Advertisement injecting effect evaluation and intelligent push decision method based on face identification and big data analysis

Abstract

The invention discloses an advertisement injecting effect evaluation and intelligent push decision method based on face identification and big data analysis. The advertisement injecting effect evaluation and intelligent push decision method comprises a face identification technology is employed to obtain face feature data of the audience group, and the data is introduced into an advertisement injecting effect evaluation module as parameters, and is used for quantifying the advertisement injecting effect; furthermore, historical data is stored in a database, a data analysis system can carry out further analysis, the analysis result can be provided for the advertiser as an injecting decision reference, and can also be provided for the advertising agency who can carry out reasonable bidding and charging on the advertising position. At the same time, an FAEM matching algorithm is employed to match the advertisement played at present with audience face feature data at present, and advertisement push is carried out in dependence on the matching result. According to the invention, accurate evaluation of the advertisement injecting effect can be given out scientifically and objectively, and advertisements can be injected selectively and intelligently in dependence on audiences of the advertisements.

Description

technical field [0001] The invention relates to the fields of face recognition and big data analysis technology and advertising psychology, in particular to an advertising delivery effect evaluation and intelligent push decision-making method suitable for advertising media such as electronic billboards. Background technique [0002] The types of advertisements in China can be divided into print advertisements, electronic advertisements, traffic advertisements, and outdoor advertisements according to the media, and the evaluation methods for the effectiveness of these advertisements can be summarized as observation, experiment, interview, projection, and questionnaire. These traditional evaluation methods almost all rely on manual investigation, which is an inefficient and inaccurate evaluation method. [0003] At the same time, the evaluation of advertising delivery effects can be divided into: pre-advertising testing, advertising testing, post-advertising testing, and track...

AI Technical Summary

Problems solved by technology

Some small businesses don’t even get real-time and objective evaluation of the effect of advertising. They can only estimate the effect based on the nature and quantity of the advertising space to be placed. During this period, high costs are incurred, and the conversion benefits are very little.

At the same time, the real profit brought by advertising is difficult to calculate

[0005] To sum up, with the diversification of advertising delivery forms, merchants and advertisers are eager to seek such a solution that can help them solve "difficulties in obtaining real-time evaluation information of advertising delivery effects" and "there is no reliable evaluation of advertising delivery effects". Data sources", "Historical delivery data is difficult to make scientific statistics, making it difficult to make correct decisions on advertising delivery", etc.

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