Auxiliary pricing method and device which are implemented through computer and based on data analysis

Abstract

The embodiment of the present invention provides a computer-implemented method for assisting price determination based on data analysis. The method includes: providing each expected price of the sales target to a preset price and sales model, wherein the price and sales model is based on the characteristics that affect sales. The information is established and trained by using the sales target historical influence sales feature information; the expected sales volume corresponding to each expected price is determined according to the output of the price sales model, and an expected price and its corresponding expected sales volume form an expected price sales volume pair; Determine the sales target price according to the expected price and sales volume matching and the actual sales volume demand. The expected sales volume corresponding to the expected price is determined by using the price and sales model trained based on the historical sales feature information of the sales target, which is conducive to formulating a more reasonable price for the sales target in a timely and low-cost manner. In addition, the embodiments of the present invention also provide a medium, an apparatus, and a computing device.

Description

technical field [0001] The embodiments of the present invention relate to the computer field, and more specifically, the embodiments of the present invention relate to a computer-implemented method, device, computing device, and medium for assisting price determination based on data analysis. Background technique [0002] This section is intended to provide a background or context for implementations of the invention that are recited in the claims. The descriptions herein are not admitted to be prior art by inclusion in this section. [0003] It is a very important issue for the seller to set the price for the sales object to meet the seller's sales expectation of the sales object. [0004] At present, sellers often set prices for their sales targets by manually setting prices or by using web crawler technology to follow the prices set by competitors for sales targets or quasi-sales targets. Contents of the invention [0005] However, manual pricing often has problems su...

AI Technical Summary

Problems solved by technology

[0005] However, manual pricing often has problems such as strong uncertainty and untimely price adjustment due to its excessive reliance on subjective factors such as human experience, which will not only lead to high labor costs for pricing, but may also exist There is a high risk that the artificial price cannot meet sales expectations; and with the improvement of anti-crawler technology, follow-up pricing based on web crawler technology often cannot achieve follow-up pricing in the true sense. There is a greater risk in using follow-up pricing to set prices for sales targets due to obvious anomalies

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