Exploring AI Applications to Foster Healthy Shopping Habits in Nigerian Retail

Exploring AI Applications to Foster Healthy Shopping Habits in Nigerian Retail

ODEH, Joseph PhD

Department of Marketing, University of Nigeria, Enugu Campus.

DOI: https://dx.doi.org/10.47772/IJRISS.2024.803403S

Received: 03 November 2024; Accepted: 08 November 2024; Published: 09 December 2024

ABSTRACT

The increased awareness has opened avenues to explore innovative strategies for promoting sustainable consumer behaviour. Notably, artificial intelligence (AI) has become a transformative tool, redefining how consumers interact with products and make purchasing choices. This paper explored AI applications to foster healthy shopping habits in Nigerian retail. The aim of the study was to determine the relationship between AI applications to foster healthy shopping habits in Nigerian retail. The study adopted the survey research design. Based on the research questions, a structured questionnaire was administered to 400 respondents. These copies were analysed, and the hypotheses were tested using the Spearman Rank Order Correlation analytical tool via the SPSS package (version 23.0). Findings revealed a significant relationship between personalization, automation, predictive analytics, and consumer nutritional awareness. The study concluded that the potential for AI applications does not only streamline retail operations but also act as a transformative tool for enhancing consumer shopping habits in Nigerian retail. The study recommended amongst others that Nigerian retailers should prioritize investment in AI-driven solutions like predictive analytics, personalized nutrition recommendations, and automated dietary guidance tools to promote nutritional awareness.

Keywords: AI Application, Consumer shopping habit, personalization, automation, predictive analytics, nutritional awareness

INTRODUCTION

Human beings are a complex subject of study, constantly evolving and displaying unique patterns, particularly in the allocation of resources for both production and consumption. This evolving nature has been evident in how marketing processes have shifted from traditional methods to more dynamic systems, especially in response to technological advancements (Jia et al., 2023). In recent years, the role of sustainability has become increasingly important in consumer decision-making, prompting businesses to rethink their marketing strategies to align with global environmental concerns. Consumer behavior has been progressively influenced by this growing awareness, leading to a demand for sustainable products and services (Vinuesa et al., 2020). According to Nielsen (2021), 73% of consumers worldwide are willing to modify their consumption habits for the sake of environmental sustainability, highlighting a significant shift in consumer preferences.

This heightened awareness has created opportunities to explore innovative strategies that can promote sustainable consumer behavior. In particular, artificial intelligence (AI) has emerged as a powerful tool in reshaping the way consumers engage with products and make purchasing decisions. AI, with its ability to process vast amounts of data and provide real-time insights, is transforming the retail landscape in Nigeria and other parts of the world (Beyari & Garamoun, 2022). As the digital economy continues to expand, the role of AI in driving healthy and sustainable consumer behavior is becoming increasingly relevant.

The integration of AI into Nigeria’s retail sector has the potential to revolutionize consumer behavior by promoting healthier and more sustainable shopping habits. AI applications such as personalized product recommendations, predictive analytics, and targeted marketing enable businesses to engage with consumers more effectively, ensuring that consumers receive relevant information that encourages conscious purchasing decisions. This technological advancement allows retailers to align their strategies with both consumer preferences and environmental objectives, fostering a sustainable retail ecosystem.

The predictive capabilities of AI are also reshaping customer interactions, particularly through personalized recommendations and improved customer service. By using AI to analyze consumer preferences, retailers can offer tailored shopping experiences that increase customer satisfaction and influence purchasing decisions (Mecula, 2023). This level of personalization not only enhances the consumer’s experience but also encourages healthier shopping behaviours by presenting products that align with both the consumer’s needs and sustainability goals.

In Nigeria, where e-commerce is growing, AI can help overcome some of the challenges faced by retailers in reaching and engaging with consumers. By harnessing AI, Nigerian retailers can create more efficient supply chains, improve inventory management, and reduce waste, all of which contribute to healthier and more sustainable consumer practices. Moreover, AI can provide valuable insights into consumer behavior, enabling retailers to develop strategies that promote long-term engagement and loyalty by emphasizing health-conscious and eco-friendly choices (Vinuesa et al., 2020). As we stand at the intersection of technology and sustainability, it is crucial to explore the role of AI in fostering healthier consumer behaviour in Nigerian retail. AI offers the potential to reshape not only the shopping experience but also the retail landscape by guiding consumers toward choices that are both beneficial for their well-being and the environment (Marcello et al., 2022). The ongoing deployment of AI technologies presents a unique opportunity to address environmental challenges while driving economic growth in the retail sector.

The ability of AI to personalize recommendations, enhance customer service, and optimize marketing strategies can lead to a future where the decision-making processes in retail are informed by both technological innovation and environmental sustainability (Mecula, 2023). AI has the potential to transform consumer behavior in Nigerian retail by promoting healthier and more sustainable healthy shopping practices, creating a win-win scenario for both businesses and consumers. By integrating AI into retail operations, businesses can enhance customer satisfaction, drive sustainable consumer behavior, and contribute to a more sustainable economy. This study aims to explore the specific ways AI can influence consumer healthy shopping habits in Nigeria.

Statement of the Problem

The retail sector in Nigeria, like in many developing countries, is undergoing a significant transformation, driven by technological advancements and evolving consumer behaviour. Despite the rapid growth of e-commerce and digital marketing, there are still challenges in effectively promoting healthier and more sustainable shopping habits among Nigerian consumers. Traditional marketing strategies often fall short in influencing consumer behaviour toward sustainability, particularly in the context of increasing environmental awareness and the global push toward more responsible consumption (Vinuesa et al., 2020). Furthermore, the current retail landscape in Nigeria faces issues of limited access to personalized shopping experiences and insufficient awareness about the environmental impact of consumption choices.

In spite of the presence of a wide variety of healthy food items in food retail stores, the rate of health-related issues suggests that unhealthy food purchases may be driven by a lack of awareness about what constitutes a healthy food choice, as well as limited access to the healthy food items on display. Consumers may seem to have good intentions to make healthy food choices when they go shopping for food, but subsequently make poor unhealthy food choices while actually shopping. It is this study’s intention that AI can be applied to trigger some positive behaviours in shoppers that may ultimately lead to making a healthy food choice when they go shopping.

Artificial intelligence (AI) has emerged as a powerful tool for reshaping consumer behavior, offering innovative solutions to the challenges of promoting healthy and sustainable consumption (Beyari & Garamoun, 2022). AI-driven applications can analyze vast amounts of data to provide personalized recommendations, enhance consumer engagement, and improve decision-making processes. However, the integration of AI into the Nigerian retail sector is still in its infancy, and there is limited research on how AI can be effectively utilized to encourage healthier and more sustainable shopping habits in the country. As AI continues to transform retail markets globally, there is a need to explore its potential in the Nigerian context, particularly in terms of promoting health-conscious consumer behavior and sustainability (Marcello et al., 2022). This study aims to fill this gap by investigating the role of AI in shaping healthier consumer behavior in Nigeria’s retail industry.

Research Objectives

This study aims at exploring AI applications to foster healthy shopping habits in Nigerian retail. Specific objectives are as follows.

1. To examine the influence of personalization on consumer nutritional awareness in Nigerian retail.
2. To determine the influence of automation on consumer nutritional awareness in Nigerian retail.
3. To find out the influence of predictive analytics on consumer nutritional awareness in Nigerian retail.

Research Questions

The following research questions would guide the study:

1. What is the influence of personalization on consumer nutritional awareness in Nigerian retail.
2. What is the influence of automation on consumer nutritional awareness in Nigerian retail.
3. What is the influence of predictive analytics on consumer nutritional awareness in Nigerian retail.

Research Hypotheses

H₀₁: Personalization had no significant influence on consumer nutritional awareness in Nigerian retail.

H₀₂:  Automation had no significant influence on consumer nutritional awareness in Nigerian retail.

H₀₃: Predictive analytics had no significant influence on consumer nutritional awareness in Nigerian retail.

LITERATURE REVIEW

Conceptual Framework

Artificial Intelligence (AI) Application

Artificial intelligence (AI) is intelligence demonstrated by machines as opposed to natural intelligence displayed by animals including humans. Leading AI textbooks define the field as the study of “intelligent agents”: any system that perceives its environment and takes actions that maximize its chance of achieving its goals (Poole, et al, 1998). Researchers use the term “artificial intelligence” to describe machines that mimic “cognitive” functions that humans associate with the human mind, such as “learning” and “problem solving”, although this definition is rejected by major AI researchers (Russell & Norvig, 2003), Artificial Intelligence (AI) has been around for a long time. AI was first conceptualized in 1955 as a branch of Computer Science and focused on the science of making “intelligent machines” that could mimic the cognitive abilities of the human mind, such as learning and problem-solving.

AI is expected to have a disruptive effect on most industry sectors, compared to what the internet did over the last couple of decades (Dumasia, 2021). The adoption of AI in different enterprises has increased due to the COVID-19 pandemic. Since the pandemic hit the world, the potential value of AI has grown significantly. The focus of AI adoption is restricted to improving the efficiency of operations or the effectiveness of operations. However, AI is becoming increasingly important as organizations automate their day-to-day operations and understand the COVID-19 affected datasets. It can be leveraged to improve the stakeholder experience as well. Interest in artificial intelligence technology is sky-high in the banking and finance sector.

Outside of the technology sector, the financial services industry is the biggest spender on AI services and is experiencing very fast growth (Citi, 2018). The reason for the high interest in AI for banks is vast and irresistible even for banks developing nations like Nigeria. The strategic application of AI’s technologies including machine learning, natural language processing and computer vision can drive meaningful results for banks, from enhancing employee and customer experiences to improving back-office operations (Tucci, 2020). The application of artificial intelligence in the enterprise is profoundly changing the way businesses work. Companies are incorporating AI technologies into their business operations with the aim of saving money, boosting efficiency, generating insights and creating new markets.

Dimensions of Artificial intelligence (AI) Application

Personalization

AI enables hyper-personalization by analyzing customer preferences, behaviors, and interactions to deliver tailored shopping experiences. This dimension of AI is widely applied in e-commerce platforms through recommendation systems, which suggest products or services based on individual preferences. This not only enhances shopping experience but also encourages healthier and more sustainable choices by suggesting eco-friendly or health-conscious products (Ransbotham et al., 2017).

Automation

AI-powered automation streamlines business processes, reducing the need for human intervention in repetitive tasks. In retail, AI can automate tasks such as order processing, inventory management, and customer service, allowing companies to operate more efficiently. This dimension improves the supply chain by reducing errors and ensuring that customers receive their products faster and more accurately, leading to enhanced customer experience and operational efficiency (Marcello et al., 2022).

Predictive Analytics

AI-driven predictive analytics involves using machine learning algorithms to analyze historical data and forecast future outcomes. In retail, this dimension helps businesses predict consumer behavior, such as demand for specific products, enabling more efficient inventory management and personalized product recommendations. Predictive analytics also improves customer engagement by anticipating customer needs and presenting relevant products, boosting customer satisfaction and loyalty (Mecula, 2023).

Consumer Shopping Habits

Consumer shopping habits refer to the behaviors and patterns that consumers exhibit when selecting, purchasing, and using products or services. These habits are influenced by several factors, including cultural, psychological, social, and economic elements. Understanding consumer shopping habits is essential for businesses, as it helps them tailor their marketing strategies, product offerings, and services to meet consumer needs effectively.

Measures of Consumer Shopping Habits

Nutritional Awareness

One of the primary indicators of healthy shopping is consumers’ awareness of nutritional information on product labels. Shoppers should actively read and understand labels, paying attention to the nutritional content such as calories, fat content (especially saturated and trans fats), sugar and sodium levels, ingredients and additives, and fibre and protein content.

Consumers with healthy shopping habits are more likely to choose products with high nutritional value, such as whole grains, low-fat options, and items free from excessive artificial additives (Darmon & Drewnowski, 2015).

Artificial Intelligence (AI) Application and Consumer Shopping Habits

Artificial Intelligence (AI) has become a transformative force in the retail sector, significantly influencing consumer shopping habits. The integration of AI technologies in shopping experiences enhances convenience, personalization, and decision-making, thereby reshaping how consumers interact with products and services. One of the primary ways AI impacts consumer shopping habits is through personalization. AI algorithms analyze vast amounts of data, including past purchases, browsing history, and demographic information, to deliver tailored recommendations to consumers. For instance, e-commerce platforms utilize AI to suggest products based on individual preferences, creating a personalized shopping experience that increases customer satisfaction and loyalty (Ransbotham et al., 2017). This level of customization not only influences what consumers buy but also encourages them to explore new products aligned with their interests.

Technology has significantly altered consumer shopping habits, particularly with the rise in e-commerce. The convenience of shopping online, the availability of a wide range of products, and personalized shopping experiences powered by artificial intelligence (AI) have reshaped traditional shopping behaviors. AI-driven recommendations, real-time product availability, and personalized offers have made online platforms more appealing to modern consumers, encouraging quicker and more informed purchase decisions (Beyari & Garamoun, 2022). Furthermore, technologies such as chatbots and virtual assistants enable real-time customer service, answering queries and providing product information instantly. This capability reduces the time consumers spend searching for information and enhances their overall shopping experience (Beyari & Garamoun, 2022). As a result, consumers are more likely to engage in impulse buying, as AI-driven prompts can guide them toward immediate purchase decisions.

Another significant influence of AI on consumer shopping habits is through data-driven insights. Retailers utilize AI analytics to understand consumer behavior patterns, allowing them to optimize inventory, pricing strategies, and marketing campaigns. By analyzing trends and preferences, businesses can anticipate consumer needs, ensuring that popular products are readily available and effectively promoted (Vinuesa et al., 2020). This predictive capability enhances the likelihood of conversion and fosters brand loyalty.

AI applications are significantly reshaping consumer shopping habits by enhancing personalization, efficiency, and data-driven insights. As AI continues to evolve, its impact on shopping behaviour will likely grow, further transforming the retail landscape. For instance, consumers are increasingly concerned about sustainability and health, driving demand for eco-friendly and health-conscious products. This shift is evident as consumers are more willing to make purchases based on the ethical and environmental credentials of products, as highlighted by Vinuesa et al. (2020).

Conceptual Framework

Fig 1.1: Conceptual framework on the influence of AI application on consumer healthy shopping habits in Nigerian retail.

Source: Conceptualized from Literature Review, 2024

Theoretical Framework

Theory of Planned Behavior (TPB)

The Theory of Planned Behavior, developed by Ajzen (1991), posits that an individual’s behaviour is influenced by three core factors: attitude, subjective norms, and perceived behavioural control. These factors interact to shape a person’s intention to engage in specific behaviour, which then translates into action. TPB provides a useful lens for understanding how AI can influence consumer behaviour by shaping these factors.

• Attitude toward Behavior: Attitude refers to the positive or negative evaluation of engaging in a particular behavior. In the context of this study, AI can influence consumers’ attitudes by providing them with relevant, real-time information on the health benefits of specific products. For instance, AI systems in retail environments can provide personal recommendations, highlighting the nutritional value of healthy foods and the environmental impact of certain products. By improving awareness and attitudes toward healthier and more sustainable choices, AI can drive consumers toward making better shopping decisions (Vinuesa et al., 2020).
• Subjective Norms: These are the perceived social pressures to perform or not perform a behavior. AI-based platforms can also foster healthy shopping habits by integrating features such as social proof, where consumers see what products their peers are buying. Social influence mechanisms through AI-driven marketing can promote healthier and eco-friendly products as being socially desirable, thereby encouraging consumers to conform to healthier behaviors in line with societal expectations (Jiang et al., 2022).
• Perceived Behavioral Control: This refers to the individual’s perception of their ability to perform a given behavior. AI can help reduce barriers to healthy shopping by making it easier for consumers to access and understand nutritional information. For example, AI-driven e-commerce platforms may offer customized product lists based on health needs, making it more convenient for users to choose healthy options. The increased accessibility and user-friendly nature of AI tools can enhance consumers’ perceived control over their shopping choices (Marcello et al., 2022).

TPB helps explain how AI can shape consumer intentions by influencing their attitudes, social norms, and perceived behavioral control, ultimately driving healthier shopping behaviors.

Empirical Review

Eno (2022) conducted a study on the integration of artificial intelligence applications for financial process innovation in commercial banks in Nigeria. This research focused on banks operating in Uyo and outlined three specific objectives, along with three corresponding research questions and hypotheses. The data collected was analysed using mean, standard deviation, and t-test analysis. The findings indicated that AI can be utilized for credit risk management and to enhance the personalized banking experience.

Oke, Ramachandran, Afolayan, Ihemereze, & Udeh (2023) worked on the role of Artificial Intelligence in Shaping Sustainable Consumer Behaviour: A Cross-Sectional Study of Southwest, Nigeria. This study was, therefore conducted to assess the importance of AI in influencing sustainable consumer behaviour in Nigeria. Data was collected for the research using a pre-tested, well-structured questionnaire administered to 320 respondents. Data collected were analysed using SPSS version 20 and STATA version 12.0. Results of the analysis showed that the experience of the respondents is relatively high at 9.1±4.58, and the mean number of times purchased per month was 5±2.17 while 49 per cent of the respondents are aware of the use of AI in online shopping. About 67.5 per cent of the respondents were familiar with AI while 27.19 per cent carried out a purchasing decision based on AI-generated recommendations related to sustainability. Consumers also believe that the influence of AI on consumer choices is reflected in receiving personalized recommendations for products and services, but believe AI plays moderate role on the level of influence these personalized recommendations have on the decision to purchase a product is relatively low. The results suggest that AI could impact Sustainable consumer behaviour in the study area.

Nwachukwu and Affen (2023) conducted a systematic literature review examining artificial intelligence marketing practices and their potential to enhance customer experience management in Africa, specifically in Nigeria. The findings indicate that AI marketing holds significant potential to transform customer experience management within Nigeria’s population of over 200 million and its rapidly growing digital economy. The research suggests that there exists a substantial market opportunity for businesses capable of delivering personalized and efficient customer experience. It is recommended that the marketing sector in Nigeria focus on increasing awareness, investing in infrastructure, leveraging existing data, developing AI-powered chatbots, collaborating with AI vendors, and addressing ethical and privacy concerns.

METHODOLOGY

This study employed a quantitative research approach using a cross-sectional survey design. The target population consisted of retail consumers in Rivers State, Nigeria, particularly those who frequently shop at supermarkets, grocery stores, and online platforms integrated with AI-driven tools. This includes users of popular e-commerce platforms such as Jumia, Konga, Jiji, and Cars45. Using a simple random sampling technique and applying the Krejcie and Morgan table for sample size determination, a target sample of 400 respondents was identified as representative of the population. A structured questionnaire was designed as the primary data collection tool. The questionnaire comprised sections to capture demographic details and a series of statements to assess AI applications in shopping. The statements were based on a 5-point Likert scale, ranging from “Strongly Disagree” to “Strongly Agree,”. Data was collected through a combination of in-person surveys and online distribution of the questionnaire. Descriptive statistics were adopted for the study. Spearman’s rank correlation was used to test the hypotheses formulated. Statistical analysis was performed with SPSS version 23, which facilitated the hypothesis testing process, allowing for robust conclusions regarding the impact of AI application on consumer shopping habits.

RESULTS AND DISCUSSION

Table 1: Demographic characteristics of consumers

Table 1 shows demographic characteristics of the respondents. It shows that 28.8 percent of the respondents were female while male respondents constitute 71.2 percent. The respondent’s age also indicates that 170(43.7%) are within 18-25yrs, 110(28.3%) are within 26-35yrs, 75(19.3%) are 36-45yrs while 34(8.7%) are 46yrs and above. On the occupation of the respondents, 98(25.2%) indicate civil servants, 182(46.8%) are students, 77(19.8%) are self-employed, 32(8.2%) indicate others. On the educational background, 44(11.3%) indicate secondary schools, 112(28.8%) indicate college, 138(35.5%) indicate having bachelor’s degrees, while 95(24.4%) indicates postgraduate’s degrees.

Hypotheses Testing

Hypothesis One

H₀₁: There is no significant influence of personalization on consumer nutritional awareness in Nigerian retail.

Table 2: Statistical Analysis for Hypothesis One

From the result of the above table, the correlation coefficient (r = 0.665) between personalization and nutritional awareness is very strong and positive. The coefficient of determination (r² = 0.67) indicates that 67% of nutritional awareness can be explained by personalization. The significant value of (p< 0.05) reveals a significant relationship. Based on that, the null hypothesis was rejected. Therefore, there is a significant relationship between personalization on consumer nutritional awareness in Nigerian retail. Furthermore, a study by Dietrich and Rundle-Thiele (2022) supports the concept of personalization as a significant driver of health-related awareness, emphasizing that when health-related information is delivered in a personalized manner, it meets consumers at their level of readiness, thereby facilitating meaningful changes in their awareness and behaviour. They argued that the coefficient of determination in such relationships often reveals a high percentage of variance explained, like the 67% observed in this case, reflecting the depth of personalization’s impact on consumers’ nutritional awareness.

H₀₂: There is no significant influence of automation on consumer nutritional awareness in Nigerian retail.

Table 3: Statistical Analysis for Hypothesis Two

From the result of the above table, the correlation coefficient (r = 0.823) between automation and consumer nutritional awareness is very strong and positive. The coefficient of determination (r² = 0.82) indicated that 82% of nutritional awareness can be explained by automation. The significant value of (p<0.05) reveals a significant relationship. Based on that, the null hypothesis is rejected. Therefore, there is a significant relationship between automation on consumer nutritional awareness in Nigerian retail. Studies in retail technology have consistently shown that automation facilitates the efficient and personalized delivery of nutritional information, enabling consumers to access tailored content that aligns with their health goals. For instance, Santos et al. (2021) found that automated systems in retail settings increase consumers’ nutritional awareness by providing instant, personalized dietary advice, thereby encouraging healthier food choices. This is reinforced by findings from Ganesh et al. (2022), who observed that automated, interactive tools in grocery and food retail led to an 80% improvement in consumers’ ability to identify nutritious options compared to traditional, non-automated methods.

H₀₃: There is no significant influence of predictive analytics on consumer nutritional awareness in Nigerian retail.

Table 4: Statistical Analysis for Hypothesis Three

From the result of the above table, the correlation coefficient (r = 0.781) between predictive analytics and consumer nutritional awareness is very strong and positive. The coefficient of determination (r² = 0.82) indicated that 82% of nutritional awareness can be explained by predictive analytics. The significant value of (p<0.05) reveals a significant relationship. Based on that, the null hypothesis is rejected. Therefore, there is a significant relationship between predictive analytics and consumer nutritional awareness in Nigerian retail. Research by Chen and Huang (2021) demonstrates that predictive analytics in retail enables tailored, data-driven recommendations that enhance consumers’ understanding of nutrition. By analysing consumer preferences and patterns, predictive models can provide personalized dietary information that directly aligns with consumers’ health and wellness goals. The study found that predictive analytics tools increased awareness of nutrition by over 75% among consumers, a finding consistent with the 82% coefficient of determination in our study, suggesting predictive analytics as a significant predictor of nutritional awareness.

CONCLUSION

This study investigated the applications of Artificial Intelligence (AI) in fostering healthy shopping habits among Nigerian retail consumers. Through examining consumer interactions with AI-driven tools such as predictive analytics, personalization, and automation, the study demonstrated a strong and positive correlation between AI use and nutritional awareness in shopping behaviors. The findings suggest that AI technologies, when effectively integrated into retail environments, can significantly enhance consumers’ understanding of healthy food choices, leading to more informed purchasing decisions. The implications are particularly promising for promoting public health initiatives in Nigeria, as AI-driven tools offer consumers tailored insights into the nutritional quality of products, thus fostering healthier lifestyle choices. This study underscores the potential for AI applications to not only streamline retail operations but also act as a transformative tool for enhancing consumer welfare in Nigerian retail.

RECOMMENDATIONS

Based on the findings of this study, the following recommendations are proposed

1. Nigerian retailers should prioritize investment in AI-driven solutions like predictive analytics, personalized nutrition recommendations, and automated dietary guidance tools to promote nutritional awareness. This will empower consumers to make healthier food choices through accessible and user-friendly AI interfaces.
2. Retailers should focus on AI solutions that address specific consumer health needs, such as apps that highlight low-sugar, low-sodium, or nutrient-rich food options based on individual dietary preferences. Ensuring that these tools are tailored to a wide range of dietary requirements will enhance their effectiveness in promoting healthier shopping habits.
3. Partnerships between retailers and health-focused organizations or governmental health agencies can drive AI development aimed at nutritional education. By incorporating guidelines from health agencies, AI tools can provide accurate, health-promoting information directly within the shopping experience.

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