Big Data How to carve out a new outlet for the winter food?

The catering industry is really not going to do it? Originally is a single-minded solution to eat the sweet cause of the problem, China's well-known restaurant chain Enterprises Xiang-e love must half-hearted to engage in technology, this is not forced to let the chef to become a scientist! Network new media and large data Joint laboratory "This series of academic language, you can imagine this is the development of Xiang-e" new dishes "it? can large data really open up a new outlet for the cold winter in the catering industry?

Big Data How to carve out a new outlet for the winter food?

Stone Chapter Strong

This is a time of cross-border, and many irrelevant things are linked together. Maybe a few years ago, many of the restaurant's big guys were munching on the big cakes that were just needed, but mutation, a few years later the catering industry has become a youngster's world, sell a pancake dare shout to 10 billion forward, sell a brisket all said I was using the most advanced Internet marketing thinking. The big guys finally sit down, Xiang-e sentiment is taken as the first step.

We are entering the "Big Data" era, large data applications show great economic value. And for the catering industry, is really to make full use of large data, may build a laboratory is far from enough.

Stepping into the first block of large data--o2o closed loop

Now the restaurant industry many practitioners to find a public comment, the United States Group chat, and then sign a contract to dare to say that they are new era catering O2O model pioneer. In fact, they just do a little bit about the spread of the surface of things, O2O is the value they do not realize, and not really to dig. The real value of catering O2O mode lies in the seamless closed loop of information through online tools and cloud server, CRM and catering management system, relying on cloud computing function to process, transform and apply large data. Therefore, only the seamless integration of online resources under the line, the formation of O2O closed loop is the key to enterprises can enter the era of large data.

The difficulty and pain point of the catering O2O closed loop is how to collect the feedback information of the consumer experience under the line, and to lead the offline users to the online communication and to carry on the online experience. Some businessmen think that they have prompted consumers to complete the online payment is O2O closed loop, this is a superficial idea. To send consumers down the line to the line, this line is not just pay, but to form the online consumer and consumer, consumer and business interaction.

Interaction requires a platform that can accommodate consumers and businesses. Now it seems that the micro-trust platform is a good choice. Create a public platform on the micro-letter to interact with consumers. The interactive topic can be to allow consumers to design their own favorite menu, so that consumers themselves to design their favorite dishes. Once accepted, the consumer can get a prize, or the dish is always free to the designer.

In this way, in addition to the platform to complete the meal reservation, ordering, payment and other functions, but also according to consumer consumer behavior targeted promotion and promotion, more importantly, can give full play to the role of the fan economy, so that fans participate in service improvement, food improvement, improve customer satisfaction and enhance the sales and image of businesses.

Since then, the consumer from the line and then lead to the line on the way to achieve, this is a real O2O closed loop. From line to line, from line to line, consumers are being led, data and information will flow into the merchant's pockets.

Dining O2O large data from line to line

O2O from line to line is mainly a process of drainage, in the catering industry, the current drainage mainly includes group buying and ordering two channels. Before the big data is applied to the catering O2O, the drainage method of group purchase is simple and rough, it is to attract the consumers to bring the traffic on line to a restaurant which is willing to sacrifice profits for the flow. And the way to order is simply ordering, booking, online payment and other processes. When we use large data to think about how to drainage, we will find, in fact, catering operation can also be very high-end, very intelligent.

1, large data-driven group buying mode

May 17, Baidu Glutinous Rice launched 517 Cargo Festival, from May 16 to May 18 in Beijing, Shanghai, Chengdu, Xian, Xiamen 5 major cities, the use of large data Baidu to screen out the user's attention to the special dishes, find the most authentic Top10 restaurant. The activities of the daily 9:17 to 20:17, hundreds of seconds to kill food products sold only 5.1 yuan 7 cents.

This is the new type of big data driven by Baidu Glutinous rice to buy the model. It relies on Baidu, the search data, geographical location, user browsing data comprehensive analysis, to extract the effective data on specific objects, and to assist related product operations and promotion. Baidu from the catering O2O to provide a large number of consumer data to find out where users, their favorite snacks, as well as the best of these snacks shop, and then invite these stores to participate in the Baidu glutinous Rice Regiment. Baidu glutinous rice through the large data analysis, find most people's preferences, so as to attract more people involved, this is the use of large data Baidu glutinous rice to drive group buying mode method.

In the Baidu glutinous rice before, the drive mode of group buying exists American regiment and public comment two kinds. The United States is a typical trading drive model, the business is relatively single, the profit is mainly from the Purchase Business transaction Commission. Public comments is a typical information driven model, relying on its early business comments on the accumulation of information, the public comments to expand the group buying business, and has become the main source of profit reviews. The two drive modes end up buying in the same way, gathering a large group of people online, and then luring them to the offline restaurant at a discounted price.

Previous years such a group buying mode is very popular, but also brought a certain amount of traffic to the restaurant, but this simple group purchase drainage method but slowly exposed his problem. Group buy drainage to the restaurant of the consumer's stickiness is very bad, they see is only group purchase concessions, and the restaurant's impression is not profound. Consumers will just keep looking for cheaper prices on the line without paying attention to which restaurant they are in. In this way, the restaurant sacrificed the part of the profit, but not to bring consumers to return. So, this kind of buying mode brought to the restaurant is only a moment of human traffic.

Baidu Glutinous rice is launched by this large data-driven group buying model is the restaurant like. In the case of consumers, they are still able to get preferential treatment from this group purchase mode, and they can satisfy the desire of cargo for local food. In the restaurant, such a glutinous rice TOP10 model is clearly the building of its own restaurant reputation, although it will sacrifice a certain profit, but it can enhance consumer stickiness, enhance the reputation of the restaurant.

2, large data for consumers to make decisions

You just have to pay, what to eat, the big data to help you make decisions.

BAT is now doing large data development, they want to use their own resources to build an intelligent data platform. Baidu through the collection of user's active needs of data, know what users want, through data analysis, Baidu know what users like. Ali before the introduction of Amoy Point, Amoy Point set meal, takeout and other functions as a whole, so Ali's data more clearly reflects the user's purchase needs. Tencent's data sources are mainly social networks, large amounts of data and scattered information points, not only to understand consumer preferences, but also to analyze the consumer's dissatisfaction with certain products.

Through the smart data platform created by bat, it can refer to people's decision-making process, help the users in need to make decisions and recommend the content that users like. When you are worried about what to eat and where to eat, you can take advantage of these recommendations to easily handle your eating problems.

Food O2O Line Big Data

Here the line is mainly refers to the restaurant store, in the store location and store traffic control, many businesses appear very helpless, because there are many factors they can not control. However, when we use large data to look at the problem, the merchant can finally hold the initiative firmly in their hands.

1, large data adjustment line store layout

Many restaurant chain in the location of the factors considered more is the cost of the store and the local people flow, in the store layout when not from the consumer's point of view, in the end where is the real consumer gathering place? Perhaps, at this point the intelligent analysis of large data can give you some inspiration.

Stick John through the O2O mode to do the takeaway business, stick John will order to the service center, unified supply chain integration, the user experience to unify, through the "three unified", will be online under the integration line. The O2O closed loop formed by "three unification" formed important large data.

The merit of John Johnson is the analysis and application of large data. Stick John promised to deliver for 45 minutes or so, a commitment that is closely related to the area where the restaurant brand stores radiation. John Johnson has a map of the area in his hand, and when he sees a blank place for a phone order, he says he needs to open the shop in that place. By using the large data obtained, Rod John can optimize the layout of its stores, and Johnson is making big data through the takeaway business to adjust the store layout strategy.

After the adjustment of the store layout is fully consumer-oriented, where there is demand, where there is my store.

2, large data control store traffic

Perhaps all hotel owners have had such an idea, in the business is hot, the store customer line waiting for the table, the hope that the customer hurriedly eat finished immediately leave. In the shop when the business is cold and want to let customers order more food, let them eat slowly, eat well.

The restaurant is facing a changing consumer group, the store's people flow is not the restaurant to average. When the staff, including waiters, cooks and managers of the efficiency of the ultimate, we are not able to actively control the flow of people in the shop? In another way, we can use big data to solve this problem.

Now a well-known fast food restaurant is using this clever method. The company uses video to analyze the length of waiting queues, and then automatically changes what the electronic menu displays. If the queue is longer, displays food that can be supplied quickly, and if the queue is shorter, displays those foods that have a higher profit but are prepared for a relatively long time.

This is a smart way to use large data for crowd control in the store. Through the video data, the backstage intelligent system can analyze the current human traffic, weigh the queue length in the store and the food supply speed, make a decision that combines efficiency and profit perfectly.

Dining O2O Large data on line

This is the most critical step in the O2O closed loop and the hardest step to control, because you can't force your customers. From the line down to the line, is the business of consumers from the line and then drainage to the line, the online interaction and experience of the process. In this process, the business need to do is to fully tap the consumer's own evaluation and feedback, to build a consumer database.

The current catering business is not aware of the importance of using large data to analyze consumer feedback. The catering industry is a word of praise, the customer's decision to repeat the restaurant business is good or bad. Customer feedback is critical when businesses build their reputation. We can use large data technology, analysis of consumers favorite dishes and the place to improve, digging out the consumer's expectations of the business to upgrade their service level, I believe that the use of large data to proactively improve their own businesses can be invincible.

The use of large data in the catering industry is still in its infancy, and many well-known catering enterprises are also investing money in the study of large data. The so-called wine is not afraid of deep alley, the reason, the catering industry is a heavy reputation of the profession. Large data can be excavated at all times changing consumer demand, so that catering enterprises continue to cater to the tastes of consumers, create better products, provide more intimate service to improve their reputation.

It is hoped that the cooperation between Xiang-E and the Institute of Computing Technology of the Chinese Academy of Sciences is not to peel off the food business to cut the wrist again. I believe that China's catering industry is not lack of market, but the lack of eyes to find the market, and the big data may be the one to tap the new market eyes.