Player consumption potential-based game prop pushing method and device

Abstract

The invention provides a player consumption potential-based game prop pushing method and device. The method comprises the following steps that: the consumption data of players are extracted from a database; the players are grouped, the consumption ability of each player in each group is predicted; props matched with the consumption ability of the players are selected, and a prop candidate list isgenerated; and candidate props are sorted and pushed to the corresponding players. According to the player consumption potential-based game prop pushing method and device of the invention, the pushinglist of the game props is sorted and outputted on the basis of a plurality of factors; the game props that are matched with the consumption expectation of the players are pushed to the players; the effective conversion rate of conversion from pushing to transaction is significantly improved; and industrial problems are solved.

Description

technical field [0001] The present invention relates to the field of information analysis, in particular to a method and device for pushing game props based on player consumption potential. Background technique [0002] In the operation of the online game mall, item push is the key point. There are players of different consumption levels in the game, and these players have different spending power and willingness to spend. When high-priced game items are pushed to players with low consumption potential, the players may feel that their consumption expectations are exceeded, resulting in failure to reach a transaction, the item push is invalid, and the business goals of the enterprise cannot be achieved. Players of different consumption classes have different spending power, and the business goal of item recommendation is to customize and recommend items of different price levels to players of different classes. According to the known literature, the industry has proposed ma...

AI Technical Summary

Problems solved by technology

Due to the different value of different items, when related or similar items are pushed to the user, but the price of the item exceeds the user's consumption capacity, it is difficult for the user to reach a transaction

This leads to a low effective conversion rate of recommendations, and it is difficult to achieve the business goal of maximizing the business benefits of the enterprise

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