Resource allocation method and device, storage medium and computer equipment

Abstract

The invention discloses a resource allocation method and device, a storage medium and computer equipment, and the method comprises the steps: screening a comparison object corresponding to a target object from delivered objects according to the target content submitted by the target object and the actual content of the delivered objects; based on the historical order information corresponding to the comparison object, carrying out statistics of order actual payment data and order actual addition content corresponding to the comparison object; screening out virtual addition content corresponding to the actual addition content of the order from the target object to obtain simulated order information of the target object; and determining resource configuration information of the target objectaccording to the order actual payment data and simulated pricing data corresponding to the simulated order information. According to the invention, resource allocation is carried out on the target object based on the historical order data of the comparison object, so that the target object can provide preferential activities according with the consumption preference and the consumption ability ofthe user, and growth and retention of the target object are facilitated.

Description

technical field [0001] The present application relates to the technical field of the Internet, and in particular to a resource configuration method and device, storage medium, and computer equipment. Background technique [0002] Takeaway has penetrated into all aspects of people's lives now, and the largest traffic is catering takeaway. Many takeaway merchants will conduct full discount activities (a type of marketing activity, that is, the original price of the order reaches a certain level, and the original price can be deducted from the original price. A certain amount) means to attract users. [0003] At present, new food delivery merchants have entered the food delivery platform, and the first time to set up full discount activities is more dependent on human subjective experience, which has the following defects: 1. The activity recommendation is more based on the cost of the main category, and the recommended activity configuration has no correlation with the origina...

AI Technical Summary

Problems solved by technology

[0003] At present, new food delivery merchants have entered the food delivery platform, and the first time to set up full discount activities is more dependent on human subjective experience, which has the following defects: 1. The activity recommendation is more based on the cost of the main category, and the recommended activity configuration has no correlation with the original price of the merchant’s dishes; 2. The full discount activities configured by each merchant of the same category are basically the same, and the diversity effect is poor; 3. The full discount activities after configuration lack data support and lack of business guidance for merchants

To sum up, the existing full discount activity configuration method relies on manual settings, which takes a long time to configure, low efficiency, high cost, and poor effect

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