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What data do you need to understand in the precise operation of tea?

at the 21.22 million drinking power conference in Kamen, brands are talking about one thing: using data to guide operations. Some brands use data to do precise marketing, precipitating more than 211,111 members a month, and the repurchase rate has increased by 5.4 times; Some use data to analyze user habits, so that the repurchase rate of small programs reaches 45%, exceeding the industry average. In the tea industry, data is playing its role and becoming more and more important. Refined changes are accelerating, and head brands are looking for profits in the data. In the past two years, tea brand stores have been growing, potential brands have emerged one after another, and market competition has been intensifying. The market inevitably enters the "stock" stage, and every practitioner is trying to revitalize the existing resources. And this has also prompted more refined operation methods and business concepts to be put on the agenda. For example, match different marketing strategies to different groups of people, and recommend different product combinations to stores in different regions in order to obtain better transformation effects. The premise of refined management is the cognition of digitalization and the control of data, which is more obvious in the post-epidemic era. According to Accenture's report "Digital Transformation Index of China Enterprises in 2122", nearly 61% of China enterprises indicated that they would increase their investment in digitalization in the next 1-2 years. In the tea industry, head brands have put their energy into the cultivation of data ability to cope with the test. For example, at the beginning of the school season, the book also made a precise marketing for students with the support of data: using data to gain insight into college students' "consumption influencing factors" and "consumption behavior habits", giving accurate discount strength and discount times, and guiding college students to become members and continue to operate. This move precipitated more than 211,111 student consumers within 31 days, of which 29.16% were new members that the brand had never consumed, and the repurchase rate of members increased by 5.4 times within 7 days. After a comprehensive data pull-through, the third chapter of Taoyuan also focused on "tea latte", focused on student groups and sinking market, and used data to analyze user habits and platform characteristics for precise operation, achieving a repurchase rate of small programs of 45% and a community conversion rate of 41%. Whether it is accurate marketing for the target population or adjusting the operation mode according to the characteristics of the platform, the above are only the "partial functions" played by data. Then, what data do you look at in different links, and how do you analyze the existing data to improve the turnover? After in-depth study of the actual combat experience of 15+ head tea brand, Yunyun Shuying refines and draws a knowledge map, namely "China Fresh Tea Management Data Map", which covers four modules: people, goods, market and revenue * * * 511+ data indicators, 11+ business data, healthy traffic light reference values and business intelligence application examples, so as to help the brand straighten out the data system. To this end, I interviewed Miao Yu, assistant president of Cloud Migration Technology and general manager of Cloud Migration Digital Profit Division. How do tea brands look at data? Here is a "tea business data map". In daily operations, tea shops generate a lot of data every day: membership data, transaction data, inventory data and so on. Miao Yu said that at present, it is not the "data blank" that bothers most tea brands, but the "lack of analyzability of data". For example, the same "Jasmine Tea" is called "Jasmine Tea (large, medium and small cups)" on the take-away platform, but "large cup Jasmine Tea" on the applet. Different names will affect the SKU number of the database and greatly reduce the accuracy of data-driven business. Therefore, in order to make the data analyzable, the first thing is to establish standards. Through OneID, every product, member and channel data can be traced and empowered for business growth. "This is also the concept of cloud migration. Business+data are double-central, and business data is pulled in two directions, which feeds back each other." Miao Yu told me. Data Map of China Fresh-made Tea Management (Excerpt),