The Evolution of Marketing in the Context of Voice Commerce: A Managerial Perspective

The world is confronted with the rise of voice assistants, increasingly used for shopping activities. This paper examines managers’ perceptions of the evolution of voice assistants and their potential effects on the marketing practice. Shopping-related voice assistants are likely to radically change the way consumers search and purchase products with severe impact on brands. However, the behavior of these AI-enabled machines represents a “black box” for brand owners. The study of the managers’ interpretation of a voice-enabled marketplace is critical as it may influence future marketing choices. The authors use an inductive theory construction process to study the phenomenon of voice commerce through the eyes of AI experts and voice-aware managers. A mixed-method approach paced three distinct data collection phases. First, systematic machine behavior observations (Amazon Alexa) unfolded the unique characteristics of voice shopping. Second, in-depth interviews with 30 executives drew the current brand owner’s challenges and opportunities in the context of voice commerce. Third, an expert survey with international managers (N = 62) revealed the expected impact of voice assistants on the shopping process. Findings show that managers consider voice assistants a disruptive technology assuming a central relational role in the consumer market. However, they often divergence in opinions across industry, function, and seniority level. Besides, managers’ familiarity with voice commerce is correlated to a higher optimism towards voice technologies (opportunity for brands) but also a greater sense of urgency (short-term focus) with implications for marketing strategy. This article offers support to brand owners explaining how voice assistants work and examining their effects on consumption. The authors discuss empirical results while providing managerial guidelines to create resilient and sustainable brands in the era of voice commerce.

[1]  John T. Gourville,et al.  Consumer Control and Empowerment: A Primer , 2002 .

[2]  Chris Janiszewski,et al.  The Influence of Avatars on Online Consumer Shopping Behavior , 2006 .

[3]  D. Ford,et al.  Networking under uncertainty: Concepts and research agenda , 2010 .

[4]  Pattie Maes,et al.  Agent-mediated Electronic Commerce : A Survey , 1998 .

[5]  R. Thaler,et al.  Nudge: Improving Decisions About Health, Wealth, and Happiness , 2008 .

[6]  Cass R. Sunstein,et al.  Chapter 25. Choice Architecture , 2013 .

[7]  Michael D. Giebelhausen,et al.  Touch versus Tech: When Technology Functions as a Barrier or a Benefit to Service Encounters , 2014 .

[8]  Andreas M. Kaplan,et al.  Siri, Siri, in my hand: Who’s the fairest in the land? On the interpretations, illustrations, and implications of artificial intelligence , 2019, Business Horizons.

[9]  Bernd H. Schmitt From Atoms to Bits and Back: A Research Curation on Digital Technology and Agenda for Future Research , 2019, Journal of Consumer Research.

[10]  Lorenzo Cantoni,et al.  Digital Fashion Competences: Market Practices and Needs , 2017, Business Models and ICT Technologies for the Fashion Supply Chain.

[11]  Emi Moriuchi Okay, Google!: An empirical study on voice assistants on consumer engagement and loyalty , 2019, Psychology & Marketing.

[12]  Frank Bentley,et al.  Understanding the Long-Term Use of Smart Speaker Assistants , 2018, Proc. ACM Interact. Mob. Wearable Ubiquitous Technol..

[13]  Efraim Turban,et al.  Effect of personalization on the perceived usefulness of online customer services: a dual-core theory , 2009, ICEC.

[14]  Jim Sterne,et al.  Artificial Intelligence for Marketing: Practical Applications , 2017 .

[15]  Thomas H. Davenport,et al.  The AI Advantage: How to Put the Artificial Intelligence Revolution to Work , 2018 .

[16]  Anyuan Shen,et al.  Recommendations as personalized marketing: insights from customer experiences , 2014 .

[17]  Elena Karahanna,et al.  Online Recommendation Systems in a B2C E-Commerce Context: A Review and Future Directions , 2015, J. Assoc. Inf. Syst..

[18]  Johanna Gollnhofer,et al.  Sensing the Vocal Age: Managing Voice Touchpoints on Alexa , 2018 .

[19]  Anol Bhattacherjee,et al.  Individual Trust in Online Firms: Scale Development and Initial Test , 2002, J. Manag. Inf. Syst..

[20]  Izak Benbasat,et al.  E-Commerce Product Recommendation Agents: Use, Characteristics, and Impact , 2007, MIS Q..

[21]  Izak Benbasat,et al.  Trust In and Adoption of Online Recommendation Agents , 2005, J. Assoc. Inf. Syst..

[22]  H. Håkansson,et al.  Developing relationships in business networks , 1995 .

[23]  John G. Lynch,et al.  Smart Agents: When Lower Search Costs for Quality Information Increase Price Sensitivity , 2003 .

[24]  Matthew B Hoy Alexa, Siri, Cortana, and More: An Introduction to Voice Assistants , 2018, Medical reference services quarterly.

[25]  Lorenzo Cantoni,et al.  Editorial: Fashion communication: Between tradition and digital transformation , 2019, Studies in Communication Sciences.

[26]  Ashutosh Dixit,et al.  Research framework, strategies, and applications of intelligent agent technologies (IATs) in marketing , 2015, Journal of the Academy of Marketing Science.

[27]  J. Zaichkowsky,et al.  How Bots Have Taken over Brand Choice Decisions , 2018, Proceedings of the Future Technologies Conference (FTC) 2018.

[28]  Jodi Forlizzi,et al.  "Hey Alexa, What's Up?": A Mixed-Methods Studies of In-Home Conversational Agent Usage , 2018, Conference on Designing Interactive Systems.

[29]  Heetae Yang,et al.  Understanding adoption of intelligent personal assistants: A parasocial relationship perspective , 2018, Ind. Manag. Data Syst..

[30]  One-Ki Lee,et al.  AI-Based Voice Assistant Systems: Evaluating from the Interaction and Trust Perspectives , 2017, AMCIS.

[31]  Paul Voosen,et al.  The AI detectives. , 2017, Science.

[32]  Gerald Häubl,et al.  "Double Agents": Assessing the Role of Electronic Product Recommendation Systems , 2005 .

[33]  A. Arvidsson,et al.  Echo Chamber or Public Sphere? Predicting Political Orientation and Measuring Political Homophily in Twitter Using Big Data , 2014 .

[34]  Charles J. Kacmar,et al.  Developing and Validating Trust Measures for e-Commerce: An Integrative Typology , 2002, Inf. Syst. Res..

[35]  Kurt P. Munz,et al.  Not-so Easy Listening: Roots and Repercussions of Auditory Choice Difficulty in Voice Commerce , 2019, SSRN Electronic Journal.

[36]  Russell W. Belk,et al.  Servant, friend or master? The relationships users build with voice-controlled smart devices , 2019, Journal of Marketing Management.

[37]  Roland T. Rust,et al.  Artificial Intelligence in Service , 2018 .

[38]  Dhruv Grewal,et al.  How artificial intelligence will change the future of marketing , 2019, Journal of the Academy of Marketing Science.

[39]  Izak Benbasat,et al.  Recommendation Agents for Electronic Commerce: Effects of Explanation Facilities on Trusting Beliefs , 2007, J. Manag. Inf. Syst..

[40]  Izak Benbasat,et al.  The Effects of Personalizaion and Familiarity on Trust and Adoption of Recommendation Agents , 2006, MIS Q..

[42]  Aradhna Krishna,et al.  The Skeptical Shopper: A Metacognitive Account for the Effects of Default Options on Choice , 2004 .

[43]  W. Goldstein,et al.  Consumer Choice and Autonomy in the Age of Artificial Intelligence and Big Data , 2017, Customer Needs and Solutions.

[44]  Ruhi Sarikaya An overview of the system architecture and key components The Technology Behind Personal Digital Assistants , 2022 .

[45]  Donald A. Schön,et al.  Theory in Practice: Increasing Professional Effectiveness , 1974 .

[46]  Elena Karahanna,et al.  The future of technology and marketing: a multidisciplinary perspective , 2019, Journal of the Academy of Marketing Science.

[47]  Shruti Sannon,et al.  "Alexa is my new BFF": Social Roles, User Satisfaction, and Personification of the Amazon Echo , 2017, CHI Extended Abstracts.

[48]  Eli Pariser,et al.  The Filter Bubble: How the New Personalized Web Is Changing What We Read and How We Think , 2012 .

[49]  Venkatesh Shankar,et al.  How Artificial Intelligence (AI) is Reshaping Retailing , 2018, Journal of Retailing.

[50]  Peter Naudé,et al.  Sense-making and management in business networks — some observations, considerations, and a research agenda , 2010 .

[51]  Daniel G. Goldstein,et al.  Beyond nudges: Tools of a choice architecture , 2012 .

[52]  D. Hoffman,et al.  Consumer and Object Experience in the Internet of Things: An Assemblage Theory Approach , 2018 .

[53]  Arun Rai,et al.  Explainable AI: from black box to glass box , 2019, Journal of the Academy of Marketing Science.

[54]  H. Håkansson,et al.  No business is an island: The network concept of business strategy , 1989 .

[55]  John G. Lynch,et al.  Creating Boundary-Breaking, Marketing-Relevant Consumer Research , 2019, Journal of Marketing.

[56]  Xueming Luo,et al.  Frontiers: Machines vs. Humans: The Impact of Artificial Intelligence Chatbot Disclosure on Customer Purchases , 2019, Mark. Sci..

[57]  I. Ajzen,et al.  Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research , 1977 .

[58]  Todd J. Arnold,et al.  Store Manager–Store Performance Relationship: A Research Note , 2019, Journal of Retailing.

[59]  Valerie J. Trifts,et al.  Consumer Decision Making in Online Shopping Environments: The Effects of Interactive Decision Aids , 2000 .

[60]  Erik Jan Hultink,et al.  How Today’s Consumers Perceive Tomorrow’s Smart Products , 2007 .

[61]  Bernard J. Jaworski,et al.  A Theories-in-Use Approach to Building Marketing Theory , 2019, Journal of Marketing.

[62]  Andreas Janson,et al.  The What and How of Smart Personal Assistants: Principles and Application Domains for IS Research , 2018 .