Background: 

The prevalence of augmented reality (AR) is on an upward trend and is expected to accelerate in growth in the upcoming years. This poses a strategic opportunity for marketers as it paves the way for incorporating AR into their marketing activities. However, a challenge for companies who wish to incorporate AR into their marketing is the lack of internal capabilities concerning AR among marketers. Research has shown that AR marketing (ARM) has several advantages such as it improves customer engagement, customer-brand relationships, customer’s purchasing intentions, and customer’s attitudes towards brands. The key factor that drives these positive outcomes of ARM is the enhanced hedonic and utilitarian benefits it provides. However, there is currently a lack of understanding regarding what utilitarian and hedonic benefits customers expect to derive from ARM. understanding these expectations is essential as their fulfillment is a determinant of how meaningful and satisfactory the ARM experiences are perceived. 

Purpose: 

The purpose of this study is to bridge the current research gap by exploring customers' expectations regarding the hedonic and utilitarian benefits of ARM and how well they perceive that these expectations are met and subsequently what this means for the overall customer experience. 

Method: 

The study is based on an exploratory qualitative research design with an abductive approach. The data were collected using semi-structured interviews with fifteen participants that were purposely sampled. This allowed us to get rich data and develop an in-depth understanding of customers’ expectations and experiences with ARM. The interviews were conducted in two rounds, the first round was to explore their expectations of ARM shopping applications while the second round was to explore their experiences. Between the two interviews, the participants used two ARM applications (IKEA Place & Wanna Kicks) and were asked to use them in their domestic setting. We analyzed the interview data using thematic analysis. By doing so we took a systematic approach to identify and compare similarities and dissimilarities in our data, leading to emerging themes. The results were compared to existing literature to identify new findings and develop conclusions. 

Findings: 

Our findings contribute to a deeper theoretical understanding of ARM by identifying and categorizing customers' hedonic and utilitarian expectations and shedding light on the specific AR attributes that contribute to these expectations. Furthermore, we also present novel insights into how ARM can provide meaningful customers experiences. Our findings have several theoretical and managerial implications offering valuable insights for the continuation of theoretical development and strategic marketing practices.