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Author: Marat Ibragimov
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
Online retailers are challenged by frequent product returns. High return rates significantly decrease companies' profit which makes the issue of managing product returns very important from the practical standpoint. Typically, practitioners study returns in connection with purchase decisions or as a part of customer behavior/type. In this paper, we show that the events which precede the purchase decision are related to the return decision. Generally, this information is readily available to online retailers and thus provides a low-cost opportunity to better understand and predict the product returns.
Author: Marat Ibragimov
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
Online retailers are challenged by frequent product returns. High return rates significantly decrease companies' profit which makes the issue of managing product returns very important from the practical standpoint. Typically, practitioners study returns in connection with purchase decisions or as a part of customer behavior/type. In this paper, we show that the events which precede the purchase decision are related to the return decision. Generally, this information is readily available to online retailers and thus provides a low-cost opportunity to better understand and predict the product returns.
Author: Marat Ibragimov (Management expert)
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
In Chapter 1, I and coauthors study the problem of predicting the product return rate using the products' visual information. In online channels, products are returned at high rates. Shipping, processing, and refurbishing are so costly that a retailer's profit is extremely sensitive to return rates. Using a large dataset from a European apparel retailer, we observe that return rates for fashion items bought online range from 13% to 96%, with an average of 53% - many items are not profitable. Because fashion seasons are over before sufficient data on return rates are observed, retailers need to anticipate each item's return rate prior to launch. We use product images and traditional measures available prelaunch to predict individual item return rates and decide whether to include the item in the retailer's assortment. We complement machine-based prediction with automatically extracted image-based interpretable features. Insights suggest how to select and design fashion items that are less likely to be returned. Our illustrative machine-learning models predict well and provide face-valid interpretations - the focal retailer can improve profit by 8.3% and identify items with features less likely to be returned. We demonstrate that other machine-learning models do almost as well, reinforcing the value of using prelaunch images to manage returns. In Chapter 2, I consider customer search and product returns on the individual level. Previous research has focused on linking customers' purchase and return decisions. However, online retailers have access to the information which precedes the purchase decision -- customer search. I demonstrate that customer search information provides important insights about product returns. Using data from a large European apparel retailer, I propose and estimate a joint model of customer search, purchase, and return decisions. I then provide theory and data indicating that using search filters, viewing multiple colors of a product, spending more time, and purchasing the last item searched are negatively associated with the probability of a return. Finally, I use the proposed model to optimize the product display order on the retailer's website. Chapter 3 extends and reinforces the results obtained from previous Chapters. In the paper, I study the assortment planning problem in presence of frequent product returns. I develop a deep-learning model of customer search, purchase, and return. The model is based on a transformer framework and allows the recovery of important relations in the data. I use the estimated model to demonstrate that retailers could identify successful and unsuccessful products and modify the assortment. The modified assortment would increase the retailer's sales and at the same time decrease returns. Lastly, I provide qualitative insights on which products are most likely to be unsuccessful in online retail.
Author: Jisu Cao
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
Product returns are one of the most significant pain points of the retail industry, especially for online retailers. Two key priorities in managing product returns are to reduce product returns and to better handle product returns, as processing returns incurs substantial costs, and poorly handled product returns can hurt customer loyalty and lead to lost future revenue. Based on 4.3 million purchase and return records from a quarter million representative customers, we present a causal analysis of whether and how fast delivery affects product returns and fast return-handling affects customer retention. We exploited a natural experiment of the opening of a new fulfillment center by a large e-commerce platform in China which significantly reduced the delivery time and return-handling time of serving nearby customers but had little impact on those further away customers. On product delivery, we find that a 10% improvement in delivery speed lowers the average product return rate from 14.37% to 13.50%. The rich purchase data also allowed us to provide corroborating evidence in support of the competition mechanism as a potential explanation for this effect: a longer delivery time may encourage consumers to reconsider their purchased item and opt for a cheaper alternative. On return handling, we find that a 10% improvement in return-handling speed leads to a remarkable 23.96% increase in the monetary value of the customer's next purchase. This accelerated return-handling not only allows customers to receive their refunds faster so that they have budget for future purchases, but also significantly enhances customer satisfaction. Our study represents the first attempt to causally examine the benefits of fast delivery and return handling from a product return and customer retention perspective and offers valuable insights for online retailers seeking to enhance their service quality and optimize customer satisfaction.
Author: Robert W. Palmatier
Publisher: Springer
ISBN: 3319619853
Category : Business & Economics
Languages : en
Pages : 332
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Book Description
This book provides a synthesis of research perspectives on customer engagement through a collection of chapters from thought leaders. It identifies cutting-edge metrics for capturing and measuring customer engagement and highlights best practices in implementing customer engagement marketing strategies. Responding to the rapidly changing business landscape where consumers are more connected, accessible, and informed than ever before, many firms are investing in customer engagement marketing. The book will appeal to academics, practitioners, consultants, and managers looking to improve customer engagement.
Author: Peter S.H. Leeflang
Publisher: Springer Science & Business Media
ISBN: 146154050X
Category : Business & Economics
Languages : en
Pages : 642
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Book Description
This book is about marketing models and the process of model building. Our primary focus is on models that can be used by managers to support marketing decisions. It has long been known that simple models usually outperform judgments in predicting outcomes in a wide variety of contexts. For example, models of judgments tend to provide better forecasts of the outcomes than the judgments themselves (because the model eliminates the noise in judgments). And since judgments never fully reflect the complexities of the many forces that influence outcomes, it is easy to see why models of actual outcomes should be very attractive to (marketing) decision makers. Thus, appropriately constructed models can provide insights about structural relations between marketing variables. Since models explicate the relations, both the process of model building and the model that ultimately results can improve the quality of marketing decisions. Managers often use rules of thumb for decisions. For example, a brand manager will have defined a specific set of alternative brands as the competitive set within a product category. Usually this set is based on perceived similarities in brand characteristics, advertising messages, etc. If a new marketing initiative occurs for one of the other brands, the brand manager will have a strong inclination to react. The reaction is partly based on the manager's desire to maintain some competitive parity in the mar keting variables.
Author: Nachiketa Sahoo
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
Although many researchers in Information Systems and Marketing have studied the effect of product reviews on sales, few have looked at their effect on product returns. We hypothesize that, by reducing product uncertainty, product reviews affect the probability of product returns. We elaborate this hypothesis starting with an analytical model that examines how changes in valence and precision of information from product reviews influence the purchase and return probabilities of risk-averse, but rational, consumers. We then empirically test our hypotheses using a transaction level dataset from a multi-channel, multi-brand North American specialty retailer. Harnessing different consumers' purchases and returns of the same products, but with varying sets of product reviews over two years, we show that the availability of more reviews and the presence of more 'helpful' reviews, as voted by consumers, lead to fewer product returns -- after controlling for customer, product and other context-related factors. Analyzing the purchase behavior of the consumers, we find that when fewer product reviews are available, consumers buy more substitutes in conjunction with a product, potentially to mitigate their uncertainty. Purchase of substitutes, in turn, leads to more product returns. Finally, leveraging a discontinuity in the displayed average ratings, we find that when products are shown with an average rating that is higher than the true rating they are returned more often. These results support the predictions of our theoretical model -- unbiased online reviews indeed help consumers make better purchase decisions leading to lower product returns; biasing reviews upwards results in more returns. The presence of online reviews has important cost implications for the firm beyond the cost of reprocessing the returns; we observe that when consumers return products they are more likely to write online reviews and these reviews are more negative than reviews that follow a non-returned purchase.
Author: Edward L. Nash
Publisher: McGraw-Hill Companies
ISBN:
Category : Business & Economics
Languages : en
Pages : 872
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Book Description
Author: Christopher Woodruff, David McKenzie, Suresh de Mel
Publisher: World Bank Publications
ISBN:
Category :
Languages : en
Pages : 37
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Book Description
Abstract: Small and informal firms account for a large share of employment in developing countries. The rapid expansion of microfinance services is based on the belief that these firms have productive investment opportunities and can enjoy high returns to capital if given the opportunity. However, measuring the return to capital is complicated by unobserved factors such as entrepreneurial ability and demand shocks, which are likely to be correlated with capital stock. The authors use a randomized experiment to overcome this problem and to measure the return to capital for the average microenterprise in their sample, regardless of whether they apply for credit. They accomplish this by providing cash and equipment grants to small firms in Sri Lanka, and measuring the increase in profits arising from this exogenous (positive) shock to capital stock. After controlling for possible spillover effects, the authors find the average real return to capital to be 5.7 percent a month, substantially higher than the market interest rate. They then examine the heterogeneity of treatment effects to explore whether missing credit markets or missing insurance markets are the most likely cause of the high returns. Returns are found to vary with entrepreneurial ability and with measures of other sources of cash within the household, but not to vary with risk aversion or uncertainty.
Author: Necmi K. Avkiran
Publisher: Springer
ISBN: 3319716913
Category : Business & Economics
Languages : en
Pages : 243
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Book Description
This book pulls together robust practices in Partial Least Squares Structural Equation Modeling (PLS-SEM) from other disciplines and shows how they can be used in the area of Banking and Finance. In terms of empirical analysis techniques, Banking and Finance is a conservative discipline. As such, this book will raise awareness of the potential of PLS-SEM for application in various contexts. PLS-SEM is a non-parametric approach designed to maximize explained variance in latent constructs. Latent constructs are directly unobservable phenomena such as customer service quality and managerial competence. Explained variance refers to the extent we can predict, say, customer service quality, by examining other theoretically related latent constructs such as conduct of staff and communication skills. Examples of latent constructs at the microeconomic level include customer service quality, managerial effectiveness, perception of market leadership, etc.; macroeconomic-level latent constructs would be found in contagion of systemic risk from one financial sector to another, herd behavior among fund managers, risk tolerance in financial markets, etc. Behavioral Finance is bound to provide a wealth of opportunities for applying PLS-SEM. The book is designed to expose robust processes in application of PLS-SEM, including use of various software packages and codes, including R. PLS-SEM is already a popular tool in marketing and management information systems used to explain latent constructs. Until now, PLS-SEM has not enjoyed a wide acceptance in Banking and Finance. Based on recent research developments, this book represents the first collection of PLS-SEM applications in Banking and Finance. This book will serve as a reference book for those researchers keen on adopting PLS-SEM to explain latent constructs in Banking and Finance.
Author: Michele Samorani
Publisher:
ISBN:
Category :
Languages : en
Pages : 41
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Book Description
The return of a product is often one of a series of transactions that a consumer undertakes in search of a good. Recognizing this, we analyze returns as part of a product search process: Upon returning a product, consumers may immediately purchase an alternative one, which they may later replace with another product, and so on, until they either ultimately keep their last purchase (Keep outcome) or not (No-keep outcome). We call such a sequence of transactions a product return episode. In this work, we study consumer Keep and return abuse behavior using episodic metrics. Using data from a consumer electronics retailer, we show that analysis of product returns with episodic metrics provides insights that differ from, and go beyond, analyses with commonly-used transactional metrics. We find that although higher average price and larger store assortment at a subcategory level both tend to increase the return probability, they also increase the probability of keeping a product at the end of an episode, which points to profit-improving opportunities for retailers by allowing returns and tracking episodes. We also find that episodic metrics are useful for identifying return abuse.
