Research On The Online Precision Marketing Of Company A Based On The User Big Data

With the development of the Internet,people can do a lot of things through internet,such as daily shopping,entertainment,access to information,communication,sharing,etc.At the same time,enterprises collect and statistic all data which is generated by people's behavior on internet.After processing and analyzing the data,enterprises can forecast users' needs in the future with insights based on users' historical behavior effectively.According to these data and forecasts,enterprises can make accurate advertising and marketing activities to users and avoid the waste of advertising,which we call Big data precision marketing.It improves the transformation effectiveness by sending the right information to the right target group with the right way at the right time.The basis of big data precision marketing requires data on all dimensions of users.Through processing these data effectively,such as filtering,integrating,excavating and modeling,the results will apply to business marketing activities.This thesis focuses on the case of Company A.In the research,we integrate users' data storage in different systems through connecting internal data inland,and then use data modeling to analyze and excavate data effectively.Finally we identigy the users labeling.This research solves the current problems that happened in marketing activities of company A,which will improve the precision of marketing of this company.We also hope that the result of this research can be used by other companies in their big data marketing activities.The main innovation points outlined in this thesis include the following: First,this research uses data model process method and integrate the accuracy users' data into the model to improve the precision marketing of the company,which highlights the value of model in the process of marketing decision-making.Second,this research distinguishes the data between anonymous and real-name users clearly,which can identify all browsing behavior that is created by users effectively.Thus,the model can collect more comprehensive data on users' decision behavior,which can reflect the users' characteristic richer and more precise.And this method makes the forecast and the oversight of data marketing based on the browsing behaviors more accurate.Third,on the user identification,this research establishes the users' portrait through analyzing and excavating user data,which can identify users in all aspects effectively.Thus,it will give companies more precision marketing and better effectiveness.