The only example of a master-level profit-making through partnerships is Tsutaya Books. In 2005, Tsutaya Books' parent company launched the points system, hoping to use the points redemption business to connect the points and membership systems of various Japanese retailers. At first, Tsutaya Books' cards only facilitated users to purchase and borrow books, and they could use consumption points to enjoy discounts and benefits to increase the bookstore's repurchase rate. Then, using the huge "card" member data, Tsutaya Books analyzed users' consumption behavior, portrayed user portraits, improved the quality of bookstore selection, and achieved precision marketing. With the continuous expansion of the scale of operations, it accumulated tens of thousands of member data. It began to actively seek alliances with large supermarkets, restaurants, convenience stores, gas stations, banks, telecommunications and other industries, or exchange resources to promote the card system to other industries. After more than a decade of development, major points cards in Japan, covering more than 10,000 stores in Japan, accumulating consumption data of 10,000 Japanese people.
At the same time, this has become the "magic weapon" of Tsutaya Books and israel phone numbers even the group. At the same time, when users buy in other stores, the card system will also analyze user preferences and accurately push new products. After the order is converted, the group can share the order. Today, Tsutaya Books' income depends on bookstores and other retail income from the card franchise business. . Big data aggregation analysis companies often overlook big data aggregation analysis Big data is the result of network effects and continuous relationships. These data come in various forms, including salary data, demographic data, or behavioral pattern information. Using big data to track customer behavior has shown incredible development momentum. For membership companies, one of the great benefits of big data aggregation analysis is that it can observe member behavior over a long period of time.
Longitudinal data collected over a long period of time not only has various values for companies, but also for individual members or other types of organizations. For example, LinkedIn can collect data on employees of a specific company and then provide very useful company profiles to share popular employees and job titles. This is priceless competitive intelligence. This data is invaluable to companies and partners. On the one hand, it can provide additional value to existing users, and on the other hand, it can cultivate a new group and become a new source of income for the company. See the Tsutaya Bookstore case mentioned above. . Advertising revenue You can let other brands contact your members and have the opportunity to generate revenue, but remember that it must match your own business and create value for your members. There are two extreme or wrong practices.