Hotel Pricing: Use Web Scraping to Price your Hotel Right
Updated: Feb 5, 2021
The hospitality industry is steadily growing over the years and shows no sign of slowing down. Digitally literate travelers are making use of online platforms for planning, booking, and experiencing a journey. Not to be left behind, the hospitality industry is increasingly getting to grips with the concept of big data and the numerous ways in which the use of web data in the right hotel pricing can help them in revenue generation and provide a better customer experience.
Why need web data to understand hotel pricing?
Today, intelligent customers research a lot. They compare the prices from different websites, before making a buying decision. Price comparison websites, especially of the hospitality industry, have mushroomed over the years to cater to these active consumers. These websites allow consumers to compare prices across firms in a matter of clicks. This, in turn, intensifies competitive pricing pressure between firms. This is where dynamic pricing comes into play.
Dynamic pricing, which can be applied across industries like e-commerce and hospitality, is a very powerful yet underutilized revenue management tool. It is a foolproof way of improving the financials of a business by maximizing their revenue and margin. Dynamic pricing is already being lauded as a “game-changer”, especially in industries that face fierce competition.
Source: Statista – Survey on the importance of dynamic pricing in Germany 2017
Pricing is hard. Finding the right balance between underselling and overpricing is something many hoteliers struggle with. Leveraging web data through hotel price scraping, they can maximize the profit by changing the room prices daily, hourly or even by-the-minute.
Also Read: How Data-Driven Decision Making is Driving Businesses Towards Success
What are the factors that influence hotel pricing dynamics?
The objective of a hotel pricing strategy is very simple – maximize the bottom line. But, managing this complex pricing model is very challenging. It depends on a lot of factors like:
1. Hotel Capacity
Hotel prices are primarily dependent on room availability and customer demand. If a hotel expects full capacity booking around a certain event, they can raise the price of their rooms and still get enough bookings to sell out. Likewise, hotels decrease the rate close to arrival if the expected occupancy isn’t met.
2. Room Type
Normally, you would expect the suite rooms of a hotel to cost the same. This is not the case as each room is rated differently and comes with different perks. A room with a beach view would cost a lot more than one that looks over a parking lot.
3. Discounts offered
Smart travelers on a budget always look out for discounts and deals to save money. Promotions are great initiatives to keep up with, and stay ahead of, your competition.
4. Competitor price
Hotels often try to increase the revenue by matching their competitors on price. It helps them to strategically position themselves in front of their customers by taking into account the current market situations.
5. Booking time/date
Traditionally, hotel prices are adjusted based on how far in advance they have customers made the reservations. Sometimes, customers who wait for the last moment often make off with the best deals at the lowest prices.
6. Central Location
There is a lot of demand for hotels that are centrally located in a city or conveniently close to popular tourist locations. Likewise, room prices go up if the hotel hosts important seminars or conferences.
7. Changing seasons
Room prices of hotels at tourist locations will drop during the off-season. These hotels will aim to maximize their income before the demand wanes by increasing prices during the peak season.
8. Demand forecasting
Fixing the “right price” requires a lot of forecasting. Management needs to have a firm grasp on the demand level for every day to price the hotel room efficiently.
9. Network effect
The network effect is the increase in demand and value offered by a service based on its usage by more people. In simple words, the network effect is the by-product of the popularity of your hotel. People are willing to pay more to stay at a hugely popular destination.
10. Business Rule
The hospitality industry is rigorously monitored by regulatory bodies like the government. The pricing strategies of the hotel business should follow the pricing rules and regulations.
Through hotel data scraping, the above parameters will be extracted and converted into meaningful, well-structured and usable data.
Also Read: How Brands Use Data to Enhance Customer Experience
How dynamic pricing is used by hotels today to offer the right price at the right time
Dynamic Pricing has a host of benefits for the hotel industry,
Increase Room Revenue, Average Daily Rate (ADT), and Revenue Per Available Room (RevPAR)
Match the ever-changing price trends in minutes by observing competitor price
Make the pricing process more efficient, as automation makes it easier, faster, and more precise
Give leeway to experiment with “high to low” approach wherein a hotel quotes high prices at the start of the day and lowers the prices later if the demand fails to materialize as opposed to the “low to high” approach where the price is increased based on the number of rooms reserved.
So, how is a dynamic pricing strategy formulated?
It is based on a timely, reliable source of high-quality data extracted through hotel data scraping. Web crawlers parse real-time pricing parameters from thousands of websites.
Web scraping helps hotels predict when demand will be high or low. Prices are lowered to attract visitors to book empty rooms during periods of low demand. Conversely, hotel prices are the highest during peak vacation season or around major local events. Even if the initial forecast turns out to be inaccurate, the price can be quickly adjusted to the real-time demand fluctuations.
Apart from rates management, web data scraping can be used to obtain:
Insightful data analytics
Web scraping is widely used for competitor research. It gives actionable data which will help you to stay one step ahead of your competition. Watching your competitor prices is a great tool to gauge the market response. Based on the market trends, companies can choose either a premium pricing model or a penetration pricing model.
A truly dynamic pricing model will more flexible and personalized. That is, the price will vary from customer to customer based on their purchasing habits. Web data scraping can be used to extract customer behavioral data which includes their spending habits and willingness to search for a better price.
More and more hotels are incorporating pricing intelligence solutions to transform their businesses. Once you get hold of the relevant data through hotel price scraping, you can derive more insights and understanding about customer preferences and demand curve. Using this knowledge, pricing parameters can be continuously adjusted to extract more value for your business.
Also Read: Competitive Pricing Strategy: How Products Are Priced
How can hotels leverage web data to implement dynamic pricing?
Robert L. Crandal, Ex-CEO of American Airlines, has once famously said, “If I have 2000 clients in a given route and have 400 different prices, obviously I miss 1600 prices.”
This embodies the true spirit of dynamic pricing. The tight competition in the hospitality industry has made sure that the fixed pricing strategy no longer works. Dynamic pricing holds the key to significant financial improvement.
Setting up a dynamic pricing model requires planning, pre-modeling analysis and designing and building the pricing model by adjusting the parameters and preparing customer communications. Hotels are increasingly investing in strong data analytics. If that proves to be a financial overhead, companies can opt for third-party service providers.
Do you wish to design a dynamic pricing strategy based on clean, reliable competitor data extracted through web scraping from thousands of travel and hotel websites? Get in touch with our experts for efficient and affordable web scraping services.