Top 5 Challenges of Scraping Travel Fare Aggregator Websites

Humans love to travel – with the travel and tourism industry accruing trillions of dollars in revenue until the happenstance of Coronavirus last year.

However, now that things are starting to ease back gradually, we see the industry gathering traction once more.

But traveling entails a lot of work, finding a destination, checking the availability of hotels and accommodation, and determining the cost of the entire trip.

This is why travel fare aggregators are growing in popularity. Travel fare aggregator websites contain the data needed to plan and execute a successful trip. This then makes scraping data from these websites equally important.

But these websites do not make scraping easy as they don’t want you to scrape their content in the first place. This then makes extracting their prices very tricky and challenging. Today, we will see what these challenges are and how to overcome them.

How Data Scraping Is Important In the Travel and Tourism Industry

Data is a big deal in every niche and industry today. And in travel and tourism, where information can determine the success or failure of a trip, data is even more vital. There are different areas where data can be used in this industry, including the following:

1. Building Search Engines

The data gathered in travel and tourism can build search engines to make information even more accessible and available to people from every region and country.

We see this in typical examples such as Kayak and Trivago – meta-search engines that make finding anything regarding destinations and travels easier.

2. Providing Better Customer Services

Data is also vital in delivering impeccable customer services. Brands in this industry can collect such data as travel destinations, accommodation, transportation fares, and even customers’ preferences and comments to tailor services that offer the best satisfaction to customers.

3. Price Optimization

Another way that businesses in this industry can put data to meaningful use is to adjust their prices to benefit both them and their customers.

Setting fares too high can cause customers to seek out other brands, and dropping the fare to below-average can cause an unprecedented loss of revenue.

To set a price that works for the brand and the customer, the brand must use relevant data to optimize its prices.

Who Might Need Data from Travel Fare Aggregators

The data collected from travel fare aggregators can be used by both customers and brands alike; hence, we see travelers and travel managers seeking data every day.

Some of the data that are scraped the most in this industry include:

• Travel locations, fares, rental availability in the location, and sites to see nearby
• Hotel listings, room pricing, and availability, and current or ongoing promotions
• Aviation information, airline routes and ticket fares, and timestamps
• Customer reviews and feedbacks about travel destinations, hotels, and travel products

Challenges of Scraping From Travel Fare Aggregators Websites

We now know why data is scraped in this industry and what types are scraped. But we also know there are several challenges that brands face when trying to scrape this data, and here are the most common challenges:

1. Outdated Information

The first challenge that many brands run into during scraping is finding outdated information. The way things work, a piece of information from last week or the week before may not be relevant today.

Finding websites that always have up-to-date data can pose a significant challenge that still needs to be dealt with.

2. IP Bans and CAPTCHAs

It is effortless to get blocked when scraping data because data extraction needs to be repetitive if accurate, and relevant. It means repeatedly visiting data sources and extracting their content. This is not something most websites like and hence have mechanisms that block an IP that continues to interact and extract their data frequently.

Secondly, CAPTCHAs exist on most websites to differentiate human users from bots. It then allows human users and block scraping bots. This discourages web scraping as bots are the tool of choice for data collection.

3. Cost of Scraping

Web scraping comes at a high cost sometimes. There is the need to employ skillful individuals in data extraction, handling, storage, and analysis. But when a brand cannot afford to hire extra hands, they will need to dedicate some staff members to handle this crucial aspect. However, these staff will still need some training which also costs money.

This, along with the cost of storing the data and maintaining the tools, are enormous challenges, especially for smaller companies.

4. Website Complexity

Most of the websites in the travel industry are complex and have layouts that change from time to time. And this can prove problematic for scrapers whether you are using a simple bot or a human for collecting the data.

When a layout or website structures change, most simple bots become overwhelmed and crash, whereas human scrapers have to start learning how to work with the new layout until it changes again.

5. Geo-Restrictions

This is the last and final obstacle that brands have to deal with when scraping fares from aggregators’ websites.

Some websites are not available to people from certain regions, and they use geo-restrictions to make sure of this.

This technique identifies where users are browsing from and blocks their activities if they are coming from a forbidden location.

Web Scraper API as a Solution

Web scraping is the process of using specific sophisticated tools to collect a large amount of data from multiple sources in the most hassle-free manner possible.

One of such tools is a web scraper API by Oxylabs, a high-level software designed to interact with aggregators’ websites and extract their content effortlessly. This tool recognizes website changes and adjusts accordingly.

Web scraping combines this with proxies which can conceal original IPs and locations then switch to different IPs and locations to evade IP blocks and geo-restrictions.

The process is often automated to ensure that data is collected regularly; there will be no space for outdated information.

And lastly, these tools require minimal effort, no training, and occasional little maintenance, thereby cutting away the cost of collecting data.

Conclusion

Travel and tourism are growing, and big data is becoming an essential component of this industry because of technological advancement.

Scraping data is, therefore, a necessity. Although some challenges are involved, using a web scraper API and other tools will make the process smoother, more timely, and more efficient.