How to use big data to do hotel management well

First, the support of big data is more conducive to accurate pre-market positioning.

To build a hotel, we must first carry out project evaluation and feasibility analysis. Only through project evaluation and feasibility analysis can we finally decide whether it is suitable to build a hotel. If it is suitable for building a hotel, what is the cultural theme of this hotel? What scale and grade will it be built? What kind of products are designed? What's the tour group like in the hotel? What price can you sell? Supply and demand in the future market, etc. These need to be determined before the hotel is completed, which is what we often call the early market positioning.

Building a hotel not only requires a lot of money, but also the construction period usually takes 3 to 5 years or even longer, and the construction cost is very high; Once the hotel is built and put into operation, it is difficult to change its market position. It can be said that the early market positioning is a work that cannot be deviated. Otherwise, it will bring immeasurable late losses to investors. It can be seen that the early market positioning is very important for hotel construction. Only by positioning accurately, even accurately, can the hotel adapt to the future market environment, build hotel products that meet the market demand, and be invincible in the competition. But to do this, there must be enough relevant data and market information for hotel researchers to analyze and judge, and working experience alone is far from enough. Usually, in the pre-market positioning of hotels, the relevant data mainly come from statistical yearbooks, industry management department data, relevant industry reports, industry expert opinions and local market surveys. Most of these data have the defects of insufficient sample size, time lag and low accuracy, and the amount of information that hotel researchers can obtain is very limited, which makes the accurate market positioning have data bottlenecks. With the advent of the era of big data, cloud computing and data mining technology can not only provide researchers with sufficient sample size and data information, but also provide researchers with a broader space for data collection, statistics and analysis by establishing mathematical models and forecasting the future market with historical data. Of course, it is difficult to complete the collection and statistical analysis of a large number of data only by the hotel itself, and the help of relevant data companies is needed to formulate a more accurate pre-market positioning for the hotel.

Second, big data will become a sharp weapon for hotel marketing in the future.

In hotel marketing, whether it is products, channels, prices or customers, it can be said that every job is closely related to market data, and the following two aspects are the most important in hotel marketing. First, by obtaining data and statistical analysis, we can fully understand the market information, grasp the business situation and dynamics of competitors, and understand the market position of hotels in competitive groups, so as to achieve the goal of "knowing ourselves and knowing ourselves, winning every battle"; Secondly, by accumulating and mining customer file data, the hotel can help to analyze customers' consumption behavior and value interest, better serve customers and develop loyal customers, and form stable member customers of the hotel.

In the traditional market competition mode, because hotels have limited data resources, they can only rely on limited survey data to compare and analyze a single competitor, so they can't fully grasp the market dynamics and the relationship between supply and demand, especially the competitive situation, and they can't determine the position of hotels in the competitive market, which makes it difficult for hotels to formulate correct competitive strategies. With the constant renewal of hotel marketing management concept, the original traditional marketing model has faced severe challenges, which puts forward higher requirements for managers to accurately grasp market information, accurately understand the dynamics of competitors and formulate appropriate prices. The analysis of market competition has also changed from the simple analysis of room occupancy rate, average house price and RevPAR to the data analysis of competitive groups, such as market penetration index (MPI), average house price index (ARI) and income index (RGI), and there are also time dimensions, market share and year-on-year change rate. Through the analysis of these market benchmark data, hotel managers can fully grasp the changing information of market supply and demand, understand the potential market demand of hotels, accurately obtain the operating conditions of competitors, and finally determine the position of hotels in the competitive market, thus playing a key role in formulating accurate marketing strategies, creating differentiated products and setting appropriate prices for hotels. The application concept of big data requires hotels to obtain these market data and provide help to hotels through statistical analysis technology. In the analysis of customers' consumption behavior and interest orientation, if the hotel is good at accumulating, collecting and sorting out customers' information and data on hotel consumption behavior, such as: customers' consumption in the hotel, selected booking channels, preferred room type, average stay days, purpose of coming to the hotel, favorite background music and dishes, etc. If hotels accumulate and master these data, they can master customers' consumption behavior and interest preferences through statistics and analysis. When the customer comes to the store again and finds that you have prepared his favorite room, playing his favorite music and recommending his favorite dishes, then he is already your loyal customer. So it can be said that the data contains the power of surprise. If hotel managers are good at using it in marketing, it will become a sharp weapon for hotels to remain invincible in the market competition.

Third, hotel revenue management is inseparable from the support of data.

Revenue management, as a theoretical discipline of hotel revenue maximization, has been widely concerned and promoted by the industry in recent years. Revenue management means to sell the right products or services to the right customers at the right time, at the right price and through the right sales channels, and finally achieve the goal of maximizing hotel revenue. To realize the effective combination of the above five elements, demand forecasting, market segmentation and sensitivity analysis are three important links in this work.

Demand forecasting refers to the establishment of a mathematical model through statistics and analysis of data and scientific forecasting methods, so that hotel managers can master and understand the potential market demand, the booking volume of future market segments and the price trend of hotels, so that hotels can adjust the balance between supply and demand in the market through price leverage and implement dynamic pricing and differential pricing for different market segments; When the market demand is strong, we can get more profits by raising the price, and attract tourists by introducing promotional prices and discount prices during the weak market period, thus ensuring the maximum income of hotels in different market cycles. The advantage of demand forecasting is that it can improve the foresight of hotel managers to judge the market, and put them on the market with appropriate products and prices in different market fluctuation cycles, thus obtaining potential benefits. Market segmentation provides conditions for hotels to accurately predict the booking volume and implement differential pricing. Differential pricing is the behavior and method of setting different prices for the same hotel products (like rooms, restaurants and sports) according to different market segments, which is characterized by charging high prices for customers with high willingness to pay and low prices for customers with low willingness to pay, thus leaving the products to the most valuable customers. Its scientific nature is reflected in formulating and updating prices through market demand forecasting, and maximizing the income of each market segment. Sensitivity analysis is to optimize the prices of different market segments through demand price elasticity analysis technology to maximize the potential benefits of the market. Hotel managers can find the best saleable room prices in different market cycles of hotel market segments through price optimization method, and reserve or reserve rooms for the most valuable customers through reservation control means, which better solves the problem that rooms suffer losses because of being booked by discounted customers too early.

The arrival of the era of big data provides a broader space for the development of hotel revenue management. Demand forecasting, market segmentation and sensitivity analysis need a lot of data. In the past, the historical data of the hotel itself were mostly collected for prediction and analysis, which easily ignored the external market information data, which inevitably led to some deviation in the prediction results. In the process of revenue management, if hotels can learn more market information on the basis of their own data, with the help of more market data, and introduce competition analysis, it will promote the formulation of accurate revenue strategies and earn higher profits.

Fourthly, the multi-dimensional analysis of customer reviews has become an important factor to tap the potential of hotel service quality.

Internet comments originated from Internet forums, which are social networking platforms for netizens to communicate with each other in their spare time. In the past, the online evaluation of the hotel by customers after staying in the hotel, which is what we often call customer comments, has not attracted enough attention from hotel managers. In view of the problems reflected by customers, most hotels did not reply in time or even did not reply at all. I don't know whether the problems reflected in customer reviews are solved in time in daily management, which not only widens the distance between customers, but also makes the information between customers and hotels more asymmetric and loses the opportunity of emotional interaction and communication between hotels and customers.

With the development of Internet and e-commerce, hotel guest evaluation is no longer a simple comment in the past, but a qualitative change has taken place. From the simple customer's praise and evaluation of hotel services in the past, it has evolved into an objective and true evaluation with multiple contents, channels and dimensions. The evaluation content of customers has become more professional and rational, and the distribution channels have become more extensive. Therefore, today's guest reviews are not only valued by hotel managers, but also highly concerned by consumers. A market survey shows that more than 70% of the guests will browse the hotel's guest reviews before booking, which has become one of the main motivation factors to lead customers to book this hotel. From a certain point of view, today, when the Internet has entered people's lives, guest reviews have become an important factor to measure the brand value, service quality and product value of hotels. Multi-dimensional collection, statistics and analysis of customer evaluation data will help hotels to deeply understand customers' consumption behavior, value interests and the lack of hotel product quality, and will promote product improvement and innovation, quantify product value, formulate reasonable prices and improve service quality. To do this, the hotel needs to be good at collecting, accumulating and counting a large number of guest review data, making a multi-dimensional comparative analysis, and finding valuable nodes from them, which will be more conducive to promoting the marketing and quality management of the hotel and gaining greater benefits from it.

To sum up, big data is not a mysterious word. As long as the hotel is good at accumulating, collecting, mining, counting and analyzing these data for my use, it can effectively help the hotel improve its market competitiveness and profitability and achieve good profits.