this user will continue to buy fresh food? By mining user behavior

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If a user's consumption category changes from multiple to single, or the distribution of the average price of consumption changes from low to high or from high to low, and the frequency of consumption changes from stable to random or random to stable, it can predict a user's next consumption behavior. For example, a user on an e-commerce platform consumed digital fresh food in the last consumption cycle. The consumption category in this cycle only includes digital fresh food. The comprehensive customer unit price has increased from hundreds to thousands. The repurchase cycle trend has increased from days to days.



What is the probability that we can build a iran telephone code prediction model. The second step is to build a regression response model. It is necessary to build response models for the strategy group and the control group respectively. Finally, the target users are input into the two models and the t score is calculated. How can user operations accurately issue coupons by building a t model? With the help of analysis and mining tools, we build the above data flow.



Users calculate the response rate under intervention and non-intervention conditions. First, let's look at the prediction accuracy of the model. How can user operations accurately issue coupons by building a t model? Modeling data is used for training and testing. The training set prediction accuracy rate. Reached.; the test set prediction accuracy rate. Value.; The model prediction performance is acceptable. The third step is how to accurately issue coupons. The response model can help us generate several types of prediction graphs, namely response graphs, gain graphs, and profit graphs. We can guide the marketing actions of coupons based on these types of graphs.