We extract cruise itineraries, Select Price vs Early Saver rates, cabin availability, and ship metrics from pocruises.com. 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 Itineraries & Sailings objects from pocruises.com. All fields typed and schema-versioned.
"itinerary_id": "G412", "cruise_name": "Norwegian Fjords", "ship_name": "Iona", "departure_port": "Southampton", "departure_date": "2025-05-10", "duration_days": 7, "destination_region": "Northern Europe"
| # | itinerary_id | cruise_name | ship_name | departure_port | departure_date | return_date |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Cabin Pricing objects from pocruises.com. All fields typed and schema-versioned.
"itinerary_id": "G412", "cabin_type": "Balcony", "early_saver_price": 899.0, "select_price_price": 1049.0, "currency": "GBP", "availability_status": "Available", "onboard_spend_offer": 50.0
| # | itinerary_id | cabin_type | cabin_code | early_saver_price | select_price_price | currency |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Ship Details objects from pocruises.com. All fields typed and schema-versioned.
"ship_name": "Arvia", "guest_capacity": 5200, "tonnage": 184700, "year_built": 2022, "dining_venues": 26, "deck_count": 15
| # | ship_id | ship_name | guest_capacity | crew_to_guest_ratio | tonnage | length_meters |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Shore Excursions objects from pocruises.com. All fields typed and schema-versioned.
"port_name": "Stavanger", "title": "Pulpit Rock Cruise", "duration_hours": 3.5, "activity_level": "Moderate", "price_adult": 65.0, "currency": "GBP"
| # | excursion_id | port_name | title | duration_hours | activity_level | price_adult |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Ports of Call objects from pocruises.com. All fields typed and schema-versioned.
"port_name": "Southampton", "country": "United Kingdom", "region": "Europe", "tender_required": false, "arrival_time": "06:00", "departure_time": "17:00"
| # | port_id | port_name | country | region | arrival_time | departure_time |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Our pocruises.com scraper handles dynamic booking interfaces, session management, and UK geo-routing to extract accurate cabin availability and pricing.
Extract full sailing schedules, port orders, sea days, and departure dates across the entire P&O fleet.
Track Select Price, Early Saver, and Saver fares across all cabin grades including Inside, Sea view, Balcony, and Suites.
Monitor inventory levels and sell-out status for specific cabin categories on high-demand sailings.
Extract passenger capacities, tonnage, deck plans, and onboard venue details for Arvia, Iona, Britannia, and others.
Scrape excursion titles, durations, activity levels, and pricing per port of call.
Capture onboard spend offers, low deposit promotions, and flight-inclusive package details.
Execute Playwright scripts to navigate P&O's dynamic React-based booking flow and reveal final pricing.
Route requests through UK residential proxies to capture accurate GBP pricing and bypass geo-fencing.
Compare daily runs to output only changed prices or newly sold-out cabins, reducing data warehouse bloat.
Brief in. Clean data out.
Provide target regions, ships, or date ranges. We map out the required data schema.
We configure Scrapy/Playwright crawlers, session management, and UK proxy rotation.
Schema validation, null-rate checks, and price-outlier detection before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Cruise booking engines use complex session states and dynamic availability matrices. Here is how we extract reliable data.
Booking flows require maintaining cookie state across multiple requests to view final pricing. We manage persistent sessions to simulate legitimate user journeys.
P&O Cruises alters pricing and availability based on user IP. We use UK residential proxies to ensure all extracted data reflects authentic local market rates.
The search interface relies heavily on client-side rendering. We use Playwright to trigger filters, select passenger counts, and hydrate dynamic price elements.
Aggressive polling of cabin availability triggers blocks. We randomize request intervals and rotate IP addresses to maintain high pipeline throughput without detection.
Travel sites update DOM structures seasonally. We use fallback XPath and JSON-LD extraction to ensure data consistency despite front-end redesigns.
Cruise lines track P&O pricing tiers to adjust their own yield management algorithms and maintain market parity.
OTAs ingest itinerary and pricing data to populate their own booking engines and offer comparative search.
Analysts monitor cabin sell-out rates to forecast UK leisure travel demand and consumer spending health.
Tour operators analyze shore excursion pricing to position competing local tours at popular ports of call.
Maritime researchers track ship movements and port congestion based on scheduled itineraries across operators.
Travel agents monitor Early Saver drops to alert clients, secure bookings, and optimize commission structures.
"Cruise pricing is a highly dynamic yield management game. Without structured daily snapshots of cabin availability, you are flying blind."
Extracting data from cruise booking engines requires more than simple GET requests. It demands session state management, JavaScript execution, and precise geo-routing to bypass regional price discrimination. DataFlirt handles this complexity natively so you can focus on analysis.
Everything supported by our pocruises.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 orchestration and retry logic. Playwright manages React SPA interactions and complex session states required for cruise booking engines.
Localized IPs ensure authentic pricing, bypass geo-blocks, and prevent automated blocks from aggressive rate limiting.
Airflow schedules daily sweeps of all active itineraries. State and diff histories are stored in managed Postgres for reliable change detection.
Data delivered to where your team already works — no new tooling required.
About pocruises.com scraping, legality, and pipeline operations.
Ask us directly →Yes, we extract all available fare codes, promotional rates, and standard pricing tiers for every mapped itinerary.
Yes, we extract pricing and availability status for Inside, Sea view, Balcony, and Suites on every sailing.
We use Playwright to simulate user interactions, select passenger counts, and navigate to the final pricing page where accurate rates are exposed.
We route all requests through UK residential proxies to ensure GBP pricing matches local search results and avoids generic default rates.
Yes, we extract all port excursions including prices, durations, descriptions, and activity levels.
We typically run daily sweeps of all itineraries, but can configure hourly runs for specific high-priority sailings nearing departure.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a daily sweep of all Mediterranean itineraries or continuous tracking of Arvia cabin prices. Tell us what you need.
