Hotel Business Intelligence: Leverage Web Scraping to Price your Hotel Right

The hospitality industry is growing at an unprecedented rate. Its expansion is still ongoing. The current value of the Indian hospitality sector is USD 32 billion. This is inbound and outbound hotels combined. It is expected to touch USD 52 billion thresholds by 2026. In addition, the country’s overall hospitality sector is inflating at a CAGR of 4.73 percent. Such figures are promising, indeed. The hospitality sector must reach its full-fledged potential. The importance of data, web scraping, and intelligent technology are indispensable for this.

The 21st-century traveler is digitally sound and technologically proficient. They use the web and the internet to plan, book, and enjoy a novel expedition. Thus, to cater to this new-age nomad, the Indian hospitality industry gets to grips with Big Data. Big Data and web scraping have multiple benefits. It is from pricing to revenue generation and better customer experience. What are they, and how do they help the hospitality sector? Well, let us find out.

Dynamic pricing is an effective strategy. It is one of web data’s most pertinent ways to help hotels and related sectors. Today’s travelers are intelligent. They compare prices from varying websites before making the final call. Price comparison websites have mushroomed in the past few years. There is a culmination of such active and savvy consumers. These sites enable users to compare prices across platforms in a few seconds. The end-consumer benefits, but the pricing competition intensifies among the firms. It is in this context that dynamic pricing comes to the rescue. Dynamic pricing is a strategy that shuns fixed pricing and co-opts variable pricing. Thus, the cost of a specific item changes as per market forces. It also changes as per ongoing customer demands and supply forces.

In all honesty, dynamic pricing is the key to staying afloat. It is because a profitable business within the competitive hospitality industry. However, more than leaning on intuition and observation is required to ace the strategy. Hoteliers must invest in the right technology. This will help you find the right balance between underselling and overpricing. Leveraging web data via hotel price scraping culminates in hotel rate intelligence. It is wherein profits are maximized by altering the room prices daily, hourly, or even by the minute. So, how can hoteliers come to terms with the precarity of dynamic pricing? The answer lies in understanding the preemptive factors. These are the ones affecting the strategy, an explanation of which is given below.

The aim of dynamic hotel pricing data is simple – maximizing the bottom line. However, managing it can be complex, as dynamic pricing depends on many factors.

Hotel Capacity – Hotel rates mainly rely on room availability and customer demand. Suppose the hotel expects full booking around an event. They can raise the room prices and still rope in enough bookings. On the contrary, the room rates can be reduced close to arrival if the expected occupancy is not met.

Room Type – The second factor determining dynamic hotel pricing is room type. Each room is rated differently. It has diverse perquisites; it is important to charge them variably.

Discounts Offered – Savvy travelers on a budget always look for discounts. They check on deals on hotel bookings. Thus, promotions are a great way to attract smart globe trotters. They stay a class apart from competitors.

Booking Data and Time – Traditionally, hotel prices are based on how far the booking has been made. They get the best deals at the lowest prices. That too in advance. However, ironically, some people wait for the eleventh-hour grab.

Competitor Rates – Hotels often attempt to increase revenue by aligning their charges. They align it with their competitors. The move helps them strategically position themselves in front of the customers.

Strategic Location – A few hotels have the edge over the rest. They are the ones centrally located in a city. Or nestled at the optimum distance from a popular tourist spot. Their room prices are usually higher, and their rooms are always booked way in advance.

Changing Seasons – It is another factor upon which dynamic hotel pricing is based. It is common knowledge that hotel rates plunge during the off-season. However, the same hotels can maximize their income. They can do so by increasing costs during peak season.

The Network Effect – The Network Effect is the by-product of a hotel’s popularity. Simply put, people are willing and happy to pay more to stay in a massively trendy destination.

Demand Prediction – Determining the right hotel prices requires a lot of preemptive planning. Prediction is also necessary. The management has to invigilate. They need to evaluate the demand level for each day to price the hotel rooms efficiently.

Business Rule – Government regulation is the last factor determining dynamic hotel pricing. State-sponsored bodies diligently monitor the hospitality industry. They are the ones set by such third-party agencies. The pricing strategies of hotels must comply with the rules.

The hotel industry can benefit from dynamic pricing. They can also benefit from hotel business intelligence in the following ways

• Increased Room Revenue and higher Average Daily Rate (ADT)
• Improved Revenue per Available Room (RevPAR)
• An efficient pricing process made easier and more precise via automation
• Hotels get the liberty to experiment and play around with high and low prices