The Influence of Retailer Choices on Consumer Behaviors and Sales Productivity

The Influence of Retailer Choices on Consumer Behaviors and Sales Productivity

Giuseppe Russo, Maja Bozic, Ylenia Cavacece, Giuseppe Granata
DOI: 10.4018/978-1-5225-7856-7.ch007
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Abstract

The aim of this chapter is to analyze the most relevant factors affecting retailers by investigating the relationships between store type, assortment level, customers' purchases, and sales productivity. Analyzing the dataset of the German retailer Rossmann through classification and regression tools, this work investigates what store type customers visit more often, what kind of assortment they prefer, and how sales profitability is affected by internal and external factors. Results show a tendency from customers to shop in smaller neighborhood markets rather than in the large shopping centers with extensive assortments, determining an increase in sales productivity in smaller size stores. Results suggest managers developing strategies for creating multiple retail formats in order to meet the diverse customers' tendencies in the today's market.
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Introduction

The 2008 financial and economic crisis led to a reduction in consumption that affected retail sales. Consumers have become more rational in purchasing, actively seeking the best offerings in order to save money. For retailers it is more and more difficult to predict consumers' purchasing behaviors, to be able to satisfy them and gain customers’ trust and loyalty. Consumers spend time looking for the store that offers more advantages for a product, instead of making all their choices in the same store. In view of these significant changes, it becomes essential for retailers to identify which factors influence consumers' purchasing behaviors in order to plan their store strategies and increase sales productivity. The actual competitive retail environment is characterized by a growing heterogeneity of demand and by the proliferation of new retail formats, determining cross shopping behaviors by consumers - consumers change from a store to another according to their purchase needs and the attributes of each store (Bustos-Reyes and González-Benito, 2008). Consumers may switch on and off shopping mood without necessary explanation and avert.

The uncertainty of consumer preferences is difficult to predict. Investigating and then predicting the causality between the competition, assortment size, promotions, and sales productivity may give the clue for a retail manager what a tendency of consumers is and whether they will be faithful to the chosen store and its assortment.

Prior marketing literature focused on the role of the assortment size to define consumer’s choice of a retailer although providing opposite findings. According to Broniarczyk et al. (1998), when choosing among assortments, consumers prefer the variety offered by larger assortments. Reduction of the category assortments appears to have little or no negative impact on sales; however, it could determine a loss of the store visits (Fox & Sethuraman, 2010). Other works, instead, show that consumers prefer smaller assortments because they are less confident in making choices when the assortment is larger (Chernev 2006, 2003a, 2003b; Iyengar & Lepper, 2000). This confusion is reflected in the trend of large retailers to use multiple retail formats in order to satisfy the different consumers' preferences (Reutterer & Teller, 2009; Ruiz-Real et al., 2016).

The aim of this work is to investigate the influence of assortment sizes and store type on consumers’ purchasing behaviors, as well as the influence of internal and external factors on sales productivity. Using the data of a retail chain drug stores, this chapter investigates how assortment size and store type influence consumers’ choices and what external factors - such as competition distance and school holidays - or internal ones - such as promotional strategies - influence sales productivity.

Modelling approaches for store planning are often based on demand forecasts. Usually, choice models are used to estimate demand based on actual customer behavior approaches (Borin & Farris, 1995; Borin et al., 1994). This work adopts a multiple method based on a mix of classification and regression tools to analyze secondary data of a drug retailer.

The chapter is organized as follows: firstly, the literature background regarding the relationships between store type, assortment size, customers’ visits, retail environment and sales productivity is analyzed; secondly, the research hypotheses have been tested through statistical analyses of the Rossmann retail data; thirdly, the results have been discussed proposing the related solutions and recommendations; finally, the work ends with the conclusions, implications, limitations and emerging future research directions.

Key Terms in this Chapter

Retail Park: Unenclosed complex retail format of big and small retailers with a surface area from 20,000-55,000 sqm (in the chapter: the drug store located in a retail park with net sales area 500-1000 sqm).

Sales Productivity: Sales per unit area – the effective measure of generating store’s revenue using the available amount of sales space.

Preference: Customer’s attitude towards a set of goods or services reflected in a decision-making process.

Store’s Visit: The traffic of customers inside the store.

Classification Method: A model that yields optimal discrimination between several classes in terms of predictive performance.

Assortment: A display of goods or services that a retailer provides to the customers.

Shopping Center: Large retail format of interconnected shops that enables the customer to walk from one to another. Net sales area: 500 - 1000 sqm.

Neighborhood Market: A store adapted to satisfy the needs and wants of local surroundings. Net sales area: 200-800 sqm.

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