Essays on multichannel marketing

Multichannel marketing is the practice of simultaneously offering information, goods, services, and support to customers through two or more synchronized channels. In this dissertation, I develop an integrated framework of multichannel marketing and develop models to assist managers in their marketing resource allocation decisions. In the first essay of the dissertation, I investigate the factors that drive customers multichannel shopping behavior and identify its consequences for retailers. In the second essay, I build on this work and develop a model that enables firms to optimize their allocation of marketing resources across different customer-channel segments. In the first essay, I develop a framework comprising the factors that drive consumers’ channel choice, the consequences of channel choice, and their implications for managing channel equity. The results show that customer-channel choice is driven in a nonlinear fashion by a customer demographic variable such as age and is also influenced by consumer shopping traits such as number of categories bought and the duration of relationship with a retailer. I show that by controlling for the moderating effects of channel-category associations, the influence of customers’ demographics and shopping traits on their channel choices can vary significantly across product categories. Importantly, the results show that multichannel shoppers buy more often, buy more items, and spend considerably more than single channel shoppers. The channel equity of multichannel customers is nearly twice that of the closest single channel customers (online or offline). In the second essay, I propose a model for optimal allocation of marketing efforts across multiple customer-channel segments. I first develop a set of models for consumer response to marketing efforts for each channel-customer segment. This set comprises four models, the first for purchase frequency, the second for purchase quantity, the third for product return behavior, and the fourth for contribution margin of purchase. The results show that customers’ responses to firm marketing efforts vary significantly across the customer-channel segments. They also suggest that marketing efforts influence purchase frequency, purchase quantity and monetary value in different ways. The resource allocation results show that profits can be substantially improved by reallocating marketing efforts across the different customer-channel segments

Comportamento do Consumidor em Canais Cruzados: Modelo de Mediação-Moderada nas Compras Online/Offline

As novas tecnologias móveis com acesso à internet têm propiciado o surgimento de um novo processo de compra dos consumidores. Esse processo influencia tanto as compras online quanto as offline (em lojas físicas), a depender do produto a ser adquirido. Teorias de aprendizagem comportamental, como as relações entre precorrentes e correntes, podem explicar esse novo repertório comportamental. O presente estudo testou a mediação do Comportamento em Canais Cruzados (CCC) na relação entre a adoção de dispositivos móveis com acesso à internet e a frequência de compra nos canais online e offline, moderada pelo tipo de bem (durável versus não durável). Com delineamento quase experimental, os dados foram analisados por Modelagem de Equação Estrutural. Os resultados demonstram que a adoção de tecnologias móveis com internet incentivou as dimensões do CCC (busca de informação simultânea, comparação de produtos e preços, e interação com o varejista/fabricante), com maior força para bens não duráveis, e que cada dimensão do CCC altera a frequência de compras online e offline, porém, o efeito específico depende do tipo do bem. A pesquisa analisa o processo de adoção de novas tecnologias geradoras destes novos comportamentos, e que os mesmos incentivam a frequência de compra

Essays on multichannel marketing

Multichannel marketing is the practice of simultaneously offering information, goods, services, and support to customers through two or more synchronized channels. In this dissertation, I develop an integrated framework of multichannel marketing and develop models to assist managers in their marketing resource allocation decisions. In the first essay of the dissertation, I investigate the factors that drive customers multichannel shopping behavior and identify its consequences for retailers. In the second essay, I build on this work and develop a model that enables firms to optimize their allocation of marketing resources across different customer-channel segments. In the first essay, I develop a framework comprising the factors that drive consumers’ channel choice, the consequences of channel choice, and their implications for managing channel equity. The results show that customer-channel choice is driven in a nonlinear fashion by a customer demographic variable such as age and is also influenced by consumer shopping traits such as number of categories bought and the duration of relationship with a retailer. I show that by controlling for the moderating effects of channel-category associations, the influence of customers’ demographics and shopping traits on their channel choices can vary significantly across product categories. Importantly, the results show that multichannel shoppers buy more often, buy more items, and spend considerably more than single channel shoppers. The channel equity of multichannel customers is nearly twice that of the closest single channel customers (online or offline). In the second essay, I propose a model for optimal allocation of marketing efforts across multiple customer-channel segments. I first develop a set of models for consumer response to marketing efforts for each channel-customer segment. This set comprises four models, the first for purchase frequency, the second for purchase quantity, the third for product return behavior, and the fourth for contribution margin of purchase. The results show that customers’ responses to firm marketing efforts vary significantly across the customer-channel segments. They also suggest that marketing efforts influence purchase frequency, purchase quantity and monetary value in different ways. The resource allocation results show that profits can be substantially improved by reallocating marketing efforts across the different customer-channel segments

Models for purchase frequency

Purchase frequency modeling began with the pioneering work of Ehrenberg [Ehrenberg, A.S.C., 1959. The pattern of consumer purchases. Applied Statistics 8, 26-41]. This note provides an extension of this work. A collection of some seventeen flexible distributions is discussed for purchase frequency modeling. The corresponding estimation procedures are derived by the method of moments and the method of maximum likelihood. An application is illustrated to a consumer purchasing data used by Ehrenberg.Maximum likelihood Method of moments Mixture model Purchase frequency modeling