionally overlaps edges to prevent data loss. We maintain a deduplication layer based on POI IDs and spatial coordinates, ensuring you receive a clean, normalised dataset.
Our smallest packages start at defined geographic regions (e.g., a single US state or major metropolitan area) with one-off delivery. For continuous monitoring or national-scale extractions, we price based on spatial volume and delivery frequency.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off spatial export or a continuous POI monitoring feed across North America - we scope, build, and operate the pipeline. Tell us what you need.
