Research On New Media Advertising Strategy Based On Uesr Portrait

With the advent of the era of digital media,people's choice of information is more personalized,and the choice of new media is more active.With its efficient information dissemination speed and convenient communication characteristics,new media quickly attracted people's attention and use.Individuals can express their feelings and opinions through new media,companies can spread brand value,and strengthen consumers' identity and connection through the interaction of new media platform.The user's eyes are there,and the advertisement is there.How to locate the target audience according to the characteristics of the products and improve the promotion conversion rate are the key concerns of new media advertisers.In the era of new media,user portraits should not only be aimed at individuals,but also at shaping people instead of persuading people.The user portrait based on big data includes quantitative and qualitative methods.It is to model user data of various platforms,that is,to label user information.The setting of these labels is the description of the user's behavior.By analyzing the user's different information data,including the user's age,living habits,hobbies,consumption habits,living conditions and other life attributes and social attributes,a user's information panorama is established on the basis of many such information.This paper analyzes these information and the corresponding big data,establishes models,and interprets and analyzes user behavior from multiple perspectives,that is,the demand,attitude and purchase behavior of products.This can not only associate users with various kinds of information,but also provide scientific and comprehensive support for the precise placement and dissemination of advertisements.The research of this paper is based on user portrait,which is based on user data.With the help of its characteristics of visualization,tagging and informatization,it sums up the motivational behaviors of the target consumers,which is a powerful premise for accurate delivery.User portrait strategy selection and feature dimension selection modeling are of great significance to new media advertising.The research purpose of this paper is to help s company to solve the current business difficulties.Based on the research of user portrait,through the acquisition of big data,this paper analyzes the results of new media advertising,and then effectively improves the return on investment of the enterprise.This paper adopts the method of literature research and quantitative and qualitative combination.First,it understands the concept and characteristics of new media and user portrait.Then,it builds a multi-dimensional user portrait model of delivery channel by studying the theory of audience acceptance behavior and the research status of new media advertising development at home and abroad,combining with the existing business of S company,and collects massive interactive data in the community,clean and store,train and cluster interactive data with natural semantic analysis,assign values to indicators of the model by means of machine and human.Finally,verify and summarize the results of advertising.Through the above analysis and verification,this paper believes that in the era of new media marketing,KOL's community is the research object for user portrait,and appropriate dimensions and indicators are selected Standard can improve ROI,namely KOL community conversion rate,and then improve the accuracy of new media advertising.