Research On The Influence Of Online Store's New Product Preannouncement Strategy On Consumers' Purchase Intention

In recent years,with the rapid development of the Internet,online shopping platforms have entered a period of vigorous development,Many enterprises have flocked to online shopping platforms,and the original brand stores are developing,it results in intensified competition among similar stores.At the same time,the national life is constantly enriched,more and more individual products are pursued.Therefore,online stores continue to launch new products,in order to seize market share.As a marketing method,new product preannouncement helps stores to carry out new product,however,some new product have a positive impact on consumers' decision on making,while some new product preannouncement have little effect.If it fails,it will lose the advantageous position of industry competition,even affect investors' confidence,and affect the long-term development of stores.Therefore,it is an urgent problem to analyze the relationship between the online store's new product preannouncement strategy and consumers' purchase intention,so as to help the store to carry out effective new product preannouncement.The research idea of this paper: in order to analyze the process and the factors of consumers' purchase decision-making,on the one hand,this paper analyzes the imple-mentation path of consumers' online shopping according to the S-O-R theory and the perception risk theory,and constructs the key index system of new product preannouncement strategy by using the grey correlation theory.In order to quantitatively analyze the relationship between online shop new product preannouncement strategy and consumers' purchase intention,on the other hand,this paper analyzes the advantages and disadvantages of AHP and BP neural network algorithm in analyzing the relationship between variables,and constructs the AHP-BP neural network model.In order to analyze the influence relationship between research variables,the specific research contents are as follows:First of all,based on the theoretical research,this paper analyzes the online shopping behavior of consumers,through combing the previous literature of the new product preannouncement,and the suggestions of relevant experts,we initially construct the new product notice index system,and then cuts back the preliminary index system byusing the gray correlation theory,and finally obtains the key index system of the new product preannouncement strategy of online stores,in order to facilitate a more comprehensive analysis of the factors of new productpreannouncement strategy.Secondly,this paper combs the literature to analyze the implementation process and advantages and disadvantages of AHP and BP neural network in studying the influence relationship between variables,this paper proposes a method of using AHP to get the index weight to improve the initial value of the connection weight between BP neural network neurons,we construct the AHP-BP neural network model.Finally,this paper builds a judgment matrix for the new product preannouncement index by consulting relevant experts and using satty1-9 scoring method,and uses AHP to calculate the weight of each index.Then collect the related data of the new product preannouncement of the original clothing brand online shop,train the BP neural network model,and constantly modify the connection weight between the indicators,finally gets the impact relationship between the indicators of the new product preannouncement strategy and the purchase intention of consumers.This study not only constructs the key index system of new product preannoun-cement strategy of online stores,but also constructs the AHP-BP neural network model to provide ideas for analyzing the relationship between new product preannouncement and consumers' purchase intention.According to the analysis results,it provides suggestion for online stores to carry out new product marketing from five aspects,including release strategy,content strategy,online comment strategy communication strategy,and stakeholder strategy.