Booking.com, End-to-End: Hotels, Flights, Cars, Attractions Scraped Daily

The client needed one dataset covering everything Booking.com sells, not accommodation alone: hotel bookings, flight tickets, car rentals, and information on attractions and activities. Those four product lines share a single domain, but each has its own search form, its own result logic, and its own idea of what a result even is. The job was to run all four every day against a defined list of airports and cities in the US, Europe, and Japan, and to return only the best price available for each supplier on each date.

Sources: booking.com
Coverage: hotels, flights, car rentals, attractions and activities; a set list of airports and cities in the US, Europe, and Japan
Frequency: daily
Volume: about 70,000 rows per day
Setup and launch: 6 working days

Four services on one domain, four different searches

A hotel search returns properties for a stay with a check-in and a check-out date. A flight search returns itineraries between two points. Car rental returns vehicles for a pickup window at a location. Attractions and activities return something different again. They share a brand and a domain and very little else, so treating Booking.com as a single target and writing a single collector for it does not hold up. Each service needed its own search sequence, its own parameters, and its own handling of results, while still landing in one dataset the client can work with as a whole. Coverage was not negotiable either: the brief named all four services, so a run that quietly succeeds on hotels and loses attractions is a failed run, not a partial one.

The trip dates move forward every day

This is not a catalog that can be collected once and topped up later. Travel prices only exist against specific dates, so every daily run goes out with updated start and end dates for the trips. That turns the task into a recurring set of searches rather than a crawl: the same list of airports and cities, a new date window, a new set of prices, day after day. It also means the pipeline has to run genuinely unattended - the date logic is part of the system itself.

Best price only, per supplier, per date

Raw search output is repetitive. The same hotel comes back at several rates, the same airline on several fares, the same rental company with several offers. The client did not want that pile. The requirement was a single selection - the best price for a given date - for each hotel, each airline, and each car rental company. So the filtering had to sit inside the collection process, not be left to the client to sort out afterwards. The dataset arrives already reduced to the comparison the client actually cares about, which also keeps the daily row count in a range that stays usable.

What the client gets every day

Setup and launch took 6 working days, from brief to a running daily process. Since then the client receives roughly 70,000 rows a day covering hotels, flights, car rentals, and attractions and activities across the US, Europe, and Japan, with best-price selection applied per supplier and per date.