Transfer of Autonomous Sensory Meridian Response (ASMR) to Relationship Marketing: Potential Effects on Perceived Customer Intimacy

Abstract

ASMR has attracted considerable attention in social media and advertising practices, but it lacks empirical investigation within marketing science. This study suggests applying ASMR in the design of interactions in relationships between organizations and customers in order to shorten spatial distance evoked by digitization. This experimental study comprises the first empirical investigation of ASMR in the context of relationship marketing with a focus on perceived customer intimacy. The findings demonstrate that the level of perceived customer intimacy depends on individuals’ extraversion and agreeableness, and ASMR may entail the ability to positively influence this intimacy, but is influenced by further variables.

Keywords:

• ASMR marketing
• autonomous sensory meridian response
• relationship marketing
• customer intimacy

Ethical approval

Ethical approval was not required. All participants were introduced to why the research had been conducted, informed that their anonymity was always assured and data was only stored for the purpose of the study making use of the data protection policy of the data collecting authors’ university. Further, the central aim of the research had been disclosed at the beginning of the study. Since participants only revealed their opinions on the subject and anonymity is assured, no harm or risk thereof is associated with their participation.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 In order to assess the lengthy fear of intimacy inventory, we conducted three additional procedures. First, we modeled EFAs (principal axis with GLS estimator, oblimin rotation if required) for one to three factors. Solutions for two and three factors yielded very low eigenvalues (2.15/2.20 & 1.30) compared to the first factor (11.67/11.71) with rather low loadings (highest: .42) of indicators on the second and/or third factors. Please note that not a single indicator loaded higher on the second factor than on the first factor. Second, we estimated a scree plot based on principal component analysis with no rotation for up to 10 factors. The result also indicated that a single factor is dominant. Third, we modeled CFAs with one and two factors (all items with loadings ≥ .39 loaded on the second factor) and compared the models. The two factor-model was not significantly different from the single factor-model (Chi-squared difference = 1.65, df = 1, p = .20).