User coupon behavior forecasting method in e-business environment and model building method

Abstract

The invention discloses a user coupon behavior forecasting method in the e-business environment and a model building method. The user coupon behavior forecasting method includes the steps: performingfeature extraction on data of user coupon use conditions to obtain features to be analyzed; performing multiple data sampling to form a plurality of classification models by the aid of classificationmodels of machine learning, gathering the classification models to form an integrated model; performing forecasting analysis on the features to be analyzed by the aid of the integrated model, and screening features to be analyzed maximally relevant to coupon use behaviors. According to the forecasting method, the coupon use probability of a user can be more accurately forecasted, so that a commercial tenant has a reference factor when issuing coupons, so that the operating cost of the commercial tenant is reduced, and promotion effects wanted by the commercial tenant are more effectively achieved.

Description

technical field [0001] The invention belongs to the field of electronic information, and in particular relates to a user coupon behavior prediction method and a model construction method in an e-commerce environment. Background technique [0002] Issuing coupons is a very common promotional activity. Merchants attract customers through promotional activities. Most of the existing e-commerce prediction technologies are based on the user's existing purchase behavior to predict whether the user will buy a product such as figure 1 As shown, however, some users may not use the coupons they receive, so randomly distributing coupons may hardly achieve the desired promotional effect. And the technology to predict coupon usage has yet to be applied. [0003] The existing user purchase behavior prediction technology cannot solve this problem, so we propose a technology to predict the use of user coupons. The e-commerce platform can build a model in this way to predict the probabili...

AI Technical Summary

Problems solved by technology

Most of the existing e-commerce prediction technologies are based on the user's existing purchase behavior to predict whether the user will buy a product such as figure 1 As shown, however, some users may not use the coupons they receive, so random distribution of coupons may be difficult to achieve the desired promotional effect

And technology to predict coupon usage has yet to be applied

[0003] The existing user purchase behavior prediction technology cannot solve this problem, so we propose a technology to predict the use of user coupons. The e-commerce platform can build a model in this way to predict the probability of users using coupons. According to the probability Decide whether to issue coupons to users

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