Ding Xiaogang, founder per capita: driving the development of physical retail industry with data

Editor: Topology Society? Van Zhao

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Founder per capita &; Ding Xiaogang, CEO

Heimaying 12 student, serial entrepreneur. 10 years ago, he served as the executive director of an IT company, managing a company with 120 employees until the company was acquired by the IBM team. After three failed ventures, he hung out in listed companies and was in charge of the company's core customers. I used to be a senior consultant of Ipsos, and I have always been good at corporate services. I believe that traditional retail is facing changes. Internet big data is the first and biggest profit growth point. I have personally served many well-known chain brands such as Samsung and Anta.

About per capita

Renren is the largest and only Internet-based customer data collection and analysis platform in the domestic entity chain retail field. Since the establishment of 20 14 in July, in just over a year, per capita has successively received two rounds of investment from well-known investment institutions, and the number of employees has rapidly increased from 3 to nearly 50, and offices in Guangzhou, Xiamen and Shanghai have been established. At present, the first product M series (passenger flow statistical analysis device based on domestic physical stores) has reached cooperation with 800 well-known chain brands nationwide, with more than 30,000 cooperative stores nationwide, and the classic case includes Carmen.

/The current situation faced by the physical retail industry/

This is an era of change, all kinds of changes are happening around us, and are changing our lives at an increasing speed. In the last two years, I have mainly done some work around the retail direction, so I have seen the current situation and changes facing the industry. Physical retailing is a very traditional industry. Since the rise of consumption in China in 1980s and 1990s, many changes have taken place. From the initial product and brand-oriented retail formats such as Li Ning and Anta to the fast fashion such as ZARA and Uniqlo, it began to appear and affect our lives. Of course, physical retailing has also encountered many challenges, such as:

Rising costs, e-commerce robbery

Sales are clear and users are vague.

Store traffic and never reuse it.

Brand loyalty is about zero.

I have heard a lot of truth, but I still can't operate it well.

So in the last two years, we have seen many brands close their stores. Of course, there are also new formats that have emerged under this pressure, such as fast fashion and complex stores like Sanfu Department Store, which are developing well. But on the whole, the traditional retail industry is still in an anxious mood, looking for a "life-saving straw." We can feel that the field of retail consumption is undergoing revolutionary changes, and many physical retailers must seek changes under anxiety. What remains unchanged is "waiting for death", and what may change is "waiting for death".

Let's look at the development of retail industry. At the earliest, traditional media brought traffic, and then physical stores traded online. After the emergence of Internet companies such as Alibaba and Baidu, they gained comparative advantages by using media online and online stores. But soon we found that users not only appeared in physical stores, but also appeared online. Especially in the era of mobile Internet, users need to consume and obtain services in various scenarios. Therefore, everyone agrees that both physical stores and e-commerce companies need to provide online and offline services that integrate scenes to meet the needs of customers. Therefore, the concept of omni-channel is very popular in the past two years, allowing consumers to get online convenience and benefits, as well as offline experiences and scenarios.

In fact, a large number of physical retailers know to embrace omni-channel and mobile Internet, learn the rules and concepts of the electronic world, and understand the consumption habits of these post-90s young people. However, little has really changed. Under the new situation, physical retailers will naturally have new demands.

/Demand of physical retailers/

According to the current situation of the mobile Internet, we can roughly summarize the new demands of the following physical retailers:

From operating stores to operating communities.

From single store profit to single customer profit

From IT thinking to DT thinking

From experience driven to data driven.

As shown in the above figure, retail includes market, stores, customers, commodities and other factors, in which many management tools and methods are implemented and used to organize these things together to promote the management of retail stores. The more traditional retail industry may not have this series of things on the right, but there are more on the left, and the earliest internet innovation is also produced in this part on the right.

Focusing on the above-mentioned demand transformation and the tools that stores need to use, we can abstract the demand realization of physical retailers under omni-channel, as shown in the following figure:

Under the new situation, traditional retailers need to have strategic thinking, make some changes at the strategic level, and cooperate with mobile Internet tools, DT thinking and user-oriented business philosophy. With these things, we can meet the needs of physical retailers to embrace the new environment and new consumption and go further.

/What is everyone doing? /

Faced with this situation and demand, what is everyone doing? Simply put, the per capita plan is to introduce DT thinking from the decision-making level, cut into the traditional retail industry by filling in blank data, and let traditional retailers rely on data to support decision-making, instead of relying on data to make decisions as in the past.

In the retail industry, an important data is lacking, that is, customer data. Let's help traditional retailers fill in these blank data by the following methods:

1, wake up the sleeping data

First of all, we should wake up the sleeping data of traditional retailers, because they have a lot of data, which may be scattered, online and offline. It is a data source in the form of reports, but it has not been awakened and utilized. The retail industry has a lot of data, including people, goods, markets and wealth. Traditional retailers pay more attention to goods, markets and wealth, and pay most attention to people's data, that is, a set of membership system and employee data.

For Internet companies, they have a profound understanding of users and a thorough grasp of people's information. Most users are equivalent to "streaking" online. Offline retailers know little about people or customers. So we think this is a blank data, and the physical retailers have not paid attention to it or collected it well. We just help them collect it. Everyone will help customers collect new data in the fourth dimension, such as passenger flow data, frequency of entering the store, trajectory, product attention and so on.

2. Relevance | Revitalization

Everyone will combine these collected new fourth-dimensional data with the original data for further analysis, correlation and revitalization, and give the basis for decision-making according to the law of data formation, and use data to drive retail decision-making:

Understand consumers

Efficient marketing

Target product/service recommendation

Consumer care

Personal meter can help retailers to correlate and update data by measuring, analyzing and improving the following processes:

① Measurement: Collect blank data in store operation.

② Analysis: Diagnose and analyze the store operation through data indicators.

③ Improvement: Provide improved tools and methods.

Per capita, the number of stores served in the past two years exceeded 30 thousand. We find that brands or retailers with higher popularity, larger scale and more stores will pay more attention to and understand such changes.

/What problems have we encountered/

1, these are two different worlds.

In fact, in the whole process, we also encountered many problems. First of all, these are really two different worlds. Different ideas, experiences or experiences, as well as different success paths, bring different ideas, starting points and conclusions about consumption. In the Internet age, what we pay attention to every day is traffic, the connection between people, the connection between information and so on, which are the natural advantages of the Internet. The cost of obtaining data from the internet is the lowest, so everyone will pay attention to the changes of these data. Whenever a new version of a product is released, it will be modified through data changes, which is a natural habit and method. However, offline physical retail stores will not do this, especially some brands that have been very successful, and may encounter more such problems.

However, these two worlds will merge soon in the future, and the trend of integration will be faster and faster. This change is very big. Therefore, traditional brands have realized the existence of these problems, and are looking for solutions, but also probably know the solutions. However, there is still a big gap between what can be imagined and what can be done, especially those brands that have been very successful. I think it needs a lot of people who know the electronic world and the atomic world to help them bridge the huge differences between them and make the two worlds merge faster and faster.

2. Tool thinking or strategic thinking?

Tool thinking or strategic thinking is also a very important problem we encounter. This problem leads us to use the thoughts of the electronic world and the words of the atomic world to help the physical retail of the atomic world make some changes, but many times we still have to make them feel that this is a tool, and it is still very difficult to change them from a strategic thinking. So this is one of the very serious problems we have encountered.

/everyone's new thinking/

China's retail industry is a huge market, which needs many people to try and think. We are glad to see more and more entrepreneurs and innovators leap from the pure Internet industry to the traditional industry, and can calm down and understand the traditional offline retail and help them make some changes.

In the picture given above, basically some people are trying to make some tools around the retail industry market, shops, customers, goods and wealth, and there are also many very good tools or platforms to help the retail industry make some changes. I also hope that people who have a very good traditional retail concept or a very good Internet concept in the future can do some cross-border and accelerate the process of integration. In addition to the Internet, there are some new technical directions, such as VR, AR, AI and so on. This will play a good role in promoting the development and progress of the retail industry. We are also trying to learn and understand these new directions.

Finally, whether online or offline, I believe that in the near future, a more harmonious and unified concept or method will be used to bring consumers a more concise, convenient, fast, cheap and interesting shopping experience and service experience.

/The following is a part of Q&; Content/

▎: What are the successful cases in which companies use data to greatly improve their operations, and how did they do it?

An obvious example is the fast fashion in clothes, such as ZARA, Uniqlo, or some domestic brands such as UR, Carmen, Sanfu and so on. They all regard data as very important. For example, ZARA can go to all the stores in the world within two weeks, and these new designs can reach consumers within two weeks. He can do it. In addition to the supply chain that people often mention, they are also very important for the collection and application of store data. Without these detailed data, the supply chain behind can't respond quickly. For example, the manager of Uniqlo has great power to decide whether the store should do some promotion recently, what style to use for promotion, what kind of goods to order next week, and what the quantity of these goods is. Why can they do it? Because the store manager has a lot of data to help decision-making, the store manager not only has his own store data, but also can learn the data of other stores in the whole brand. These fast fashion brands are driven by these rapidly changing data collection and analysis.

On the other hand, we went to see traditional retailers. A few years ago, everyone knew about Li Ning. There have been various dealer problems, and the number of stores has been reduced from more than 9,000 to more than 6,000. Why? In fact, it has a strong sense of * *. Traditional retail brands and retailers are actually two completely different ideas and ways. Brand owners produce products and push orders through their channels. As for how the dealers sell and the customers' feedback on the products, these are completely out of touch with the brands. Even some brands spent half a year or three months collecting the retail data of franchisees two or three years ago. Can these outdated data be collected to support decision-making?

A year or two ago, it took a year for many brands to design clothes and put them on the shelves, and there was no data to support them in making decisions. Therefore, similar to fast fashion brands, we believe that what really supports their decision-making is data. They have been very successful by using only one important aspect of the data, that is, matching and getting through the data of retail and flexible production and supply chain, so that they can know what goods need to be replenished this week and next week every day, because the trend of the data has told me the whole situation.

Traditional retailers are different. Franchisees don't know the specific sales situation until they reorder. These are some changes in retail data. Of course, there are also many brands in their direct store system that can do some such decision support. As for the customer's understanding, there are not many cases where offline retailing can be obtained, or online retailing can do better in this piece.

▎ What dimensions of user data are most worthy of physical retail to obtain and use?

From the most worthy point of view, it must be more detailed data such as customer identity and preferences, because only more detailed data will have the opportunity to understand customers from the smallest granularity, but there will be technical or methodological obstacles in the middle.

From different levels, to understand customers, we need to know the customers of the whole store first, such as: traffic, how long customers stayed, visit time and so on. To be more detailed, it is the middle-level data, such as which goods customers stay in front of, how long they stay, what kind of goods they experience, how to walk around the store, and which areas they stay longer, etc. Microscopically, it is personal data, including who this person is, what his label is, how he came from, what his online identity is, what contact he has with us, what he bought from us, his consumption habits in the business circle and so on.

These data are basically blank, except that traditional CRM may collect the result data after the transaction of our store or brand. We think these data are all useful, and the most useful data is more detailed data. However, due to technical problems, such as: it is difficult for us to accurately identify customers who have not communicated with me when entering the store, and there is no way to collect these detailed data well, whether through face recognition or the mac address of WIFI, so let's start with some rough data. Whether it is macro data, meso data or micro data, we think it is worth accumulating, because in the era of big data, there is not only a large amount of data, but also a very important dimension, that is, it takes longer to accumulate in order to form a contrast. Therefore, you have to accumulate or "raise" data first.

To sum up, we think that richer individual data, richer dimensional data describing individuals, and even cross-brand and cross-line integrated data are more important, but there are no very good methods and means to collect these fine data. In this case, it is very important to forward slightly thicker data, such as store data, medium-sized regional data and so on.

For e-commerce, what is the logic of establishing an analysis model?

The logic of establishing an analysis model is actually very simple, just like we often say artificial intelligence. In fact, the essence of artificial intelligence is an inductive method. The same is true of the logic of e-commerce. In essence, it is a process of continuous iteration and trial and error, which allows machines to establish causal relationships in a stupid way and correct the calculation methods and weights of these models according to the degree of correlation.

▎ What stage of development is the chain data analysis industry currently in? What do you think the approximate market is like? What is the situation abroad?

Compared with foreign countries, the analysis and understanding of data in China is actually far weaker than that in foreign countries. Many foreign companies will provide such services for retailers, which is also caused by the compulsory retail environment abroad. We know that in the last two or three decades, the domestic economy has developed very fast, which has also driven the explosive growth of the retail consumption market in China. Although the year-on-year growth rate dropped below 20% after 20 12, the growth rate is still very high, which was above 20% before. When 20 165438 and 20 12 fell to 15.7% for the first time, many retail investors said that winter was coming.

In fact, when we look back at European data, the growth rate for many years is 2%, 3% and 4%. There is no way to grab land at such a growth rate. They can only go to intensive cultivation, so they analyze the data and understand the users much earlier than we do. For example, the often mentioned story of Wal-Mart's "beer+diapers" is a typical example of data analysis. Therefore, these companies doing data analysis abroad, especially those consulting after data analysis, are actually living very well.

However, in China, this market is actually in an awkward state. Just like the tool thinking and strategic thinking mentioned above, most domestic customers, merchants and brands pay more for tools, and it is difficult for tools to obtain a higher premium. Even if you have manual consultation, it is still not so valuable in front of many customers. Therefore, on the one hand, it needs to be cultivated in the domestic market, because they are not so willing to pay for data analysis and consultation; On the other hand, even if they are willing to pay, the price they are willing to pay is not that high. The final result is that compared with foreign countries, this market is a very good one; But at this stage, it is still in an embarrassing situation.

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