We extract property listings, daily/weekly/monthly rate tiers, availability, and room amenities from Extended Stay America. 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 Property Details objects from extendedstayamerica.com. All fields typed and schema-versioned.
"property_id": "ESA_9821", "name": "Extended Stay America - San Jose - Downtown", "brand": "Extended Stay America Suites", "city": "San Jose", "state": "CA", "pet_friendly": true, "guest_rating": 3.8, "check_in_time": "15:00"
| # | property_id | name | brand | address_line_1 | city | state |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Room Types objects from extendedstayamerica.com. All fields typed and schema-versioned.
"room_id": "RT_102", "property_id": "ESA_9821", "room_name": "Studio - 1 Queen Bed", "bed_type": "Queen", "kitchen_included": true, "max_occupancy": 2, "smoking_allowed": false, "accessible_features": "['Roll-in shower']"
| # | room_id | property_id | room_name | description | bed_type | kitchen_included |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Pricing & Availability objects from extendedstayamerica.com. All fields typed and schema-versioned.
"property_id": "ESA_9821", "room_id": "RT_102", "check_in_date": "2024-11-01", "length_of_stay_days": 14, "rate_type": "Weekly Rate", "base_rate": 89.99, "currency": "USD", "availability_status": "AVAILABLE", "rooms_remaining": 4
| # | property_id | room_id | check_in_date | check_out_date | length_of_stay_days | rate_type |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Amenities & Policies objects from extendedstayamerica.com. All fields typed and schema-versioned.
"property_id": "ESA_9821", "wifi_included": true, "breakfast_included": true, "parking_fee": 0.0, "pet_fee_per_day": 25.0, "pet_fee_max": 150.0, "laundry_onsite": true, "housekeeping_frequency": "Weekly"
| # | property_id | wifi_included | breakfast_included | parking_fee | pet_fee_per_day | pet_fee_max |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Reviews & Ratings objects from extendedstayamerica.com. All fields typed and schema-versioned.
"review_id": "REV_847192", "property_id": "ESA_9821", "rating_overall": 4.0, "rating_cleanliness": 4.5, "review_date": "2024-03-12", "review_text": "Great for a two-week work trip. Kitchen saved me money.", "stay_type": "Business", "length_of_stay_category": "1-14 nights"
| # | review_id | property_id | reviewer_name | rating_overall | rating_cleanliness | rating_service |
|---|---|---|---|---|---|---|
| 1 | ||||||
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| 3 |
Extended Stay America's value lies in its tiered pricing model. Our pipeline extracts daily, weekly, and monthly rate curves across their entire property portfolio, handling complex calendar interactions automatically.
Extract all active Extended Stay America properties, including precise coordinates, contact details, and brand classifications (Suites, Select Suites, Premier Suites).
Capture rate curves by simulating stays of 1 night, 7 nights, 30 nights, and beyond to map the exact discount structures applied.
Extract detailed room configurations, kitchen inclusions, accessibility features, and property-wide amenities like laundry and fitness centres.
Track hidden costs including daily pet fees, maximum pet charges, parking costs, and housekeeping upgrade fees.
Monitor inventory depletion signals and sold-out dates across specific room types and properties.
Extract guest reviews, segmented ratings (cleanliness, service), and stay types to gauge property quality over time.
Configure pipelines to automatically roll search dates forward (e.g., next 30, 60, or 90 days) without manual input.
Deploy geo-targeted proxies to verify rate parity and detect location-based pricing variations.
Run price-check pipelines at daily or sub-daily intervals to monitor dynamic pricing changes in high-demand markets.
Brief in. Clean data out.
Specify target cities, properties, date ranges, and length-of-stay parameters. We design the extraction schema.
We configure Playwright scripts to navigate calendar widgets, handle session state, and bypass anti-bot protections.
We validate rate extraction accuracy, test multi-night discount calculations, and ensure null rates are minimised.
JSON, CSV, or Parquet delivered to your S3 bucket, data lake, or via API on your required schedule.
Extracting accurate pricing from hotel sites requires more than simple HTTP requests. Here is how we handle the booking engine state.
Hotel pricing requires maintaining session state across search, date selection, and room listing pages. We use Playwright to manage cookies and session tokens precisely, ensuring the rates returned match the requested dates.
Booking engines rely on complex JavaScript calendar widgets. Our scripts programmatically interact with these elements, accurately inputting check-in and check-out dates to trigger the correct rate calculations.
Rates and availability load asynchronously after the initial page renders. We implement strict wait conditions and network interception to capture the final pricing payloads before extraction.
Travel sites aggressively block datacentre IPs. We route all requests through US-based residential proxies with rotated browser fingerprints to mimic organic user search behaviour.
Extended Stay America displays prices differently based on length of stay. We normalise all outputs into standard base_rate, taxes, and total_rate fields, ensuring your downstream models receive consistent data.
Relocation agencies and corporate travel managers monitor long-term rates to optimise lodging spend.
Economy and extended-stay hotel brands track ESA pricing to adjust their own rate strategies.
REITs and property investors analyse hotel rates and availability to gauge market demand and rental yields.
Online travel agencies verify that direct-booking rates match contracted parity agreements.
Meta-search engines ingest property details and baseline pricing to populate their own booking platforms.
Analysts track expansion patterns and brand tiering (Select vs Premier) to understand budget travel trends.
"Extended Stay America's tiered pricing model offers unique signals for the corporate housing and long-term lodging market — if you can extract the rate curves accurately."
Scraping hotel availability requires interacting with complex calendar widgets and managing state across multi-step booking flows. DataFlirt handles the JavaScript rendering, session state, and proxy rotation required to extract accurate pricing tiers without triggering bot defenses.
Everything supported by our extendedstayamerica.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.
We use Playwright to handle the complex state management required by modern hotel booking engines, ensuring accurate date selection and pricing hydration.
All requests route through US-based residential proxies, preventing IP bans and ensuring we see the exact rates presented to domestic consumers.
Pipelines run on Kubernetes clusters managed by Apache Airflow, allowing us to scale concurrency during high-volume daily rate checks.
Data delivered to where your team already works — no new tooling required.
About extendedstayamerica.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available pricing and property information is generally permissible. DataFlirt extracts only public, non-authenticated data. We do not bypass login walls to extract proprietary corporate rates or personal data.
Yes. Our pipeline can simulate stays of 30+ days to trigger and extract the specific monthly rate discounts applied by the booking engine.
We can configure pipelines to run daily, weekly, or on custom schedules depending on the number of properties and date ranges required.
Yes. We extract ancillary costs including daily pet fees, maximum pet charges, parking costs, and housekeeping fees to provide a complete view of the total cost of stay.
Absolutely. You can provide a specific list of property IDs, cities, or zip codes to monitor, rather than scraping the entire national catalogue.
When a room type or property is unavailable for a requested date range, the pipeline records an explicit 'sold out' or 'unavailable' status rather than failing, providing valuable inventory depletion signals.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off property catalogue or continuous daily rate tracking across the entire network — we build and operate the pipeline. Tell us your requirements.
