The importance of key celebrity characteristics for customer segmentation by age and gender: Does beauty matter in professional football?

Abstract

This paper examines through the lens of sport whether male and female customers as well as differently aged customers focus on different celebrity characteristics and whether they are influenced by celebrities' facial attractiveness. Drawing on psychological and sociological theories like attachment theory, social role theory of gender, or social norm theory as well as on the academic literature on celebrity endorsement in general, we develop several hypotheses regarding how a fan's age and gender affect the importance of key characteristics of football starsnamely experience, personality, exemplary behavior, and skills. Using a proprietary dataset that combines archival data concerning professional football players and clubs with survey data of more than 2100 football fans, we find evidence that female fans attach more importance to a player's personality and behavior while male fans seem to focus on experience and skills. We further find that when fans get older, the importance of a player's behavior and experience increases. Moreover, our results show that the facial attractiveness of players clearly influences fan perceptions. Our results contribute to existing research on customer segmentation by providing a & Daniel Hoegele more differentiated picture of the effects of key celebrity characteristics on different customers.

Can CEOs’ Facial Attractiveness Influence Philanthropic Behavior? Evidence from India

“…To further confirm the validity of CEO attractiveness measures, following extant literature (Halford & Hsu, 2014; Hoegele et al, 2016), we conducted a primary survey in India. We selected Indian respondents and, due to skin color, the opinion in developed countries could have been biased.…”

“…Anaface computes the facial beauty scores of a person based on facial geometry and does not consider eye, skin complexion, or color of the skin (Halford & Hsu, 2014). This application provides beauty scores on a scale of 1 to 10 with scores closer to 10, indicating higher facial attractiveness or beauty (Halford & Hsu, 2014; Hoegele et al, 2016). The algorithm of Anaface is proprietary, and it calculates the geometry of faces using neoclassical beauty, research papers, and scientific studies (Halford & Hsu, 2014).…”

“…To ensure reliability and validity (Halford & Hsu, 2014; Hoegele et al, 2016) of the CEO facial attractiveness measure, we followed a two-step procedure. First, two postgraduate students from a UK University, over a one-month period, independently uploaded each of the CEO images over anaface.com six times, and using the 17 markers obtained six facial beauty scores for all the 893*2= 1786 images.…”

“Beauty” premium for social scientists but “unattractiveness” premium for natural scientists in the public speaking market

“…Our searches successfully located a frontal portrait for 726 of the 734 speakers in the sample. We use Anaface.com, the web-based software for photo analysis that evaluates factors such as horizontal symmetry, nose to ear length ratio, nose width to face width ratio, mouth width to nose width ratio, face width to face height ratio, and eye width to innerocular distance ratio (Halford and Hsu, 2014;Hoegele et al, 2016;Sung et al, 2016;Babin et al, 2019;Baugh et al, 2019), to proxy for facial attractiveness. The software assigns each photo a beauty score from 1 to 10 based on facial geometry differentiated by gender.…”

Estado actual de la investigación sobre Segmentación de clientes y Flexibilidad de la cadena de suministro. El desafío futuro de la Microsegmentación

“…Mucho se ha investigado con respecto a la estrategia de Segmentación de Clientes (SC) y su aplicación, desde que Smith (1956) afirmó que el mercado es heterogéneo, lo que hace necesaria una actitud diferente por parte de las empresas para atender a cada grupo característico de clientes (Wind y Cardozo, 1974;Webster, 1994;Hutt y Speh, 2004;Hoegele et al, 2016).…”