How Retailers Can Use AI to Boost Their Sales and Enhance the Consumer Experience

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 study’s methodology, section five discusses the data analysis strategies that will be used, and section six presents the proposed study’s 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 1974’s “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 retailer’s specific 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 a number of valuable benefits that accrue to the use of AI in e-commerce settings, including most especially those set forth in Table 1 below.

Table 1

Benefits of Using Artificial Intelligence in E-Commerce Settings

Benefit

Description

More targeted marketing and advertising.

? Personalization is a top priority, according to surveyed retailers, but only 15% say they’ve fully implemented personalization across channels. Stand out from the crowd with a more personalized message and have one-to-one conversations with customers.

? Advances in AI and machine learning have enabled deep personalization techniques to customize content by user. By analyzing big data from purchase histories and other customer interactions, retailers can zero in on what customers really want and deliver the message that will most resonate.

Increased customer retention.

? Delivering targeted marketing and advertising messages personalized for their customers can increase retention. There is a 10-15% uplift potential in revenue and retention from omnichannel personalization strategies.

? A critical element of personalization is building better data and insights on customers, an asset that also generates additional value across the value chain. The return on investment for personalization will quickly outpace that of traditional mass marketing.

Seamless automation

? The goal of automation is to accomplish a task with as little human intervention as possible. That can mean anything from scheduling emails in a customer relationship management or marketing tool, automating tasks or leveraging advanced technology to help with hiring. In the context of future ecommerce trends, however, some of the most commonly talked about today are robotics and machine learning.

? AI can play a big role in helping automate the repetitive tasks that keep online stores functioning. With AI, retailers can automate things like product recommendations, loyalty discounts, low-level support, and more.

Efficient sales process

? Using AI can help create a more efficient sales process by gathering data about your customers, automate follow-up abandoned cart inquiries, and more.

? Retailers can help move customers through the funnel by having them engage with chatbots for simple questions.

Source: Adapted from Artificial Intelligence in E-Commerce (2022)

Given the wide array of benefits of using AI in e-commerce set forth in Table 1 above, it is reasonable to suggest that AI-enabled features will become increasingly commonplace in e-commerce settings in the future. Moreover, many consumers today not only want to experience AI in their online experiences, they are increasingly expecting it as well. Consequently, increasing numbers of retailers are incorporating different types of AI into their online offerings as a way to generate new interest and differentiate themselves from their competitors (Moriuchi et al., 2021). Chatbots in particular have become the focus of interest on the part of online retail vendors that are searching for ways to better engage consumers and enhance their online shopping experience (Li & Wang, 2023).

There are some important factors that must be taken into account when using chatbots, however, that can make or break an e-commerce platform. For example, a study by Li and Wang (2023) found that the extent to which chatbots used informal language in their online exchanges with humans was the extent to which consumers trusted the chatbots, an outcome which in turn increased their interest in the brand and the likelihood of their making a purchase. This finding underscores the need for online marketers to ensure that their chatbot offerings are fine-tuned to their consumers’ preferences.

It is also important to note, though, that even the appearance of avatars used with chatbots can have a profoundly positive or negative impact on human users. In this regard, a study by Moriuchi et al. (2021) examined the effects that the humanization of avatars used in e-commerce had on consumers’ levels of trust and their perception of the “eeriness” of the computer-generated visages. The study involved 185 subjects who were requested to evaluate their online experiences with chatbot agents. An interesting finding that emerged from this study was the fact that the more human-like avatars were made, the creepier they were perceived by the participants and this feeling translated into reduced trust levels, the willingness to use the chatbot agent again as well as the ultimate purchase intent (Moriuchi et al., 2021). This finding suggests that humans still prefer easily discernible computer-generated chatbot agents and that trust levels are essential for successful e-commerce applications using AI.

Section 4: Research Methodology

Overview of research methodology. The proposed study will use a mixed methodology consisting of a synthesis of qualitative and quantitative secondary resources together with the quantitative findings that emerge from the administration of a custom questionnaire (see proforma copy at Appendix A). A mixed methodology research strategy was regarded as the optimal approach for the purposes of the proposed study since it can provide new insights into an issue of interest that might not be otherwise possible using a qualitative or quantitative approach alone (Plock, 2021). The sampling frame for the proposed study will be consumers aged 18 years and over who routinely shop online.

Ethical Issues. Any research involving human subjects has several ethical issues that must be considered (Xia, 2023). First and foremost, participation in the proposed study will be voluntary and participant anonymity will be assured throughout the research process. In addition, although no compensation will be offered in exchange for participation in the proposed study, all participants will be offered a copy of the study when completed upon request. Finally, all institutional review board requirements will be satisfied and approval received prior to posting the custom questionnaire online for completion.

Section 5: Data Analysis

The statistical data that is collected from the custom questionnaire will be analyzed using an Excel spreadsheet to develop percentile results. These results will be presented in tabular fashion as well as in a series of charts to graphically depict the findings. The qualitative and quantitative data that emerge from the synthesis of the secondary literature will be synthesized with the primary data to develop informed and timely insights into the issues of interest to the study proposed herein. In addition, the custom questionnaire described in section seven below will be tested for face validity by having it reviewed by several classmates and friends who will not participate in the final study to ensure that the instrument appears to collect the type of data intended.

Section 6: Timings and Project Management

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