Loyalty programs and personal data sharing preferences in the Czech Republic

Analysis of Personal Data-Sharing Consent Factors, With Focus on Loyalty Programs in the Czech Republic

“…Even though most respondents have only an intuitive understanding of the subject, they are able to identify different types of potential mishandling of data: in most cases, individuals are highly sensitive to unsolicited telemarketing (phone calls and SMS) and unsought personalized marketing correspondence. Unsolicited printed correspondence is perceived much more negatively than its electronic counterpart (this is in line with our previous findings -see Tahal et al 2017). After being asked specifically about social media and related personal data protection issues, our respondents usually express data protection concerns related to posting information which becomes 'publicly' available (and a property of the social site operator).…”

“…Indeed, the structure and quality of collected customer data has a strategic importance for retailers, their decision-making accuracy and profitability. At the same time, consumers are worried about privacy and fear their personal data could be misused (Tahal et al 2017). This situation is reflected in numerous other scientific studies -for example, Limba and Šidlauskas (2018) provide an analysis of risks and recommendations aimed at improving the security of personal data of social network site users.…”

“…The research team (based at the University of Economics, Prague) is led by university employees and teachers who coordinate and supervise the work of students specializing on marketing research. This study is part of a long-term project of systematic surveys and analyses of consumer behavior (Tahal et al 2017). The surveys used to gather data for this paper may be summarized as follows: Stratified/ quota sampling was based on gender, age segmentation and location (domicile) of the respondents.…”

Socio-demographic and lifestyle determinants of loyalty program participation in the Czech Republic

“…Customers' personal data (e.g. Tahal et al, 2017) and their LPbased shopping records may serve for many purposes: from customized direct mailing (tailored gifts and discounts, follow-up offers), to complex quantitative analyses of customer behavior, product portfolio optimization tasks, etc.…”

“…This study is part of a long-term project of systematic surveys and analyses of consumer behavior (e.g. Tahal, 2016 andTahal et al, 2017). The quantitative analysis (logistic regression and related tests and methods) is adjusted to control for stratified/quota sampling.…”