Artificial intelligence (AI) enabled virtual assistants are rapidly evolving, offering promising opportunities to provide 24/7 frontline service and personalized shopping assistance. This article deliberates on the role of AI virtual assistants in personalizing e-commerce shopping experiences, factors influencing the usage of such assistants by customers, and recent developments.
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Importance of AI-enabled Virtual Assistants
AI-enabled virtual assistants/conversational intelligence/chatbots for shopping are primarily software programs that can make real conversations using natural language processing (NLP), supported by machine learning (ML), and participate in and execute important tasks like product search and recommendations, personalized shopping advice, and price comparisons and deals. These assistants leverage user data and real-time interactions and perform behavioral analysis to assist in product searches and provide product recommendations.
AI-powered conversational agents remain the most popular tools in the digitalization of conventional customer-company interactions. Advancements in AI have resulted in the extensive utilization of conversational agents for shopping. Customers leverage conversational agents like Siri, Alexa, and Google Assistant for shopping needs. They assist customers in browsing products, facilitating purchase transactions, and providing information on prices.
Conversational agents are categorized into text- and voice-based chatbots, based on their communication modes. Text-based chatbots are primarily incorporated into a company's social media, websites, and messenger platforms such as Facebook Messenger. Voice-based chatbots/digital voice assistants like Cortana and Siri are common in personal computers and mobile phones.
AI-enabled Virtual Assistants in E-commerce
In e-commerce shopping, AI virtual assistants have a positive impact on user engagement and satisfaction, leading to improved brand loyalty and customer relationships, and overall business performance in an expanding digital economy. In an e-commerce environment, AI voice assistants typically serve as virtual assistants. They interact with customers through natural language conversations and provide different personalized services.
AI efficiently analyzes a huge volume of data, like demographic, behavioral, and purchasing history data, to understand the needs and preferences of customers. This is the key to the personalization capabilities of AI virtual assistants.This data analysis enables AI voice Assistants to customize search results, product recommendations, and overall interaction to fit the personal profile of each customer.
Moreover, AI voice assistant-provided personality significantly increases customer satisfaction, positively influencing purchasing decisions. AI voice assistants also serve as efficient customer support representatives for customers visiting the e-commerce platform. The assistant effectively solves queries about services and products and addresses issues of customers to reduce friction and simplify the customer journey.
AI voice assistants also influence how customers search for products on e-commerce platforms. The assistant interprets the customer's requirements and presents the search results by understanding the type of query, making the product search more satisfying and efficient.
The product packaging is customized based on the customer's preferences, and selected products that suit the customer's interest are offered through AI voice assistant to deliver a unique experience to customers, which increases customer loyalty. The AI-based voice service enables customers to easily access the website, add products to their wish lists, and remove items from the cart.
Thus, the rising adoption of AI voice assistants in e-commerce reflects the increasing need for interactive and personalized shopping. Using AI Voice Assistant, e-commerce can create a positive experience to increase customer trust and satisfaction and reduce the transaction completion time.
However, ethical concerns like fairness, privacy, and transparency loom large for AI virtual assistants. Maintaining a balance between ethical standards and identity is important for the effective use of AI virtual assistants for shopping in e-commerce.
Factors Influencing AI Virtual Assistant Usage
AI-powered conversational agents can reshape sales and service landscapes by augmenting or replacing frontline employees. Thus, the factors influencing the usage of such AI-enabled virtual assistants by customers must be identified for a comprehensive understanding of customer attitude, motivation, and behavioral intention to use AI-powered conversational agents in shopping.
A study published in the Journal of Retailing and Consumer Services investigated the factors influencing the customers' usage and resistance of AI-driven conversational agents for shopping using the partial least squares-based structural equation modeling (PLS-SEM) and extended behavioral reasoning theory (BRT).
Researchers performed two empirical studies, designated as Study 1 and Study 2, in South Korea to evaluate the proposed framework. Study 1 examined text-based chatbots with a sample of 232 participants, while Study 2 focused on voice-based chatbots with a sample of 234 participants.
Initially, the study identified the customers' influential reasons for and against the use of AI-powered conversational agents for shopping, both for voice-based chatbots and text-based chatbots. Then, the study investigated the effects of the reasons for usage and against usage of AI-powered conversational agents on the attitude toward usage and usage intention/resistance intention to AI-powered conversational agents.
Results showed that perceived usefulness, perceived trendiness, and perceived ease of use are the influential reasons for using text-based chatbots, while ubiquity, interactivity, and convenience are the major reasons for using voice-based chatbots. The 'reasons for usage' were associated positively with attitudes toward usage and usage intentions for voice- and text-based chatbots, which validated the findings of earlier studies. Moreover, the work empirically validated the positive effect of reasons against usage on resistance intention and the adverse impact on attitude toward usage.
Intrusiveness barrier, functional risk barrier, and usage barrier were identified as the reasons against usage for both voice- and text-based chatbots. The results also demonstrated that the negative relationship between the attitude toward usage and reasons against usage was not significant for text-based chatbots/Study 1.
However, this relationship was supported in the voice-based chatbot context/Study 2. The impact of digitalization on every industry has driven customers to accept the latest technologies despite the reasons against usage. This was attributed as the possible reason for Study 1's unsupported results.
Eventually, the findings of both empirical studies displayed that inhibitors and motivators to technology readiness were positively related to 'reasons against usage' and 'reasons for usage,' respectively. Thus, this study theoretically contributed by offering a holistic understanding of customer behavioral intentions, attitudes, and motivation toward utilizing AI-powered conversational agents in shopping, and managerially provided crucial insights for AI-powered conversational agent developers and retail managers.
Recent Developments
Accessibility is increasingly becoming an important topic for e-commerce, specifically for people with vision problems. A study published in the journal Big Data and Cognitive Computing proposed the design of a voice assistant, designated as Zuri, to ensure that the user feels a level of personification in the interaction with the tool, using AI techniques to allow individuals with vision problems to shop and browse online more efficiently and quickly to improve their online experience.
This voice assistant formed an intelligent system that understands and responds to users' voice commands. The proposed design considered the visual limitations of users, like identifying images or difficulty in reading information on the screen.
Researchers considered multiple parameters, including assistive technology compatibility, intuitive voice commands, accessible conversation design, easy access to information, experience personalization, and respect for privacy, while designing the voice assistant for e-commerce that meets the requirements of people with vision problems.
AI was used as the primary tool of the designed assistant, which allowed NLP. This enables users to interact with a device using voice commands without typing text or touching the screen. Natural language models and convolutional neural networks were used for the design of the AI model.
The voice assistant provided detailed product ideas and descriptions in an easy-to-understand and clear voice. A series of additional features in the voice assistant also improved the shopping experience. For instance, the assistant provided product recommendations based on previous purchases of the user and information about special discounts and promotions. Thus, the proposed design successfully created an inclusive and accessible online shopping experience for visually impaired individuals.
Overall, AI virtual assistants in shopping are offering convenience and improving the satisfaction of customers. However, issues like privacy and fairness must be mitigated for ethical and effective use.
References and Further Reading
Jan, I. U., Ji, S., Kim, C. (2023). What (de) motivates customers to use AI-powered conversational agents for shopping? The extended behavioral reasoning perspective. Journal of Retailing and Consumer Services, 75, 103440. https://doi.org/10.1016/j.jretconser.2023.103440
Villegas-Ch, W., Amores-Falconi, R., Coronel-Silva, E. (2023) Design Proposal for a Virtual Shopping Assistant for People with Vision Problems Applying Artificial Intelligence Techniques. Big Data and Cognitive Computing, 7, 96. https://doi.org/10.3390/bdcc7020096
Lari, H. A., Vaishnava, K., Manu, K. S. (2022). Artifical Intelligence in E-commerce: Applications, Implications and Challenges. Asian Journal of Management, 13(3), 235-244. http://dx.doi.org/10.52711/2321-5763.2022.00041