Competition between Private Labels and National Brands in a Multichannel Retailer

This chapter analyzes private label and national brand competition across online and offline channels. We analyze competition using three measures: market share, a loyalty index, and what is called in the literature conquesting power (a measure of the ability of a brand to capture nonloyal consumers). We first provide a brief theoretical introduction and literature research about the topic. We also do an empirical analysis using data of a multichannel grocery retailer that sells both its own private label and national brands, through physical stores and an online store. The data include the purchases made by a sample of multichannel consumers. We find that the private label increases, in general, its competitive position in the online channel, compared to the offline channel. However, this result does not hold for all the product categories. We discuss some drivers of this general improvement, as well as potential causes for the differences between categories. We conclude with some recommendations for multichannel retailers and manufacturers

Online reviews and product sales: the role of review visibility

When studying the impact of online reviews on product sales, previous scholars have usually assumed that every review for a product has the same probability of being viewed by consumers. However, decision-making and information processing theories underline that the accessibility of information plays a role in consumer decision-making. We incorporate the notion of review visibility to study the relationship between online reviews and product sales, which is proxied by sales rank information, studying three different cases: (1) when every online review isassumed to have the same probability of being viewed; (2) when we assume that consumers sort online reviews by the most helpful mechanism; and (3) when we assume that consumers sort online reviews by the most recent mechanism. Review non-textual and textual variables are analyzed. The empirical analysis is conducted using a panel of 119 cosmetic products over a period of nine weeks. Using the system generalized method of moments (system GMM) method for dynamic models of panel data, our findings reveal that review variables influence product sales, but the magnitude, and even the direction of the effect, vary amongst visibility cases. Overall, the characteristics of the most helpful reviews have a higher impact on sales.This work was supported by the Spanish Ministry of Science and Innovation grant number ECO2015-65393-

An empirical analysis of shopping behavior across online and offline channels for grocery products: the moderating effects of household and product characteristics

We study the moderating effects of household (e.g., shopping frequency) and product (e.g., sensory nature) characteristics on household brand loyalty, size loyalty and price sensitivity across online and offline channels for grocery products. We analyze the shopping behavior of the same households that shop interchangeably in the online and offline stores of the same grocery chain in 93 categories of food, nonfood, sensory and nonsensory products. We find that households are more brand loyal, more size loyal but less price sensitive in the online channel than in the offline channel. Brand loyalty, size loyalty and price sensitivity are closely related to household and product characteristics. Light online shoppers exhibit the highest brand and size loyalties, but the lowest price sensitivity in the online channel. Heavy online shoppers display the lowest brand and size loyalties, but the highest price sensitivity in the online channel. Moderate online shoppers exhibit the highest price sensitivity in the offline channel. The online-offline differences in brand loyalty and price sensitivity are largest for light online shoppers and smallest for heavy online shoppers. The online-offline differences in brand loyalty, size loyalty and price sensitivity are larger for food products and for sensory products.This project is partially supported by the Singapore Ministry of Education Research Project R-317-000- 073-113 and the Government of Navarre and the Spanish Ministry of Science Research Project SEC2002- 04321-C02-02

Mining the text of online consumer reviews to analyze brand image and brand positioning

The growth of the Internet has led to massive availability of online consumer reviews. So far, papers studying online reviews have mainly analysed how non-textual features, such as ratings and volume, influence different types of consumer behavior, such as information adoption decisions or product choices. However, little attention has been paid to examining the textual aspects of online reviews in order to study brand image and brand positioning. The text analysis of online reviews inevitably raises the concept of 'text mining'; that is, the process of extracting useful and meaningful information from unstructured text. This research proposes an unified, structured and easy-to-implement procedure for the text analysis of online reviews with the ultimate goal of studying brand image and brand positioning. The text mining analysis is based on a lexicon-based approach, the Linguistic Inquiry and Word Count (Pennebaker et al., 2007), which provides the researcher with insights into emotional and psychological brand associations.This work was supported by the Spanish Ministry of Economy, Industry and Competitivity [grant number: ECO2015-65393-R] and by the Government of Spain Ministry of Science, Innovation and Universities Grant numbers: PID2019-108554RB-I00