How risky is it to visit a supermarket during the pandemic?

We performed large-scale numerical simulations using a composite model to investigate the infection spread in a supermarket during a pandemic. The model is composed of the social force, purchasing strategy and infection transmission models. Specifically, we quantified the infection risk for customers while in a supermarket that depended on the number of customers, the purchase strategies and the physical layout of the supermarket. The ratio of new infections compared to sales efficiency (earned profit for customer purchases) was computed as a factor of customer density and social distance. Our results indicate that the social distance between customers is the primary factor influencing infection rate. Supermarket layout and purchasing strategy do not impact social distance and hence the spread of infection. Moreover, we found only a weak dependence of sales efficiency and customer density. We believe that our study will help to establish scientifically-based safety rules that will reduce the social price of supermarket business.

The impact of perceived brand interactivity on customer purchases. The mediating role of perceived brand fairness and the moderating role of brand involvement

Purpose This study aims to investigate the effect of perceived brand interactivity on customer purchases along with the mediating effect of perceived brand fairness. To increase the explanatory power of the model, this study also examines the moderating role of brand involvement. Design/methodology/approach An online survey was conducted to measure the constructs of interest. The direct, indirect (mediation) and conditional (moderation) effects were evaluated using linear regression, PROCESS Model 4 and PROCESS Model 59, respectively. Further, the Johnson Neyman (also called floodlight analysis) technique was used to probe the interaction terms. Findings The study results indicate that perceived brand interactivity directly and indirectly (via perceived brand fairness) impact customer purchases. The results also reveal that the positive impact of perceived brand interactivity on perceived brand fairness is greater when brand involvement is lower. In the same vein, the positive impact of perceived brand fairness on customer purchases is greater when brand involvement is lower. However, brand involvement does not moderate the impact of perceived brand involvement on customer purchases. Originality/value This study examines the effect of perceived brand interactivity on customer purchases (as a customer engagement behavior) while accounting for the mediating role of perceived brand fairness and the moderating role of brand involvement. The results provide noteworthy theoretical and managerial implications.

The Role of Time-Varying Contextual Factors in Latent Attrition Models for Customer Base Analysis

Context matters when modeling customer purchases and attrition in noncontractual settings.

The role of perceived firm social media interactivity in facilitating customer engagement behaviors

Purpose The purpose of this study is to examine how customers’ perceptions of brands’ social media interactivity impact customer engagement behaviors (CEBs) (e.g. customer purchases, referrals, influence and knowledge) while accounting for the moderating role of brand type and social media platform. Design/methodology/approach Two separate online surveys (Study 1 (N1) = 341, Study 2 (N2) = 183) were conducted to measure the constructs of interest. Regression analyzes tests research hypotheses; PROCESS Model 1 was used to test the moderating roles of brand type and platform. Further, the pick-a-point approach (i.e. spotlight analysis) was used to probe the interaction terms. Findings The results indicate that when customers perceive a brand to be highly interactive on social media (vs inactive), they are more willing to buy brand offerings, refer the brand in exchange for monetary incentives, inform their family and friends about the brand on social media and provide feedback and suggestions for improving the brand. Furthermore, the positive impact of perceived social media interactivity on customer purchases, referrals, influence and knowledge varies across brand and social media platform types. Research limitations/implications Online surveys using convenience samples were conducted to assess the constructs of interest. Archival data may provide an avenue for further insight. Future research may be able to track actual online customer behavior using such data. Further, researchers are encouraged to corroborate the results found here over time as the winds of social media shift to new platforms. Practical implications The results suggest that interacting on social media encourages customers to contribute to brand value directly (through purchasing) and/or indirectly (through referring, influencing and suggesting). While all brands may leverage social media activity for success, the positive impact of perceived social media interactivity on CEBs is particularly impactful for non-global 500 brands. The results also indicate that customers are more willing to add value to the brand through purchases and suggestions when they perceive the brand to be highly interactive on both social media networking sites and the brand’s website. However, they are more willing to promote this brand and influence their social networks about it only when they perceive the brand to be highly (vs less) interactive on its own website. Originality/value This study examines the novel issue of the impact of perceived social media interactivity on different CEBs while accounting for the moderating role of the brand and platform used by customers. The results provide value in better understanding the levers through which social media affects performance.

The Double-Edged Effects of E-Commerce Cart Retargeting: Does Retargeting Too Early Backfire?

Consumers often abandon e-commerce carts, so companies are shifting their online advertising budgets to immediate e-commerce cart retargeting (ECR). They presume that early reminder ads, relative to late ones, generate more click-throughs and web revisits. The authors develop a conceptual framework of the double-edged effects of ECR ads and empirically support it with a multistudy, multisetting design. Study 1 involves two field experiments on over 40,500 customers who are randomized to either receive an ECR ad via email and app channels (treatment) or not receive it (control) across different hourly blocks after cart abandonment. The authors find that customers who received an early ECR ad within 30 minutes to one hour after cart abandonment are less likely to make a purchase compared with the control. These findings reveal a causal negative incremental impact of immediate retargeting. In other words, delivering ECR ads too early can engender worse purchase rates than without delivering them, thus wasting online advertising budgets. By contrast, a late ECR ad received one to three days after cart abandonment has a positive incremental impact on customer purchases. In Study 2, another field experiment on 23,900 customers not only replicates the double-edged impact of ECR ads delivered by mobile short message service but also explores cart characteristics that amplify both the negative impact of early ECR ads and positive impact of late ECR ads. These findings offer novel insights into customer responses to online retargeted ads for researchers and managers alike.

Predicting customer behavior with Activation Loyalty per Period. From RFM to RFMAP

Objective:Identify a new model of predicting customer behavior based on new variables that can be used by marketing management and adapted to their business planning. Methodology: New model has been used, with the definition of new calculation systems of the traditional variables R, Recency, F, Frequency, and M, monetary value, (RFM), related to the business periods. Besides, activation in each period P becomes a key variable for constructing the purchase cohorts of customers and identifying their potential. A new variable, Activation Loyalty, is recognized as a good proxy of the likelihood of future customer purchases. The model builds a weighting through a multiple regression analysis obtaining β for each variable, including the periods of activation, presenting the relative effect of the variables, and the best global explanation of the model. Results: This new model, RFMAP, which includes Activation Periods and Activation Loyalty, presents a higher prediction accuracy and improvements over traditional models with a clear impact, useful and manageable lines of segmentation, and prioritization for marketing management in CRM systems. Limitations: The main limitation of this model consists that it is based on data of only one company, and it should show the value in other sectors and give a full insight through its transversal application. Practical implications: The involved advantages demonstrated better predictability and usefulness to decision-makers, not only to determine the best customers but also with lapsed ones. It gives a meaningful explanation of differences in customer behavior, which are present in the data and are being reflected in the model. Also, it provides a prescriptive prioritization of variables to be managed in the marketing plan and how to be implemented.

Segmentasi Konsumen Berdasarkan Model Recency, Frequency, Monetary dengan Metode K-Means

A good company is a company that is responsive to market changes and opportunities by utilizing existing data and information. Company data and information can come from internal or external sources. One of the internal data sources that can be utilized is customer data. This data will be used as the basis for determining customer segmentation. Segmentation is a process to determine customer characteristics with certain similarities, making it easier to extract information related to profitable customers. Customer business behavior can be seen from recency (last transaction period), frequency (number of transactions), and monetary (rupiah issued) or known as RFM analysis. The effective RFM analysis helps achieve the implementation of customer relationship management because this model is an important facility in measuring the profitability of customer value. To consider this RFM model, researchers use clustering which assumes that customers are in the same cluster, then consider customers with customers in the cluster. This clustering will display customer segmentation. This clustering method uses K-Means clustering. From the results of data processing, 3 clusters were formed from 25 customer data. Based on the clusters formed, it can be concluded that customer purchases have a different pattern. Clusters included in the segment of potential customers are cluster 1. Clusters are needed to get customers who previously had low R, high F, and high M values. While the strategy that needs to be improved is cluster 2.

Design and Implementation of a Smart Shopping Trolley Using RFID Technology

This paper focuses on the design and implementation of a Smart Trolley Shopping in supermarkets to solve difficulties of customers whilst waiting in queues for billing. The trolley is designed to develop market services and make them modern, healthy and easy to use. The remote controls the movement of the trolley automatically and reduces the load on the client during pulling the trolley. In addition, it helps in saving money by not buying unwanted products, with the help of the Liquid Crystal Display in the trolley, which shows on the update of purchase limit. In this work the client writes the amount they have via the keypad, where the amount appears on the liquid crystal screen. The product used is then checked for price and RFID details. This information is sent to RFID in the product via radio to RFID reader which determines the radio waves. It has an antenna bar for receiving and transmitting data. It also contains a small memory for detailed information of up to 256 bytes. The total cost is summarized by the scanner for materials stored in memory, sent to Arduino. The cart moves according to the client's movements when shopping and then moves to the left, right, forward, backward, or even stops through the buttons. If the customer purchases the products more than the amount recorded on the keyboard, an alarm will serve as a reminder to the customer that he/she has exceeded the purchase limit. The smart trolley is characterized by the speed of accounting compared to conventional accounting and provides a quality service. It reduces congestion at the cashier counter and shortens the time and waste of effort during the accounting process.