The traveling industry is a key service sector in majority of countries now a days. This is a key employment as well as revenue service provider. It demands ample constant maintenance and innovation. The traveling industry is a vibrant industry where the preferences and requirements of the customer changes each moment. The market players in the field require to continue with the industry trends, the options of the customers as well as even on information of their historical performances to do better when the time grows. Therefore, as you might believe, the companies dealing with travel sector require ample data from different sources as well as a pipeline of assessing and uses that data for recommendations and insights. Amongst the most commonly adopted techniques for collecting these types of data is web scraping online and other alternative resources. Data scraping is the primary part of maximum industries as well as businesses, which trail a data-driven culture. This traveling industry has benefitted from similar in different ways than one. We will discuss here about some of the advantages. Before it, let us mention what data scraping can assist as well as how you can utilize it professionally in the hospitality and traveling industry.
Uses of Data Scraping in the Traveling Industry
Data is essential for solving the significant problems the travel industry faces. Data scraping may help you know the market and industry trends on traveling fares, efficient traveling destinations and itineraries, new transportation and flight carriers, and even information on airports, flight delays, and train station updates, amongst other details. You may also extract customer feedback, preferences, and sentiment data. The data is publicly accessible on most travel websites and aggregators. This data could also get scraped from different social media sites.
This data may help hotels, travel agencies, travel aggregators, and service providers offer customers the best available options. This will also assist in boosting travel & tourism activities by improving customers’ general sentiments. The data could serve different objectives, such as accessible listings, pricing comparison of other airlines, and interested and descriptive analytics, including market share analytics, analyzing various patterns of travelers and their preferences for helping design services, which increase revenue and business income. Let us look at accessible frameworks that we can utilize to scrape data from travel service aggregators like MakeMyTrip.
Framework of Any Characteristic Data Scraper
Which Can be Utilized by the Travel Industry
We will talk about algorithms that might extract flight detailsfrom MakeMyTrip. In case you want to extract data of all the flights working between different combinations of any provided listing of cities with a particular date range, you initially need to prepare these details. An easy code for doing so is:
When we get city codes as well as dates’ lists within the form of the array, we are now required to loop using these to create complete URLs (or website links) for pulling data. We do that using a loop. This has a well-ordered logic, which maps all cities to different cities in a list you gave and loops using every date in a list. All the string values are appended for the base templates of the targeted URL or the sites from which you need to scrape data. It could be done, therefore:
When you have complete URL, just follow these 5 basic steps:
- Open a webpage well-defined by a URL
- When the data has started filling on the webpage, get the documents body as well as save the HTML structure. It will get all the data you want.
- Just close the links
- Parse the scraped data in the organized as well as more structured manners such that you could access the elements and tags in a webpage.
- Scrape the necessary tags to have suitable values.
- Scrape this data as well as save that in the well-structured file format – including a text or a CSV file.
All the steps have been completed using easy Python codes.
There are many platforms as well as libraries, which can do that task in no time. We have utilized BeautifulSoup and Selenium in Python. We have taken the following data:
- Airline’s Name
- Arrival Time and City
- Departure Time and City
- Flight Code
- Flight Cost
- Flight Duration
Then, we stored this data in a CSV format.
Benefits of Web Data Scraping for Travel Industry
Now as we have comprised how to scrape data from the given targeted website, let us observe how web data scraping is beneficial.
Web scraping is a faster procedure compared to other straight methods of gathering data from resources like the Internet.
You may scrape data in all desired structured formats like XML, CSV, or Excel files. You may also upload that to databases including SQLs.
Most data scraped using web scraping could be used straight without additional handling. The data’s veracity and quality make it suitable for many business difficulties.
The accuracy of data scraping in an auto-algorithmic manner is advanced because it is not subjected to ambiguity and human error.
It is also vital that we discuss some sample problematic case studies and statements of the travel industry, which can utilize data extracted from different web sources.
Conclusion
Data scraping may help you resolve various problems, but you have to be very careful about different logistical problems. You need to be careful about collecting the required data legitimately and with all the necessary permissions. There are definite aspects that make web data scraping a legal procedure. It would be best if you dealt with those.
Web scraping has been advantageous to the travel industry in many ways. Many professional web scraping companies provide dedicated web data scraping services. At X-Byte, we have assisted many businesses across different industries in collecting data and solving important business problems. We have a translucent procedure that offers you data in the preferred manner. For more information, contact X-Byte Enterprise Crawling or ask for a free quote!
✯ Alpesh Khunt ✯
