This gain value is often used to

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Issue coupons based on the gain graph. The gain graph shows the relative gain of the response predicted by the model compared to random selection. In a coupon campaign, the gain graph can indicate the additional sales growth brought by the coupon among users in a certain percentile. How can user operations accurately issue coupons by building a t model? The gain value in the coupon graph is . This usually means that the model prediction is . times better than random selection.Specifically, if the response rate of random selection is a fixed value, then the response rate after using the model prediction is .



times this fixed value. at a specific percentile, especially iran telephone code in marketing activities to determine which customer groups are most likely to respond to promotions. In practical applications, if the gain value is greater than , this means that the model's predictive ability is better than random selection. The gain value of . at the percentile in the gain graph indicates that the response rate among the users predicted by the model as most likely to respond is . times the response rate of the randomly selected users.



This is a relatively high improvement, indicating that the model's prediction at this percentile is effective. Based on the profit graph, the coupon issuance profit graph shows the total profit obtained by using coupons among users in different percentiles. For coupon issuance activities, the profit graph can help us evaluate the overall financial benefits of issuing coupons among different user groups. How to accurately issue coupons by building a t model for user operations. The parameter setting diagram is as follows: How to accurately issue coupons by building a t model for user operations. The cost of issuing each coupon is RMB.