A wearable sales assistant: capturing dynamic nonverbal communication behaviors using sensor technology
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A wearable sales assistant: capturing dynamic nonverbal communication behaviors using sensor technology Sandra Pauser 1
& Udo
Wagner 1
# The Author(s) 2019
Abstract Sales research has focused on enhancing selling effectiveness and performance, which largely depends on the abilities and capabilities of the sales force. Interpersonal skills consisting of verbal and nonverbal communication have been identified as a main predictor of sales performance. However, sales researchers face the difficulty of measuring and tracking nonverbal behaviors, since these messages are perceived and processed mainly unconsciously. This field study applies a novel data-collection method in sales research to automatically track nonverbal communication behaviors (i.e., kinesics, paralanguage, and proxemics) of both, the salesperson and the customer, through wearable electronic devices, sociometric badges. The findings indicate positive effects of dynamic (versus restricted/static) nonverbal cues on a salesperson’s charismatic appearance, which, in turn, yields favorable customer responses and sales performance. Keywords Sociometric badges . Nonverbal behaviors . Dynamic nonverbal cues . Personal
selling . Charisma
1 Introduction For decades, sales research has focused on the enhancement of selling effectiveness and performance; selling effectiveness and performance, in turn, largely depend on the abilities and capabilities of the sales force. Correspondingly, the
* Sandra Pauser [email protected] Udo Wagner [email protected]
1
Faculty of Business, Economics and Statistics, University of Vienna, Oskar-Morgenstern-Platz 1, 1090 Vienna, Austria
Marketing Letters
identification of sales behaviors that drive performance has received significant attention in research (Leigh and Summers 2002). Among other factors, interpersonal skills, consisting of verbal and nonverbal communication, have been identified as a main predictor of sales performance (Rentz et al. 2002). Recent research findings confirm that a salesforce’s nonverbal communication influences both customers’ perceptions of the salespersons and the products/services at stake and sales performance (Leigh and Summers 2002). At the same time, however, there is a general consensus in the literature that such nonverbal cues are difficult to measure, as these messages are “encoded and decoded unconsciously” (Stewart, Hecker, and Graham 1987, p. 305), and thus, conventional marketing research methods are not very effective; state of the art sales researchers have mostly relied on observational data on nonverbal cues, which are subjective and can suffer from observation bias (Olguin-Olguin and Pentland 2008). This study presents a novel data-collection method to automatically detect nonverbal communication behaviors of the salesperson and the customer and thereby provides a noteworthy contribution to sales research. Following the call for a more objective measurement of nonverbal behaviors by Olguin-Olguin and Pentland (2008), this research utilizes sociometric badges
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