Marketing strategy effect evaluation method based on a retail AI system

Abstract

The invention discloses a marketing strategy effect evaluation method based on a retail AI system. The marketing strategy effect evaluation method comprises the following steps: A) loading related data conforming to a set format through a group of SQL; wherein the related data are behavior information and sales strategy release of historical customers; B) preprocessing the related data to obtain processed data; C) substituting the processed data into a multivariate linear regression algorithm for AI learning and training, solving a residual equation set of the processed data to obtain an optimal solution coefficient, and obtaining a strategy effect evaluation model according to the optimal solution coefficient; and D) inputting a simulation strategy or parameter by the user, substituting the simulation strategy or parameter into the strategy effect evaluation model, giving an estimated value and an estimated error range of a corresponding index by the retail AI system, and analyzing the degree of influence of each dimension on the index. According to the invention, a data-supported marketing strategy effect evaluation function is provided for the retail industry, and requirements on hardware and operation and maintenance personnel are low.

Description

technical field [0001] The present invention relates to the retail field, in particular to a method for evaluating the effectiveness of a retail AI system-based marketing strategy. Background technique [0002] At present, the retail system has realized the integration of online and offline. With the mode of online and offline + intelligent logistics, the traditional offline channels are deployed online to form a new retail system. Through order management, customer data management and supply chain management, retailing is digitalized, and the whole network and all channels are integrated. Fully solve sales channel problems, customer communication problems, logistics and warehousing problems, and can effectively manage marketing management problems between self-operated stores and channel vendors, unsalable goods, and chaotic prices. The retail system can share resources, increase brand exposure with the help of social media tools, and increase the consumption of target cus...

AI Technical Summary

Problems solved by technology

However, traditional retail systems are limited to massive amounts of data in the cloud, cannot conduct effective real-time analysis of daily operational data, and have high requirements for hardware and operation and maintenance personnel

Traditional retail systems cannot provide efficient marketing strategy effectiveness evaluation functions

Images