Cross-selling in customer service

textGiven the increasingly competitive environment characterizing many industries, customer service, specifically, post-sales technical support, has evolved as a key source of differentiation and profits. Against this backdrop, firms are looking to cross-sell products during customer service provision to generate revenue and transition their customer service operations from cost centers to profit centers. However, in the context of customer service, customers are contacting the firm about a product failure and not a purchase need, making cross-selling during customer service provision a challenging task. Essays 1 and 2 investigate which factors affect cross-sell outcomes in the customer service context. Essay 1 addresses the following questions: Do characteristics of the customer, customer service agent, and cross-sell offer influence cross-sell revenues? Cross-sell revenues are defined as the sales generated per customer in the customer service context. Using data on the cross-sell transactions of 6782 customers of a computer systems firm who contacted the firm for technical support, Essay 1 demonstrates that for risk-averse customers and customers who accept cross-sell goods (versus services) as the cross-sell offer, cross-sell revenues increase. However, when risk-averse customers accept a good (versus service) as the cross-sell offer, cross-sell revenues decrease. Surprisingly, for customers who own focal products with high functionality, cross-sell revenues decrease, and this effect becomes more negative as the customer service agent’s resolution ability increases. Essay 2 investigates cross-selling during customer service in an intercultural context and addressees the following question: What influences the likelihood of a cross-sell purchase during customer service by a customer in country X[subscript s] from a customer service agent in Country Y[subscript j]? Multinational firms offshore their customer service operations to a set of low-cost countries to reduce costs and gain access to specialized skills. Customer service agents in these countries provide technical problem resolution services to customers in a different set of countries, creating a cultural dyad between customers and customer service agents. Currently, such firms are asking their offshored customer service agents to cross-sell during customer service provision. Using data from a computer systems firm of 117,721 customer service encounters during which a cross-sell product was pitched, of which 3.6% resulted in a purchase, Essay 2 demonstrates both positive and negative effects of cultural distance on the likelihood of a customer making a cross-sell purchase during customer service. Specifically, Essay 2 shows that cultural distance (1) weakens the negative effect of agent resolution ability, (2) strengthens the positive effect of risk aversion, and (3) weakens the positive effect of failure severity on cross-sell purchase likelihood. I use the findings from both Essays 1 and 2 to generate implications for managers on how to improve cross-selling outcomes in their customer service operations.Marketin

sj-pdf-1-jmx-10.1177_00222429221148978 - Supplemental material for Understanding Customer Participation Dynamics: The Case of the Subscription Box

Supplemental material, sj-pdf-1-jmx-10.1177_00222429221148978 for Understanding Customer Participation Dynamics: The Case of the Subscription Box by Nita Umashankar, Kihyun Hannah Kim and Thomas Reutterer in Journal of Marketing</p

How and Why the Collaborative Consumption of Food Leads to Overpurchasing, Overconsumption, and Waste

Overconsuming and wasting food are disadvantageous for consumers and society as a whole and, therefore, are topics of great relevance. This research identifies food-based collaborative consumption (CC) as a hitherto unrecognized cause of overpurchasing, overconsuming, and wasting food. Food-based CC, which involves members of a group contributing to and taking from a collective pool of food, is a common social practice (e.g., potlucks) and a widely adopted format by the restaurant industry (e.g., family-style and tapas dining). Here, a combination of interviews, behavioral studies, and online experiments show that consumers purchase significantly more food per person in CC (vs. personal-consumption) group contexts, resulting in overconsumption and waste. This is shown to be the result of both generosity motives and cognitive errors (specifically, failing to account for the reciprocal nature of CC). However, inflated purchase amounts in CC contexts can be reduced (i.e., consumer well-being can be improved) by (i) having consumers explicitly focus on the amount they expect to take from others and (ii) providing anti-waste persuasive messages at the point-of-purchase

Acoustic surveillance of cough for detecting respiratory disease using artificial intelligence

Research question Can smartphones be used to detect individual and population-level changes in cough frequency that correlate with the incidence of coronavirus disease 2019 (COVID-19) and other respiratory infections? Methods This was a prospective cohort study carried out in Pamplona (Spain) between 2020 and 2021 using artificial intelligence cough detection software. Changes in cough frequency around the time of medical consultation were evaluated using a randomisation routine; significance was tested by comparing the distribution of cough frequencies to that obtained from a model of no difference. The correlation between changes of cough frequency and COVID-19 incidence was studied using an autoregressive moving average analysis, and its strength determined by calculating its autocorrelation function (ACF). Predictors for the regular use of the system were studied using a linear regression. Overall user experience was evaluated using a satisfaction questionnaire and through focused group discussions. Results We followed-up 616 participants and collected >62 000 coughs. Coughs per hour surged around the time cohort subjects sought medical care (difference +0.77 coughs·h−1; p=0.00001). There was a weak temporal correlation between aggregated coughs and the incidence of COVID-19 in the local population (ACF 0.43). Technical issues affected uptake and regular use of the system. Interpretation Artificial intelligence systems can detect changes in cough frequency that temporarily correlate with the onset of clinical disease at the individual level. A clearer correlation with population-level COVID-19 incidence, or other respiratory conditions, could be achieved with better penetration and compliance with cough monitoring