Travel: How to turn big data into commercial value
Come to a scenic spot with beautiful mountains and rivers, check in at an inn, unload your luggage, open WeChat to find free WiFi, and you can see authentic gourmet restaurants nearby, with map route guidance and comments from past tourists-this is the most advocated scenario of smart travel by the National Tourism Administration this year.
behind smart travel, there is the support of massive big data. These seemingly dull data can create huge commercial value for tourism industry operators, so how to use them?
forecasting and tracking
Huang Rong, who founded the online B2B ticket manager, recently founded Juchuang Zhilv, a new company that combines the concepts of big data and smart travel.
"I understand that smart tourism is a smart city built by the government. In the future, tourism enterprises need to achieve seamless interaction with tourism consumers under the background of high mobile Internet in the era of big data. Its application scenarios should include near-field payment, mobile terminal payment, mobile data management, social marketing, etc."
with this concept, where does big data come from?
Many tourists have begun to try big data collection and smart tourism development, such as Ctrip, Tongcheng and ticket manager.
Lan Meiling, general manager of Ctrip's Raiders community institution and smart tourism business, told the reporter of China Business News that after Ctrip collects data, it can know the booking situation of various tourist destinations, hotels and scenic spots. The primary function of these figures is to give market pre-judgment to upstream and downstream industry chain operators.
Lan Meiling pointed out that at present, Huangshan, Jiuzhaigou and other famous scenic spots pay great attention to the problem of tourists' quantity and safety, which is particularly important during the Golden Week, but it is difficult to predict how many guests come to the scenic spot every day, so Ctrip's big data plays a key role.
"The booking data of our scenic spot and nearby hotels is equivalent to telling the scenic spot how many tourists you expect in the near future, and whether their travel structure is family or business. We will give these data to the scenic spot in the form of a forecast report. This allows them to make safety and market preparations to control passenger flow. For us, it strengthens the resource cooperation between OTA (online travel enterprise) and scenic spots. " Lan Meiling said.
Another feature of Ctrip Big Data is "Lifelong Footprint", which is to record the places that users have visited or even the records of their fingers.
"For example, if a guest clicks and browses Singapore tourism, and then clicks on several scenic spots and hotels, all these can be recorded and tracked, and then combined with his final order, the system can know the preferences, consumption positioning and consumption habits of the guest, and even his dining habits. In the future, Ctrip can conduct accurate marketing according to the consumption characteristics of customers. Precision marketing is very important, and the profits contributed by accurate and effective customers are the highest. " Lan Meiling said.
hidden business opportunities in big data
Tomatoes is an enterprise that develops smart tourism, which mainly cooperates with inns in tourist cities. Recently, it has just developed a smart tourism product-Zhilian Ancient Town, which means that after visitors arrive at the store, they don't need to go through complicated registration procedures, just connect to the WeChat WiFi of the inn and enter the service page, that is, they can quickly check in and be automatically assigned to the room. When checking out, you can quickly notify the boss to prepare for settlement through the quick check-out on the page. At the same time, in terms of payment, when guests only need to check in quickly, they can easily get the payment link by choosing WeChat payment. Of course, they can also easily scan the code to pay the room fee through the innovative "virtual POS- fast payment" method provided by "Tomatoes Come".
"Through these intelligent services, we can get the customer's usage and their occupancy and consumption data, which is very precious. We will analyze it according to several indicators and then bring great commercial value to the tourism industry chain. " Zhao Yonglin, director of the operation of "Tomatoes Come", told the reporter of China Business News that based on these data, it can analyze the occupancy rate of rooms, and analyze the occupancy rate, income changes, year-on-year and month-on-month ratios. According to the analysis results, inn hotel operators can improve the occupancy rate by renovating the inn, changing the room type and regulating the house price. For example, if a hotel has the best sales volume and the lowest occupancy rate of standard rooms this year, then it can consider reducing the number of standard rooms and transforming them into queen rooms in the future, or lowering the selling price of standard rooms and doing promotional activities for standard rooms, so as to improve the hotel occupancy rate.
Tourists' big data also accurately shows booking habits, attribution sources, age segments, gender statistics, check-in time statistics, consumption content statistics, renewal statistics and so on. In Zhao Yonglin's view, these data are extremely valuable, because the gender ratio of guests can improve the decoration style of hotels or restaurants to meet the preferences of mainstream customers; The age ratio can make the industry tend to be younger or middle-aged in service; The data of the proportion of guest areas can allow the operators to operate differently in terms of meals and living habits between the north and the south.
"If 6% of a hotel's guests come from Beijing, and 7% of its customers are young people aged 18-26, mostly women, then our system will suggest that the hotel should pay more attention to its advertising and word-of-mouth publicity in the future, and the decoration and service of the inn should be more youthful and feminine in Beijing. At the same time, we can consider organizing some activities that young people like to enhance the popularity of the inn, which will help the operators to increase their income. " Zhao Yonglin pointed out.
in addition, tourists' consumption records and data can also provide horizontal comparative data of the industry. For example, the ranking of a hotel's occupancy rate in the region, the proportion of channel cooperation in the region, the average house price in the region, the price adjustment of holidays in the region, the situation of staying in the region, etc., so that hoteliers can be more aware of the business situation of their peers and improve their performance in a targeted manner.
an inn operator in Lijiang said that according to the above regional ranking data, it was found that its occupancy rate was 6% in holidays in 214, and the price increased by 4% compared with normal, while the overall occupancy rate of Lijiang regional inn was 89%, and the price increased by 12% compared with normal. The inn operator calculated an account, and according to the occupancy rate, house price and the average level and increase of the market, he thought that the price should be adjusted on holidays to control the increase and improve the occupancy rate, so as to gain an advantage in peer competition. This is equivalent to hotel revenue management, which is helpful to improve the profit rate.
"We can provide basic information management such as inn orders and financial management, and also provide services such as' monthly report' and' annual report' for tourism industry chain operators according to the above data classification and analysis. The main purpose is to let operators clearly understand the characteristics of themselves, customers and the market, and improve services and hardware according to the results of data analysis. " Zhao Yonglin said.
some tourists report that through the above-mentioned index analysis of big data, for the tourism industry and tourists, the changes of occupancy rate, average house price and holiday house price obtained from big data analysis, as well as the changes of overall occupancy rate, differences in booking habits of tourists in tourist destinations, days of stay, consumption content, consumption amount, tourism heat analysis at various times, consumption difference analysis, etc., can provide real-time data reference for industries, scenic spots, tourism management institutions, etc., directly. If the improvement is proper, many operators can usually increase their income by 2%~5%.
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