Piazza, Alexander; Zagel, Christian; Haeske, Julia; Bodendorf, Freimut (2017)
In: Freund, L., Cellary, W. (eds) Advances in The Human Side of Service Engineering. AHFE 2017. Advances in Intelligent Systems and Computing, vol 601. Springer, Cham 601.
DOI: 10.1007/978-3-319-60486-2_12
The performance of companies depends on the ability to leverage data to create insights and to target consumers with personalized messages Like marketing content or product offerings. One key element for personalized targeting are expressive user profiles, which are the basis for predictive models to estimate individual consumers’ preferences. Traditionally user profiles are mainly based on demographic attributes like age, gender, or occupation. Due to changes in society, consumers’ behaviors are less stable, and therefore these demographic factors are less effective. Alternatively, the consumers’ lifestyle has a significant impact on their purchase and consumption behavior. This paper investigates the relationship between Facebook Likes and the lifestyle of individuals based on the activity, interests, and opinion (AIO) model. Therefore, 14482 user-Like combinations from 214 participants were collected together with lifestyle information and a correlation analysis is conducted. The results indicate weak monotonic correlations between the AIO and the Like information.
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