Post by account_disabled on Feb 27, 2024 2:49:49 GMT -5
These reasons need to be obtained by tagging content and products In principle the more behaviors consumption interactions a user accumulates under a label the more demand the user has for the contentproducts under the label a product we should try it several times to expose the product to users so that we can accumulate data and make reasonable inferences as shown below The principles of user analysis are used by all major Internet companies Rule Combine testing with mining After completing the first step many people will naturally think of analyze how heavy users evolve from light users step by step sum up the experience and copy it to other light users The idea is good but it may
not work because the products and services a company can provide to users are limited and can only attract specific users Therefore light Europe Cell Phone Number List and heavy users are not necessarily the same type of people Therefore through the consumptioninteraction process of heavy users a growth path can be theoretically summarized Users enter from XX channel and have XX characteristics The user experienced XX product for the first time and then repurchased it X days later After the user purchases a cumulative amount of XX he begins to expand his consumption
categories BUT this set may not be useful for all light users so you may need to develop a few more test lines and use different methods to stimulate light users to see which one works There is a classic problem here which is many people rely on data to calculate an optimal recommendation rule and activate light users in one go This is difficult because light users often accumulate very little data and it is difficult to draw valid conclusions in the absence of testing Therefore it is strongly recommended to do more tests and s and beauty.
not work because the products and services a company can provide to users are limited and can only attract specific users Therefore light Europe Cell Phone Number List and heavy users are not necessarily the same type of people Therefore through the consumptioninteraction process of heavy users a growth path can be theoretically summarized Users enter from XX channel and have XX characteristics The user experienced XX product for the first time and then repurchased it X days later After the user purchases a cumulative amount of XX he begins to expand his consumption
categories BUT this set may not be useful for all light users so you may need to develop a few more test lines and use different methods to stimulate light users to see which one works There is a classic problem here which is many people rely on data to calculate an optimal recommendation rule and activate light users in one go This is difficult because light users often accumulate very little data and it is difficult to draw valid conclusions in the absence of testing Therefore it is strongly recommended to do more tests and s and beauty.