As the market of voice-activated assistants (VAAs) is rapidly expanding, these voice-based interfaces, as easy and intuitive conversational agents, are penetrating people's everyday life. To add new insight into the current understanding of this phenomenon, this study aims to explore consumers’ experiences and perceptions with VAAs for apparel shopping along with the shopping journey. This qualitative study uses semistructured interviews with 21 US-based participants who have shopped using VAAs. The phronetic iterative method identified six main themes: perceived VAA suitability for apparel, loyalty-driven VAA shopping, VAA personal assistant experiences, ecosystem credibility experiences, control and autonomy in VAA shopping, and desire for multi-modal shopping. Further, perceived benefits and barriers relating to each theme are discussed. Our findings lay a foundation for the theorization of consumer behavior while providing implications on marketing and design of voice commerce for fashion businesses and VAA developers.
AnglinL. K.StuenkelK.LepistoL. R. (1994). The effect of stress on price sensitivity and comparison shopping. NA-Advances in Consumer Research, 21(1), 126–131.
2.
BawackR. E.WambaS. F.CarilloK. D. A. (2021). Exploring the role of personality, trust, and privacy in customer experience performance during voice shopping: Evidence from SEM and fuzzy set qualitative comparative analysis. International Journal of Information Management, 58, 102309. https://doi.org/10.1016/j.ijinfomgt.2021.102309
3.
CaoL. (2021). Artificial intelligence in retail: Applications and value creation logics. International Journal of Retail & Distribution Management, 49(7), 958–976. https://doi.org/10.1108/IJRDM-09-2020-0350
ChaudhuriA.HolbrookM. B. (2001). The chain of effects from brand trust and brand affect to brand performance: The role of brand loyalty. Journal of Marketing, 65(2), 81–93. https://doi.org/10.1509%2Fjmkg.65.2.81.18255
7.
DanaherP. J.WilsonI. W.DavisR. A. (2003). A comparison of online and offline consumer brand loyalty. Marketing Science, 22(4), 461–476. https://doi.org/10.1287/mksc.22.4.461.24907
8.
FarahM. F.RamadanZ. B. (2020). Viability of Amazon’s driven innovations targeting shoppers’ impulsiveness. Journal of Retailing and Consumer Services, 53, 101973. https://doi.org/10.1016/j.jretconser.2019.101973
GrewalD.GuhaA.SchweigerE.LudwigS.WetzelsM. (2022). How communications by AI-enabled voice assistants impact the customer journey. Journal of Service Management, 33(4/5), 705–720. https://doi.org/10.1108/JOSM-11-2021-0452
11.
HalbauerI.JacobS.KlarmannM. (2022). Brand presentation order in voice shopping: Understanding the effects of sequential product presentation. Journal of Retailing, 98(4), 759–778. https://doi.org/10.1016/j.jretai.2022.06.002
12.
HalbauerI.KlarmannM. (2022). How voice retailers can predict customer mood and how they can use that information. International Journal of Research in Marketing, 39(1), 77–95. https://doi.org/10.1016/j.ijresmar.2021.09.008
13.
HuffmanT. P.TracyS. J.BiselR. S. (2019). Beautiful particularity: Using phronetic, iterative, and heuristic approaches to a positively deviant case. Communication Research and Practice, 5(4), 327–341. https://doi.org/10.1080/22041451.2019.1676632
14.
HuhJ.WhangC.KimH.-Y. (2023). Building trust with voice assistants for apparel shopping: The effects of social role and user autonomy. Journal of Global Fashion Marketing, 14(1), 5–19. https://doi.org/10.1080/20932685.2022.2085603
15.
JainS.BasuS.DwivediY. K.KaurS. (2022). Interactive voice assistants – does brand credibility assuage privacy risks?Journal of Business Research, 139, 701–717. https://doi.org/10.1016/j.jbusres.2021.10.007
16.
KautishP.PurohitS.FilieriR.DwivediY. K. (2023). Examining the role of consumer motivations to use voice assistants for fashion shopping: The mediating role of awe experience and eWOM. Technological Forecasting & Social Change, 190, 122407. https://doi.org/10.1016/j.techfore.2023.122407
LingE. C.TussyadiahL.TuomiA.StienmetzJ.IoannouA. (2021). Factors influencing users’ adoption and use of conversational agents: A systematic review. Psychology & Marketing, 38(7), 1031–1051. https://doi.org/10.1002/mar.21491
20.
Lucia-PalaciosL.Pérez-LópezR. (2021). Effects of home voice assistants’ autonomy on intrusiveness and usefulness: Direct, indirect, and moderating effects of interactivity. Journal of Interactive Marketing, 56(1), 41–54. https://doi.org/10.1016/j.intmar.2021.03.005
21.
MilesM. B.HubermanA. M.SaldañaJ. (2013). Qualitative data analysis. Sage.
22.
Morgan-ThomasA.DessartL.VeloutsouC. (2020). Digital ecosystem and consumer engagement: A socio-technical perspective. Journal of Business Research, 121, 713–723. https://doi.org/10.1016/j.jbusres.2020.03.042
23.
MoriuchiE. (2019). Okay, Google!: An empirical study on voice assistants on consumer engagement and loyalty. Psychology & Marketing, 36, 489–501. https://doi.org/10.1002/mar.21192
24.
MukhopadhyayS.de ReuverM.BouwmanH. (2016). Effectiveness of control mechanisms in mobile platform ecosystem. Telematics and Informatics, 33(3), 848–859. https://doi.org/10.1016/j.tele.2015.12.008
ParkH.KimS. (2023). Do augmented and virtual reality technologies increase consumers’ purchase intentions? The role of cognitive elaboration and shopping goals. Clothing and Textiles Research Journal, 41(2). https://doi.org/10.1177%2F0887302X21994287
28.
PitardiV.MarriottH. R. (2020). Alexa, she’s not human but… unveiling the drivers of consumers’ trust in voice-based artificial intelligence. Psychology & Marketing, 38, 626–642. https://doi.org/10.1002/mar.21457
29.
PoushnehA. (2021). Humanizing voice assistant: The impact of voice assistant personality on consumers’ attitudes and behaviors. Journal of Retailing and Consumer Services, 58, 102283. https://doi.org/10.1016/j.jretconser.2020.102283
30.
RamadanZ. B. (2021). Alexafying” shoppers: The examination of Amazon's captive relationship strategy. Journal of Retailing and Consumer Services, 62, 02610. https://doi.org/10.1016/j.jretconser.2021.102610
31.
RheeC. E.ChoiJ. (2020). Effects of personalization and social role in voice shopping: An experimental study on product recommendation by a conversational voice agent. Computers in Human Behavior, 109, 106359. https://doi.org/10.1016/j.chb.2020.106359
32.
RomanoB.SandsS.PallantJ. I. (2022). Virtual shopping: Segmenting consumer attitudes towards augmented reality as a shopping tool. International Journal of Retail & Distribution Management, 50(10), 1221–1237. https://doi.org/10.1108/IJRDM-10-2021-0493
33.
SaldañaJ. (2016). The coding manual for qualitative researchers. Sage.
34.
TaoY.RenZ.LiuX.ChenY. (2025). Color, voice type and pitch: How multi-sensory cues of virtual shopping assistants influence young people’s purchase intention in VR shopping. Electronic Commerce Research. https://doi.org/10.1007/s10660-025-09965-3
35.
TracyS. J. (2010). Qualitative quality: Eight “big-tent” criteria for excellent qualitative research. Qualitative Inquiry, 16(10), 837–851. https://doi.org/10.1177%2F1077800410383121
WhangC.ImH. (2021). I Like Your Suggestion!” the role of humanlikeness and parasocial relationship on the website versus voice shopper's perception of recommendations. Psychology & Marketing, 38(4), 581–595. https://doi.org/10.1002/mar.21437
40.
ZhangJ. Z.ChangC. W.NeslinS. A. (2021). How physical stores enhance customer value: The importance of product inspection depth. Journal of Marketing, 86(2), 166–185. https://doi.org/10.1177%2F00222429211012106
