Since the digitalization of operations, the tourism industry is undergoing a significant expansion, mainly in the hotel industry. However, pricing and comparing prices with respect to the competition is one of the most complex aspects of the business. Beyond this complexity, web scraping opportunities in tourism industry are becoming more viable and efficient.

The reality of Big Data in tourism today

Data fulfills an essential function for decision-making in the tourism business. The 21st-century traveler is digitally robust and technologically competent. They use the web to plan, book and enjoy a new expedition. In order to manage this new age nomad, the industry is becoming more familiar with Big Data.

In this regard, dynamic pricing is a feasible path where web data helps hotels, airlines, and related industries. Today’s travelers are smart and opportunistic. They compare prices from different websites before making your reservation. Price comparison websites have multiplied in recent years.

These sites allow users to compare prices between platforms in a few seconds. The final consumer benefits, but price competition intensifies between companies. It is in this context that dynamic pricing comes to the rescue. Dynamic pricing is a strategy that avoids fixed prices and opts for variable prices. Therefore, the cost of a specific item changes based on market forces. It also changes based on ongoing customer demands and supply forces.
In this sense, the dynamic pricing strategy is key. But to exploit it to the fullest, it is necessary to have the technology and the appropriate service. That is where the value of web scraping for tourism comes in.

Dynamic hotel pricing is based on high-quality, reliable, and timely hotel data. It is a process in which web crawlers extract price parameters in real-time. They find other information from thousands of websites. Web scraping can predict hotel demands and then adjust room rates accordingly. Also, even if a forecast turns out to be false, the price is set quickly.

The hospitality industry can benefit from dynamic pricing. However, hoteliers need to consider some preventative factors that can affect the complexity of pricing dynamics. Among them is the capacity of the hotel, the type of room, the discounts offered, the date and time of the reservation, the rates of the competition, the strategic location of each hotel, the change of season, the popularity of each hotel (network effect), the prediction of variable passenger demand and government regulation of the sector. Making these variables increasingly predictable is one of the key tasks of the dynamic pricing model. Undoubtedly, the methodology for setting rates is not simple.

However, dynamic pricing also benefits from hotel rate intelligence as follows:

1. Higher revenue per room and higher average daily rate.
2. Improved revenue per available room.
3. Easier and more accurate and efficient pricing process through automation.
4. Each accommodation has the freedom to experiment and play with high and low prices.

Clearly, this pricing model is in fact dynamic, personalized, and flexible. It will change according to the spending habits of customers. In this way, web scraping helps hoteliers to understand consumer behavior. Automated hotel rate intelligence solutions are the future of the global hospitality industry.

At the same time, the extracted travel data allows companies to monitor their competitors, optimize their pricing strategy, discover trending keywords in a specific topic, and personalize their customer journeys. Travel data scraping automates and improves the efficiency of many tasks in the travel and hospitality industries.

So much so that you can have data on the number of passengers who arrive at a destination by different means of transport (number of people who arrive by boat, train, plane, bus, own vehicle, etc.). If you also know the seasonality (month, day, and time) in which they move, the reasons (work or leisure), final destination (passing through, the city or rural), you can begin to understand patterns, identify why they happen, identify trends or forecasts, try to predict what will happen next and what might be the best that could happen. These are only a few of the web scraping opportunities in tourism industry.

Web Scraping opportunities in Tourism Industry: Benefit from extracted travel data and achieve your goals

1. Hotel Reviews and Prices Scraping: Web scraping helps hotel companies compare the prices of hotel competitors to adjust their own prices. The pricing strategy is influenced by strong competition, high taxes, unfavorable economic conditions, and the quality of products and services. If you want to adjust your prices based on your competitors’ prices, you must collect publicly available information about your competitor’s prices. Using this solution your company can obtain room prices from different hotel pages. You can also turn your customer reviews into valuable, structured information and analyze your competitor’s reviews. Public data to extract includes hotel listings, prices, ratings, reviews, images, addresses, etc.
2. Real-Time Dynamic Travel Data Extraction: This functionality is crucial if, for example, the business wants to track and observe hotel room prices in a specific area for a month. In that case, your dynamic data is the “room price”, which is constantly changing. The tool will extract the room price data on the first day of the month. When the price of the rooms changes on the website you pull data from, your scraper also updates the price data. Therefore, you will receive the most recent price data.
3. Flight data scraping: Web scraping helps airlines understand current airline market conditions, offer personalized prices to customers, and manage customer demands. Flight data can be extracted, including flight number, flight duration, ticket price, aircraft name, arrival/destination time, airline name, etc. In this way, airlines can monitor prices, analyze market share and the current conditions offered by competitors, identify investment opportunities such as new routes or low-cost flights, and improve the growth strategy.
4. Industry Trend Analysis: The web scraping service allows you to extract frequently topics like trends and hashtags from social media platforms. This way you can monitor the main communication channels of your competitors and identify the top companies that rank for your search target keywords. It is also possible to analyze profiles, comments, and related news.
5. Travel-Related Location Data Collection: According to Google, searches for “near me” or “nearby” have increased by 150%. When people search for a restaurant, hotel, vacation rental, or flight, they use search engine maps to find places in their area. They search for “restaurants near me” or “hotels near me,” for example. Google Maps data is a great resource for connecting customers with businesses. Web scraping services collect information about real estate, hotels, restaurants, vacation rentals, etc. Businesses can use Google Maps to collect location details, customer ratings, and reviews from their competitors.

If you belong to the tourism industry, what service should you hire? With Scraping Pros you can manage all your web scraping needs in the tourism business to focus on what matters: growing your business! You will be able to access a wide variety of data without having to worry about how it is collected or formatted. All we need is a URL and our team will take care of everything else for you. Feed your business with audited and integrated data from different websites, relying on Scraping Pros’ complete web data extraction services.