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How to use B2B with data operations

Enlarge fontReduce font Release date: 2019-01-18 Views: 756
Core tips: On August 31, the Alibaba Data Innovation Summit and the 2nd Data Pioneer Awards were held in Alibaba Hangzhou Xixi Park. This time held by a business consultant, the theme was "Discover New Wholesale
On August 31, the Alibaba Data Innovation Summit and the 2nd Data Pioneer Awards were held in Alibaba Hangzhou Xixi Park. The summit held by business consultants, with the theme of "Discovering the Power of New Wholesales", collaborated with 800 individual businesses, content professionals, trading companies, wholesale brands, and service providers in the wholesale ecosystem to reveal to us why they The only secret to becoming a big seller is to log in to business consultants every day and use data products to stop decision-making and analysis of my operations, so that 92% of people are still viewing data in the middle of the night. The result of this report is undoubtedly a wake-up call for wholesalers and B2B merchants who do not yet know the data.

In the period when data is king, people who are older than you are still looking at data in the middle of the night. Can you still get enough food and sleep?

Related to wholesale, B2B merchants will increasingly rely on data. Because the stability of B-end buyers will be relatively high, they will pay more attention to production quality, supply stability, and product style when selecting the required products. They will have more assessment aspects and be more cautious when purchasing. Therefore, the seller must do a good job of market analysis, customer group analysis and prevalence analysis at the product development side. There are some 1688 merchants. In fact, operating online stores is based on my many years of business experience to regulate my online planning for half a year or even a whole year. Experience is the result of years of theoretical accumulation. We cannot deny it, but we must recognize its limitations and high risks.

There are still many businesses that continue to use their traditional operation methods to operate their 1688 stores. Their daily operations are process store decoration, title optimization, product release, information optimization, and even ordering for ranking, but they are short. The necessary science is more a simulation based on habits or echoes. Nowadays, the development of the e-commerce industry also pays more and more attention to data. As a B2B seller, if you want to do 1688 online business, if you do n’t understand the data without data, you will definitely not go far.

In the big data era, the operation method also needs to be separated from the data, and the market response data is used to perform corresponding operations. In fact, Zhu Jiang, CEO of Shutter Network, put forward and put it into practice in 2014. As a result, the agent operation company he set up has become a dark horse with its own glory in the B2B operation industry, and has received the approval of many customers, peers, and Ali Xiaoer. This operation method is called "data operation".

What is the form of data operation?

Data operation means to stop multi-data integration, cleaning, excavation, loading and visualization analysis based on industry big data, to provide enterprises with a year-round product line plan that caters to the needs of sellers in the 1688 wholesale market, and to provide product categories, hot selling attributes, hot selling in each season The price and competition status are given to the product design department of the factory, and the product development of the factory is pushed back in accordance with market demand to assist the enterprise to maximize profit, sales and efficiency. This is Zhu Jiang's repeated operation and summary for many years, separating the abundant application of data, and then grinding out a set of operating forms applicable to all 1688 members.

In fact, to summarize the data operation form in one sentence, it is to use market data and store data to operate. The data itself is actually of no value. What is valuable is the information we extract from the data, so it is important that we stop the integration, cleaning, and exploration of the data.

When we use data for operations, we first need cognitive data. All ordinary data can be divided into three types of dividends-past, present and future. These three types of data are one-way activities. As time progresses, the future will become the present and until the past. However, each type of data has a very clear effect dimension in its corresponding time period. From our store data to understand the role of these three types of data will become clearer. The past data in the store includes all historical data such as historical store data, refund data, order data, etc. We can use it to summarize, compare and refine the knowledge points. The data in the shop today is the shop data of the day, and we can use it to understand the current situation of the shop and find out the problems. The future data is our response to the historical data of the store and the data of the day, so that we can make a series of corresponding store planning, sales planning, etc., a forecast of the purpose of the upcoming store demand data.

Second, we need to educate our digital mindset. Zhu Jiang also summarized the five most commonly used ideological methods in the operation process: control thought, split thought, dimension reduction thought, dimension enhancement thought, and hypothesis thought. We mentioned earlier that an independent piece of data is worthless in itself. As long as we compare it with other data, we can discover their differences or common ground and obtain certain valid information from it. This is the idea of comparison. Its application in store operations is very common, for example, it is used to select models, measure models, and monitor store data. When we looked at the back office data for the day of the store, we found that today's sales are only 50% of yesterday.

Related to simply looking at the single data of sales, if we analyze his key components, for example, sales are composed of the number of users and unit price, and the number of customers is composed of the number of visitors and the conversion rate. We will become clearer and more intuitive. This is what we call the idea of splitting, which breaks down the objects we need to analyze into various combined parts and analyzes from the details. When too much data is not conducive to analysis or the current dimension of the data cannot be directly used for analysis, we must stop selecting the data or perform an additional operation to make it valid data. This is the idea of dimensionality reduction and dimensionality enhancement, and the two are corresponding. When we are customizing shop sales, we do not know how to formulate a reasonable purpose. At this time, we can first assume the result and apply reverse thinking to reverse the operation plan. This is the hypothesis, which is the assumption.

Finally, when we stop a series of scientific analysis of the data, we formulate the best operating plan, and then execute and summarize it in time. Think about the direction of resolutions and the depth of implementation.

The center of Zhu Jiang's set of data-based operations is that each step of the operation is based on practical data, not by the operating commissioner. After a set of data, the information we can obtain is unlimited, which is why data is emphasized today. Alibaba CEO Zhang Yong also said at the annual meeting of Ali B2B business group that when a fast-changing digital economy comes, it is more important to adapt to change and lead change!

In fact, Zhu Jiang can also be said to be the pioneer who led the change. He was the first Ali to put forward a digital operation form, although he also called this type of operation at the time as "Zhujiang operation." It wasn't until he left Ali in 2014 that he created a company that actually does business for customers, and he officially renamed this set of operations as "data-based operations." Zhu Jiang and his company used this set of data-based operations to serve dozens of industry first, industry top ten, and industry top fifty stores in the past three years, and achieved certain results.

The period when data is king has come. If B2B sellers want to be bigger and bigger, they must adapt to the changes and understand the data to play with big data.
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