Currently, the interaction of the consumer and the retail market on the basis of the digital technologies could be described from the point of view of open innovation concept. The article aims to prove the advantages of mixing two separate formats of the interaction between the seller and the consumer in online and offline. The scientific approach to the developing of the so-called phygital environment (physical plus digital) could be considered as a research gap. The definition of the phygital environment regards the innovational concept being used in marketing practice but has not been described in scientific publication yet. The article examines the peculiarities of interaction between consumers and sellers in the framework of their interaction in the phygital environment. The concept of pop-up stores is analyzed as a new format of advertising interaction with the consumer. The authors have proposed a model of an end-to-end analytics system for assessing the effectiveness of a pop-up store in the framework of the interaction of participants in the turnover in a phygital environment. The proposed model has been tested and the efficiency of opening a pop-up store has been evaluated with and without the proposed model. The main marketing indicators and potential effects from the implementation of the proposed system for the company’s activities, in general, in the field of marketing are evaluated. The authors have studied the prospects for both development and automation, as well as the formation of the system of personalized marketing for companies, which implements the concept of interaction with consumers within the framework of the phygital environment.
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.
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