Open AccessConversion’s forecast model for ADs in social networks
Author(s) -
Aleks S. Krasnov,
Sergey Krasnov,
R. V. Griffith,
Mihail Draganov,
Красимир Костенаров
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/940/1/012074
Subject(s) - psychographic , reliability (semiconductor) , order (exchange) , computer science , behavioral modeling , resource (disambiguation) , segmentation , consumer behaviour , econometrics , marketing , artificial intelligence , business , economics , computer network , power (physics) , physics , finance , quantum mechanics
In this paper, the authors evaluate the characteristics of customers. Established interconnected segmentation and consumer targeting. Formulated groups of consumer characteristics, as well as the characteristics themselves, applicable in a digital environment. Based on data analysis, the effectiveness of targeting by behavioral and psychographic characteristics was determined. The authors proposed a model to predict the conversion rate of advertisements through the use of socio-demographic, psychographic, behavioral and geographical characteristics. The reliability of the models was checked for compliance and its testing. The results obtained during testing turned out to be comparable with the predicted ones, which allowed us to conclude that it is possible to predict conversion rates in order to increase the efficiency of resource use, including when promoting goods and services on social networks.