Тема: Personalization as Phenomenon in Online Retail Context: Consumer Characteristics Affecting Intention To Use Personalized Offers

Technological development creates new opportunities for retailers to enhance customer experience by providing better service through personalization. For example, development of Big Data, increasing computing power, rapid development of AI and neural networks allow online retailers to utilize highly personalized service for their customers by processing huge amounts of consumers’ personal data. From consumer side, there is a lot of statistics about what consumers think about personalized services by companies. According to the survey conducted by Accenture in November 2017 in North American and European countries (Accenture, 2018), more than 90% of consumers will more likely shop with brands who are able to provide relevant personal recommendations, and more than 80% of consumers are ready to disclose their personal data in exchange for personalized experience. In 2022, more than 60% of consumers worldwide who made an online purchase during the past 6 months indicated that a brand would lose them as loyal customers if this brand provided a non-personalized experience for them (Marketing Personalization Worldwide, 2022). According to the E-commerce Personalization Benchmark Report (2021) by Netcore Cloud company, more than 75% of consumers would like to have a more personalized customer experience, and more than 30% of consumers would have a more willingness to share their personal information with retailers if they had more awareness of how their data is used. Summing up, it is important for retailers to use personalization in their marketing activities to attract more customers.
Recent literature on marketing and consumer behavior indicates the importance of managing customer experience and customer engagement by companies (Lemon & Verhoef, 2016; Gogua & Smirnova, 2020; Grewal et al., 2017). Personalization and personalized recommendations in particular helps companies to provide a better customer experience, enhance engagement and brand loyalty (Basu, 2021). Considering the importance and relevance of the study of consumer perception of personalization activities in online retailing context, the focus of this paper falls into exploring consumer behavior in relation to personalized offers and recommendations in online stores.
This study investigates the behavioral intention of consumers to use personal offers and recommendations because intention is the main predictor of consumer behavior (Ajzen, 1991). Characteristics of consumers which are studied in this paper as determinants of behavioral intention to use personalization are divided into two groups: 1) online shopping related characteristics - shopping orientation and deal proneness (since this study examines personalization and consumer behavior towards it in online retail context); 2) psychological characteristics of consumers that are connected to the implementation of personalization marketing strategies by companies - privacy concerns and reactance. All these consumer characteristics are widely studied in contemporary marketing research; special interest of the author lies in expanding the existing knowledge on these consumer characteristics constructs as well as investigating the relationship between these consumer characteristics and consumers’ intention to use personalized recommendations. To the best of author’s knowledge, there are no papers among currently existing studies which examined the integrated framework of the influence of such consumer characteristics as shopping orientation, deal proneness, privacy concerns and consumer reactance on their usage intention of personalized offers and recommendations in online shopping context. To address this gap, the present study is conducted.
The purpose of the present study is to investigate how consumers’ online-shopping related characteristics (shopping orientation and deal proneness) and psychological characteristics (privacy concerns and reactance) influence consumers’ intention to use personalized offers and recommendations in online retailing context.
Objectives of the study are the following:
1. Develop a theoretical model of the influence of four characteristics of consumers (shopping orientation, deal proneness, privacy concerns and psychological reactance) on their intention to use personalized offers and recommendations in online stores.
2. Test the developed model by analyzing quantitative data collected through the survey.
3. Conduct 10 semi-structured interviews to gain detailed consumers’ insights about their intention to use personalized offers and recommendations within the framework of the developed theoretical model.
4. Analyze and compare the results of two methods, make conclusions, and determine suggestions for future research.
Research questions:
1. What are the relationships between consumers’ characteristics (online shopping related and psychological) and consumers’ intention to use personalized recommendations?
2. How are the various dimensions of the studied characteristics of consumers related to their intention to use personalized offers in online stores?
...
Купить

Online retailers constantly adapt to modern consumer trends and try to provide personalized services to their customers by utilizing developing technologies. Personalized recommendation algorithms allow online retailers to provide a better customer experience and enhance customer engagement. In this instance, it is important and necessary to study consumer characteristics and behavior in relation to personalization, as well as consumer perception of personalization to improve company’s current and future business opportunities.
This study aimed at investigation of how characteristics of consumers (shopping orientation, deal proneness, privacy concerns and reactance) influence consumers’ intention to use personalized offers and recommendations in online retailing context. Using sequential mixed methods research design allowed to get a comprehensive view on the relationships between all these consumers’ characteristics and personalized offers usage intention. The results showed that both dimensions of shopping orientation (hedonic and utilitarian) of consumers lead to increased intention to use personalized offers. Consumers see personal offers in online stores as help and support in finding the necessary goods or considering different alternatives and choosing the best option among them. Deal proneness of consumers also positively affect their intention to use and rely on personalized offers and recommendations. As it was hypothesized, deal prone consumers tend to respond to personalized price offers and promotions but only if these personal offers correctly match their current preferences.
Privacy concerns of consumers, in contrast, diminish their intention to use personalized offers. Consumers who have low level of concern about privacy of their personal data are ready to provide the required personal data to online stores in order to receive suitable and useful personalized offers. Moreover, if these consumers concern about more sensitive types of data (mobile phone number, passport data, and banking card information), they are less willing to provide such data but their intention to use personalized offers does not decrease since consumers understand that such types of data should not be used by online stores for providing personalized offers. Comparison and analysis of results of both quantitative and qualitative methods led to the conclusion that psychological reactance of consumers have no influence on their intention to use personalized offers since consumers do not perceive them as something that contradicts their freedom. They perceive personalized offers and recommendations just as support in the process of online shopping.
The present study also has practical value for online retailers. The results allow to make suggestions for online retailers in the implementation of personalization strategies with the use of personalized recommendation algorithms: personalized offers should clearly match current consumers’ preferences and contain personalized price promotions and discounts.
Купить