Cart Abandonment Research Articles

Smart moves: Flipkart’s name-personalized nudging techniques to combat cart abandonment

Flipkart, a leading e-commerce platform, has made significant global strides by offering a diverse range of products, including electronics, fashion, and groceries. Flipkart has a significant problem with high cart abandonment rates, particularly on mobile devices, despite its success. This problem is severe because it damages marketing efforts, impacts customer retention, and causes a large loss of revenue. Complicated checkout procedures and unforeseen expenses are major contributors. Flipkart uses name-based personalized nudges to address this, giving customers a sense of familiarity and customization that makes them feel appreciated. Purchase completion is encouraged by these nudges, which include recovery emails that use the customer’s name and provide customized incentives. Challenges in putting these nudges into practice include protecting customer privacy and guaranteeing data accuracy. Nonetheless, the possible advantages of lowering abandonment rates and strengthening allegiance make it valuable. Flipkart also improves the shopping experience by strategically nudging customers. Transparent pricing, streamlined checkout procedures, guest checkout, a variety of payment methods, and conspicuous security badges are a few of them. To further promote transaction completion and reduce abandonment rates, several interventions are used, such as mobile optimization, exit-intent popups, and cart recovery emails. Flipkart’s dedication to establishing a smooth shopping experience and tackling the serious problem of cart abandonment is demonstrated by these initiatives. All things considered, even though putting these nudges into practice can be difficult, Flipkart’s creative strategy for addressing cart abandonment through personalization and name-based personalized nudges demonstrates its commitment to improving customer satisfaction and increasing conversion rates.

AI-Driven Incident Management in Retail : A Case Study

This article examines the implementation of AI-driven incident management in a major U.S. retail corporation (Walmart) with annual revenues exceeding $500 billion. The company faced significant operational challenges, including high cart abandonment rates (69%), frequent system downtimes causing $3.5 million losses per incident, and slow incident response times with MTTR averaging 4 hours. Through the implementation of comprehensive AI solutions, including advanced monitoring systems processing over 1 terabyte of log data daily, anomaly detection with 95% accuracy, and automated incident management resolving 60% of issues without human intervention, the company achieved remarkable improvements. Key results include a 40% reduction in downtime, a 20% decrease in cart abandonment rates (recovering $3.6 billion in potential lost sales), and an 81.25% improvement in Mean Time to Resolution (MTTR). The article also reveals broader economic impacts, including creating 5,000 new jobs in the AI and ML fields, a 15% improvement in sector-wide operational efficiency, and a $180 billion contribution to U.S. GDP over three years. The successful implementation demonstrates the transformative potential of AI in retail operations while providing valuable insights for organizations seeking to enhance their incident management capabilities through technological innovation.

Why leave items in the shopping cart? The impact of consumer filtering behavior

Online product information provides crucial cues for consumer shopping behavior; however, the impact of consumer-side information manipulation on non-purchase behavior (e.g., shopping cart abandonment) remains unclear. Filtering, a common manipulation strategy, was initially considered synonymous with searching, both of which contribute to consumer purchase behavior. However, recent research suggests significant differences, particularly in terms of cost and product matching. This study explores how such differences affect information manipulation and subsequently shape shopping cart abandonment, drawing on information foraging theory. Based on the premise that a forager's interaction with the environment is mediated by cognition, we find that consumer filtering behavior influences perceptions of serendipity (i.e., discovering unexpected items) and similarity (i.e., encountering similar items), thereby influencing shopping cart abandonment. Mediation analyses reveal that perceived serendipity and similarity are equally potent mediators. Marginal effects analyses demonstrate that a one standard deviation increase in consumer perceptions of serendipity (similarity) in filtering results increases the likelihood of shopping cart abandonment by 32.2% (22.1%). Theoretical contributions and practical insights for information behavior researchers and digital marketers are also provided.

IMPACT OF BNPL SERVICE ON CONSUMERS PURCHASING BEHAVIOUR

The impact of Buy Now, Pay Later (BNPL) services on consumers' retail purchase behavior is examined in this study. The study uses a mixed-methods approach to investigate the attitudes, behaviors, and motives behind BNPL adoption. Quantitative analysis of survey data from many participants is combined with qualitative insights. This research aims to fill this gap by examining how Flipkart's BNPL service influences consumer behavior, cart abandonment rates, and overall e-commerce sales. Additionally, it seeks to explore the implications for both consumers and businesses and assess the role of regulatory factors in this context. The objective of the study is to examine the influence of BNPL services on consumer decision-making processes, investigate the effects of BNPL on consumer spending habits and financial behaviors, explore the relationship between BNPL services and consumer loyalty in the e-commerce sector and to assess the impact of BNPL on impulse buying and its implications for consumer financial well-being. And we have gathered primary data through questionnaire, and these questionnaire contain 12 questions which was filled by 225 respondents, we have circulated the questionnaire on social media. Among every 100 active customers 75 are using BNPL. the research underscores the transformative influence of Buy Now, Pay Later (BNPL) services on online consumer transactions. The advent of BNPL has, indeed, raided the online purchase realm, altering the traditional dynamics of how consumers engage with e-commerce. As we witness this paradigm shift, it is imperative for stakeholders to recognize the far-reaching consequences, adapt to the changing landscape, and formulate strategies that balance the allure of BNPL with responsible financial practices for sustained and healthy growth in the digital shopping sphere.

A Study on Social Media Strategies Om Online Shopping Cart

The study examines the impact of social media strategies on online shopping cart abandonment Using a sample 245 online shoppers , we analyze the effectiveness of various social media strategies in reducing cart abandonment rates. we employ u-test ,h-test, and correlation analysis to evaluate the relationship between social media engagement and cart abandonment. our findings suggest that certain social media strategies significantly influence online shopping behavior , providing valuable insights for e-commerce businesses. Future flow technologies refers to a range of emerging technologies that are expected to shape the future of online shopping. These may include artificial intelligence (AI) for personalized shopping experiences, augmented reality (AR) for virtual try- ons , and chat bots for customer service. These technologies aim to enhance user experience, increase conversion rates, and reduce cart abandonment by providing more engaging and efficient shopping experiences.

Analyzing shopping cart abandonment enablers: an ISM and MICMAC approach

PurposeThe primary purpose of this study is to examine the factors leading to shopping cart abandonment and construct a model depicting interrelationship among them using interpretive structural modeling (ISM) and Matriced Impact Croises Multiplication Appliquee an un Classement (MICMAC).Design/methodology/approachInitially, 20 factors leading to shopping cart abandonment were extracted through a systematic literature review and expert opinions. Fifteen factors were finalized using the importance index and CIMTC method, for which consistency has been checked in SPSS software through a statistical reliability test. Finally, ISM and MICMAC approach is used to develop a model depicting the contextual relationship among finalized factors of shopping cart abandonment.FindingsThe ISM model depicts a technical glitch (SC8), cash on delivery not available (SC4), bad checkout interface (SC9), just browsing (SC11), and lack of physical examination (SC12) are drivers or independent factors. Additionally, four quadrants have been formulated in MICMAC analysis based on their dependency and driving power. This facilitates technical managers of e-commerce companies to focus more on factors leading to shopping cart abandonment according to their dependency and driving power.Research limitations/implicationsTaking an expert’s opinion as a base may affect the results of the study due to biases based on subjectivity.Practical implicationsThis study’s outcomes would accommodate practitioners, researchers, and multinational or national companies to indulge in e-commerce to anticipate factors restricting the general public from online shopping.Originality/valueFor the successful running of an e-commerce business and to retain the confidence of e-shoppers, every e-commerce company must make a strategy for controlling factors leading to shopping cart abandonment at the initial stage. So, this paper attempts to highlight the main factors leading to shopping cart abandonment and interrelate them using ISM and MICMAC approaches. It provides a clear path to technical heads, researchers, and consultants for handling these shopping cart abandonment factors.

Electronic shopping cart abandonment: What do we know and where should we be heading?

This paper aims to systematically review the literature on electronic shopping cart abandonment (ESCA). It analyzes the development of ESCA literature in terms of publication trends, publication outlets, number of citations, methodologies, and theoretical underpinnings. Furthermore, based on the literature synthesis, this review proposes a conceptual framework integrating the widely used antecedents, mediators, and moderators that influence ESCA. The antecedents include customer attributes and website-related factors while research and comparison mediate the relationship between these antecedents and ESCA. Using lexicometric analysis, this SLR identified key themes studied in ESCA literature over time, including customer decision-making criteria, motives and characteristics, online shopping environment, and website attributes. Further, this SLR suggests future research directions to advance ESCA literature from theoretical, contextual, and methodological perspectives. This SLR also suggests strategies for e-retailers and marketers to overcome ESCA. Overall, this review is a silver line in ESCA literature.

The Determinant Factors of Shopping Cart Abandonment Among E-commerce Customers in Indonesia

Predicting the non-purchase behavior of potential customers, such as the abandonment of online shopping carts, is a pivotal factor in determining the success of companies. Despite several conducted studies, further investigation is still required to gain a profound understanding of the underlying causes of these phenomena. The research aims to analyze the motivating factors behind shopping cart abandonment among ecommerce customers in Indonesia using a quantitative method. Furthermore, the population size is undefined, and the sample consists of 200 respondents selected through purposive sampling. The sample size is determined by five times the indicator number. The data analysis is conducted using Structural Equation Modeling (SEM) through SmartPLS 4.0.8.5, and the Coefficient of determination (R2) value for shopping cart abandonment is found to be 37.5%. The results show that complicated checkout, information overload, complicated policies, and limited shipping options positively impact shopping cart abandonment. Complicated checkout emerges as the most significant variable. Meanwhile, perceived cost and emotional ambivalence have no impact. The research also provides theoretical contributions and suggests future research for e-commerce companies and merchants. The theoretical contribution is how user emotions, user experience, merchant policies, and e-commerce regulation affect shopping cart abandonment. From the practical implications, e-commerce companies should focus on the user experience during checkout to reduce shopping cart abandonment.

Analysis of Factors that Influence Consumer Behavior towards Shopping Cart Abandonment in Online Shopping at Shopee

This research aims to identify and analyse factors that influence shopping cart abandonment behaviour when shopping on the Shopee marketplace. This research uses a purposive sampling technique of 100 active students in the Surabaya with the analytical method used in this research is multiple linear regression analysis. From the results of the analysis carried out, it was found that simultaneously (F test) the variables emotional ambivalence, hesitation at checkout, payment intention, choice overload, compare with website, perceived transaction inconvenience, perceived cost, and perceived risk had a significant effect on shopping cart abandonment behaviour. when shopping on the Shopee marketplace. Meanwhile, partial testing (t test) shows that choice overload is a variable that significantly influences shopping cart abandonment behaviour in online shopping at Shopee.

Assessing the Influence of Product Page Design on Purchasing Influence of Products in Online Marketplaces

In the era of e-commerce, online marketplaces have become indispensable platforms for businesses to reach a global audience. This study investigates the impact of product page design on purchasing influence within online marketplaces, focusing on the relationship between key design elements and consumer behavior. The research addresses a gap in understanding how layout, visual appeal, and the strategic placement of elements affect purchase intent and behavior. Employing a quantitative research design, the study sampled 186 online market consumers within Nairobi County in Kenya, across six major e-commerce platforms, including Amazon, Jumia, and Alibaba. Data were collected through structured questionnaires and analyzed using descriptive and inferential statistics. Key findings indicate that visually appealing designs, clear product information, and well-positioned call-to-action buttons significantly enhance user engagement and purchasing decisions. The study concludes with recommendations for optimizing online product pages to increase sales and reduce cart abandonment rates. Ethical considerations were adhered to throughout the research, ensuring participant confidentiality and data integrity. This research highlights the need for e-commerce platforms to prioritize user-centric design strategies that align with consumer preferences, driving better engagement and conversion rates.

Evaluating the ending‐9 pricing strategy along the online shopping funnel

Ending‐9 prices are extremely popular among retailers, leveraging consumers’ perception biases. However, despite the popularity of this pricing strategy, understanding of its impact on online retailers is still limited. This is particularly true given the complexity of online retail where consumers need to traverse a shopping funnel, consisting of decisions with shopping cart and purchases. This study aims to answer the following three questions: First, do consumers hold a perception bias toward prices with online retailers? Second, whether and how effective is this bias in shifting consumer decisions? Third, what is an alternative pricing strategy for online retailers, to better leverage consumers’ perception bias? The results of a structural model reveal the impact of a perception bias on consumer decisions, toward both the shopping cart and purchases, at the online retailer. However, while ending‐9 prices exert a sizable impact on shopping cart additions (by nearly 20%), the impact on final purchases is marginal (by less than 4%). A possible reason could be that even if each individual product adopts its ending‐9 price, the cost of the shopping cart (which can involve multiple items) might still not preserve such a pricing structure. Consequently, a firm's ending‐9 pricing strategy for each individual product cannot effectively induce consumers’ perception bias toward the cost of the shopping cart, leading to very limited carryover in lifts from shopping cart additions to purchases. Motivated by these observations, we consider an alternative strategy in which the online retailer adjusts the cost of the shopping cart to end in 9, in addition to its current ending‐9 pricing strategy for individual products. By doing so, the retailer can induce perception bias for both the shopping cart and purchases. Our simulation results suggest that such a strategy not only promotes purchases (by 16%) but also helps reduce shopping cart abandonment (by 3%), the latter of which has become a critical concern for many online retailers.

Understanding and Mitigating Cart Abandonment in E-commerce

Understanding and Mitigating Cart Abandonment in E-commerce

Linking Online Procrastination to Online Shopping Cart Abandonment : A Multi-Group Analysis from India and Ethiopia

Linking Online Procrastination to Online Shopping Cart Abandonment : A Multi-Group Analysis from India and Ethiopia

The dimensional impact of escapism on users’ eCart abandonment: mediating role of attitude towards online shopping

PurposeBy integrating uses and gratification theory (UGT) and online buying behavior theory (OBBT), this study aims to examine the impact of escapism motives (self-suppression and self-expansion) and attitude toward online shopping (ATS) on eCart abandonment. In addition, the mediating role of ATS between escapism motives and eCart abandonment is examined.Design/methodology/approachStructural equations modeling was performed on the data of 400 consumers using AMOS 26.FindingsThe results indicated that escapism motivations impacted users’ eCart abandonment, and the attitude toward online shopping mediated this relationship.Practical implicationsThe findings of this study imply that online sellers should understand the consumer motives for website use. In response, better strategies should be developed to reduce eCart abandonment.Originality/valueThis study extends knowledge of eCart abandonment by theoretical integration of UGT and OBBT and identification of the intrinsic predictors of virtual cart abandonment behavior. In addition, it is one of the early attempts to examine the dimensional impact of escapism on eCart abandonment.

Learning To Rank for E commerce Cart Optimization

In the competitive landscape of e-commerce, optimizing the shopping cart experience is crucial for enhancing customer satisfaction and boosting conversion rates. This paper explores the application of Learning to Rank (LTR) techniques to optimize e-commerce cart functionality. Learning to Rank, a subset of machine learning, involves training models to order items or features in a way that maximizes relevance based on user preferences. By employing LTR algorithms, e-commerce platforms can improve the relevance of product recommendations, streamline the checkout process, and tailor user interactions based on historical data and user behaviour. The study outlines the integration of LTR models into e-commerce systems, focusing on how these models can predict and prioritize products that users are more likely to purchase. This involves analysing user interactions, purchase history, and product attributes to develop ranking models that enhance the cart's efficiency and effectiveness. The research also addresses challenges such as data sparsity, dynamic user preferences, and the need for real-time updates, offering solutions and best practices for implementing LTR in practical settings. The results demonstrate that applying LTR techniques can significantly improve cart optimization by presenting users with more relevant product options, reducing cart abandonment rates, and increasing overall sales. This paper provides a comprehensive framework for e-commerce businesses seeking to leverage LTR for cart optimization, highlighting both theoretical insights and practical implications.

A conceptual model to imply a negative innovation assessment framework on consumer behaviors through the electronic business platforms

Online retail platforms significantly impact consumers' purchasing decisions. Satisfaction, purchase intent, and repeat online shopping drive the platform's purchasing decisions. In contrast, individuals do not purchase products due to dissatisfaction and lack of purchasing intent. It will cause hesitation and spread negative feedback to influence online consumer behaviors. This research proposes a conceptual model incorporating the Status Quo Bias (SQB) and the Negative Online Purchase Decision-Making Process (NOPDMP) to suggest a new framework for evaluating the maintained consumer behavior of online shopping platforms. The questionnaires following the proposed conceptual model were collected from the sample data from participants of 384 experienced respondents using online shopping platforms. Data were analyzed for the causal relationship using Structural Equation Model. The implications of the assessment framework that incorporates the influence of negative factors can weigh the decision to purchase products and improve and reduce shopping cart abandonment on e-commerce platforms. This framework can also describe instances of negative perspectives regarding incentive alignments with actual behaviors.

The Intention to Cart Abandonment in the Context of Multi-Channel Pricing

Theoretical background: Shopping cart abandonment is defined as a situation when the customer chooses products but does not complete the financial transaction. The vast majority of research articles on purchase abandonment concerns the online or mobile environment. The presented research model refers to the customer intention to resign from purchasing both in physical store and via mobile app caused by a multi-channel pricing strategy. By analogy to many definitions of online cart abandonment, the author defines cart abandonment in a multichannel environment as a decision about postponing purchase at all, both in a physical store and in a purchase mobile app. One of the possibilities of consumer behaviour as a reaction to the multi-channel pricing may be purchase abandonment. The impact of price differentiation across channels on purchase abandonment still deserves research attention due to the lack of the unequivocal confirmation. Purpose of the article: Setting prices in a multichannel environment creates a vital challenge for multichannel retailers. This article attempts to explain one of the undesirable consequences of the channel based price differentiation, which is the purchase abandonment. The purpose of this paper is to identify factors influencing the customer intention to abandon the purchase under channel-based price differentiation conditions (physical store and mobile purchase app). Research methods: This study is a quantitative one employing a scenario-based approach to obtain responses from 500 participants. This research used the structural equation modelling to test its hypotheses. Main findings: Findings reveal positive impact of perceived limited self-determination and perceived price unfairness on intention to cart abandonment, whereas consumer trust in a mobile app can reduce the intention to resign from purchase. Furthermore, the author finds the indirect impact of the mobile app familiarity as well as the retailer brand awareness. Research results can help managers to reduce the likelihood of losing customers in the multi-channel pricing environment.

The psychology of online shopping cart abandonment: a scrutiny of the current research framework and building an improved model of the online shopper journey

The psychology of online shopping cart abandonment: a scrutiny of the current research framework and building an improved model of the online shopper journey

Antecedents of Electronic Shopping Cart Abandonment during Online Purchase Process

The present study synthesized the extant literature on electronic shopping cart abandonment (ESCA) for the last 22 years (2000–2022) using the PRISMA approach. This is one of the first studies that comprehensively synthesized the widely applied theories in the ESCA literature and the reasons for ESCA during the various stages of online shopping process (search stage, consideration stage, evaluation stage, and purchase stage). The findings suggest that Stimulus Organism Response theory, Cognitive Dissonance theory, and the Theory of Reasoned Action are the most prominent theories used in the ESCA literature. Further, customers abandon the electronic shopping cart due to several personal factors (e.g., trust, experience), website features (e.g., perceived behavioral tracking), and product attributes (e.g., perceived service quality). This study gives a snapshot of knowledge gaps in the ESCA domain and suggests future research directions from multifarious perspectives i.e., theoretical underpinnings, contexts, and customer characteristics. For marketers, it provides insights on factors affecting ESCA at each stage of the online shopping process to develop stage wise pragmatic strategies like gamification on shopping websites, improving navigational aspects on websites, removing threats to customer privacy, and creating greater transparency to increase customer trust.

Online Shopping Cart Abandonment, A Worth Discussing Digitalization Phenomenon in Pakistani Cultural Context.

The purpose of this study is to find out such factors that influence shopping cart abandonment as it is comparatively new phenomena to search. Online shopping cart abandonment (OSCA) is basically regarding not implementation of consumer purchasing decision. Different variables from past researches are taken under consideration to check the relationship with OSCA. This review paper gives insights to authenticate the relationship by applying qualitative, quantitative or mix method research specifically in culture of Pakistan. According to the investigation of previous papers there are inconsistent results between perceived risk and OSCA sometimes positive and sometimes negative. Emotional ambivalence and hesitation at checkout have also positive relationship. Emotional ambivalence, entertainment shopping value, hesitation at checkout is positively corelated with OSCA. The mediation of hesitation at checkout between emotional ambivalence and OSCA reduces the impact. Design has negative relationship with OSCA. While examining the given framework results the managers of Pakistani Industry might be able to lessen the OSCA behaviour among customers. And take betterment in reducing OSCA to improve Pakistani economy by increasing sales and profits.