As the airline industry has matured, the airline players have thrived, trying to win consumers by captivating them with innovation and values. For keeping ahead, airline companies are improving their level by leveraging cutting-edge airline data scraping services. This case study is about how an airline giant has leveraged data from different OTA platforms to make its business forward.
Business Challenge
Working with a highly dynamic data-demanding airline industry suggests a considerable possibility of human errors anytime. According to the degree of price liability, the client wanted to devise a data-based pricing optimization system to price flight tickets. Additionally, he wanted to keep his focus on margin improvement. The objective was to study market dynamics with access to well-structured flight data like arrival and departure times, gate details, pricing, flight numbers, and more from multiple airline sites or travel agencies worldwide.
Some challenges encountered by the customer include:
Market Losses : This client hoped to get a competitive pricing elasticity study model to prevent market share loss to the opponents.
Dynamic Pricing : Using airline pricing data, the customer wanted to take advantage of the dynamic price strategies to improve profits without obstructing the brand’s image
With complex decisions about flight ticket prices made by both historical and real-time data sets, these internal airline data extracting tools were not precise enough to assist them in driving margins. Therefore, the customer approached X-Byte Enterprise Crawling to leverage its airline web scraping solutions for better outcomes.
X-Byte Enterprise Crawling’s Airline Data Mining Solutions
X-BYTE SOLUTION
Setting up the Crawler – The crawler was initially configured such that it could automatically scrape product price and essential data fields for present categories on a daily basis.
Data Template : A template was created utilizing data structuring based on the schema provided by the customer.
Delivery of Data : Without any manual input from either side, the closing data was supplied in an XML format through Data API regularly.
The dataset had all the information including comments, news timelines, most viewed articles, customer behaviour, etc. All of the scraped data was indexed using hosted indexing components, and search APIs were made available so that a client could get the results every few minutes.