The Impact of Artificial Intelligence in Boosting E-Commerce Sales through Customer Engagement and Enhanced Experiences

Section 1: Introduction

Retail sales by e-commerce during the recent holiday season represented more than one-third of all sales for the first time in history, and current signs indicate this trend towards e-commerce alternatives will continue to accelerate in the future. Indeed, virtually any product or service that is available in a traditional retail setting can be found online, and in most cases far more options and cheaper prices as well. It is little wonder that retailers of all ilk have created an online presence in an effort to take advantage of this trend, but it is clear that consumer expectations for their e-commerce experience are maturing and expanding. One strategy that has already proven effective for this purpose is the addition of artificial intelligence to the online retail experience, and there are multiple benefits of this strategy for retailers (Chen et al., 2021). There remains a gap in the existing body of knowledge, however, concerning consumers attitude and engagement with emerging AI-based technologies when they are used in retail e-commerce settings (Moriuchi et al., 2021). To help fill this gap, the purpose of this paper is to identify the impact of AI in boosting e-commerce sales through customer engagement and enhanced experiences as the context for a proposed study. To this end, section two of the paper provides an overview of recent and current trends with respect to the addition of AI to e-commerce, and section three provides a review of the relevant literature concerning these issues. Section four describes the proposed studys methodology, section five discusses the data analysis strategies that will be used, and section six presents the proposed studys timings and project management approach. Finally, a brief description of the research instruments that will be used is provided in section seven, following by the presentation and structure of the final results.

Section 2: Unpack the novelty

Today, e-commerce is becoming a dominant alternative to traditional retailers, and growing numbers of companies of all sizes and types are searching for viable strategies to take advantage of this trend by transitioning the marketing of their existing products and services to an online environment. Many enterprises, however, most especially small businesses, quickly learn that there is far more to effective e-commerce than just listing products and services on a Web site and hoping for the best. Moreover, truly effective e-commerce strategies exploit the automation that artificial intelligence offers, but there remains a dearth of timely and relevant research in this area that can help aspiring companies become successful at e-commerce.

The phrase, We have the technology used in 1974s Six Million Dollar Man was highly prescient in its relevance for e-commerce marketing today. In fact, the potential of AI for boosting e-commerce sales through improved customer engagement and experience has already been recently demonstrated by the wildly popular ChatGPT which provided the following cogent, comprehensive, articulate response to this issue:

Artificial intelligence (AI) has the potential to greatly impact e-commerce sales by improving customer engagement and experience. AI-powered chatbots can provide personalized and immediate customer service, while machine learning algorithms can be used to recommend products or create personalized discounts for customers. Additionally, AI can be used to analyze customer behavior and preferences, allowing e-commerce companies to better target their marketing efforts and improve the overall shopping experience. Another way AI can boost e-commerce sales is through image and voice recognition technology. This allows customers to search for products using natural language or by taking a picture of an item, making the shopping experience more convenient and efficient. AI can also assist e-commerce companies with inventory management and forecasting demand. This can help companies make sure they have the right products in stock at the right time, reducing the likelihood of stockouts and lost sales. Finally, AI-powered fraud detection systems can help e-commerce companies prevent fraudulent transactions, improving customer trust and loyalty. Overall, AI can help e-commerce companies boost sales by providing a more personalized and efficient shopping experience for customers.

To many observers, this response is virtually indistinguishable from one written by a competent human technical writer, but the important point about the above response is the relative infancy of this AI-driven technology and ChatGPT is learning all the time. The same mathematician that helped the Allies win World War II by cracking the Enigma code, Alan Turing, also proposed the so-called Turing test whereby a computer could be regarded as exhibiting human-like qualities if humans could not differentiate its responses from another human. When AI-powered applications such as ChatGPT and combined with lifelike avatars with human speech, the overall effect can be both powerful and a little creepy according to recent research. Nevertheless and not surprisingly -- other vendors are also currently developing their own AI-powered interfaces for online exchanges with consumers, and it is reasonable to posit that the Turing test will no longer represent the gold standard for differentiating a computer from a human in the foreseeable future and these and related issues are examined below.

Section 3: Literature Review/ Overview

Although every retailers specifc circumstances and requirements for their e-commerce needs are unique, there has been a clear move towards the implementation of AI-supported chatbots, avatars and augmented reality interactive technologies in e-commerce offerings in recent years (Ruan & Mezei, 2022). This trend is based on the fact that there are...

The custom questionnaire will be posted on SurveyMonkey for a period of 30 days. During the period immediately prior to the posting and throughout the 30-day period, participants will be recruited using invitations in online forums devoted to AI technologies in general and those focused on AI-enabled retailing in particular. This 30-day period will also be used to complete the final literature review and fine-tune the methodology section to better reflect all of the steps that were performed to prepare for and complete the study. The data analysis and synthesis are projected to require about one week and another 3 days will be needed for the final write-up as set forth in the Gannt chart depicted in Table 2 below. Because a free SurveyMonkey account will be used, there will be no costs incurred in completing the proposed study.

Table 2

Gantt chart of timings and project management

Task

Start Date

Completion Date

Duration

Questionnaire administration

February 1, 2023

March 2, 2023

30 days

Literature review completion

February 1, 2023

March 2, 2023

30 days

Data analysis and synthesis

March 3, 2023

March 9, 2023

7 days

Final write-up

March 10, 2023

March 12, 2023

3 days

Section 7: Research Instrument

A five-level, Likert-scaled custom questionnaire that is intended to develop fresh insights into consumer preferences for AI-enabled e-commerce offerings is provided at Appendix A.

Section 8: Presentation and Structure

The findings that emerge from the synthesis of the secondary and primary data will be presented in a PowerPoint presentation and interpreted in a hard-copy brochure to provide timely guidance for retailers seeking to maximize the effectiveness of their AI in their e-commerce offerings.

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References

Artificial Intelligence in E-Commerce. (2022). Big Commerce. Retrieved from https://www.big commerce.com/articles/ecommerce/ecommerce-ai/.

Chen, J.-S., Le, T.-T.-Y., & Florence, D. (2021). Usability and responsiveness of artificial intelligence chatbot on online customer experience in e-retailing. International Journal of Retail & Distribution Management, 49(11), 15121531

Li, M., & Wang, R. (2023). Chatbots in e-commerce: The effect of chatbot language style on customers continuance usage intention and attitude toward brand. Journal of Retailing & Consumer Services, 71, 1-16.

Moriuchi, E., Landers, V. M., Colton, D., & Hair, N. (2021). Engagement with chatbots versus augmented reality interactive technology in e-commerce. Journal of Strategic Marketing, 29(5), 375389.

Plock, S. du. (2021). Enjoying Research in Counselling and Psychotherapy: Qualitative, quantitative and mixed methods research/Reflective Practice and Personal Development in Counselling and Psychotherapy/Making Research Matter: Researching for change in the theory and practice of counseling and psychotherapy. Existential Analysis: Journal of the Society for Existential Analysis, 32(2), 351356.

Ruan, Y., & Mezei, J. (2022). When do AI chatbots lead to higher customer satisfaction than human frontline employees in online shopping assistance? Considering product attribute type. Journal of Retailing & Consumer Services, 68, 1-12.

Song, S. W., & Shin, M. (2022). Uncanny Valley Effects on Chatbot Trust, Purchase Intention, and Adoption Intention in the Context of E-Commerce: The Moderating…