Retail Futures

The Good, the Bad and the Ugly of the Digital Transformation

Eleonora Pantano, Eleonora Pantano

• Publisher: Emerald Publishing Limited
• Year: 2020
• ISBN:
  9781838676650
• Topic: Betriebswirtschaft
• Subtopic: Marketingforschung

Retail Futures presents a comprehensive collection of new theory, original empirical evidence, and applied case studies synthesizing the emerging contributions in innovation and technology management for the retailing sector. Eleonora Pantano presents readers with an accessible and wide ranging collection of chapters aimed at clearly identifying the challenges retailers have to face in response to innovative new practices, while suggesting how the sector can respond to the technological developments.
The book analyses theories, frameworks and guidelines for successfully managing innovation in retailing, empirical research on retailers and consumer behavior when facing innovation in retail settings, ethical considerations and privacy issues, and case studies of retailers and innovation.
Retail Futures is primarily aimed at academic researchers studying retailing (including internet and e- retailing), as well as upper level students who want to understand this phenomenon. In addition, the book is useful for practitioners who are experiencing the dramatic effects of new and smart technologies on their retail strategies. This work provides a strong collection of theories, empirical evidence, and case study applications synthesizing the emerging studies on the innovation and technology management for retailing in an accessible way.

Section 1

Theoretical and Technological Background

Chapter 1

How Innovative Technology Serves the Retailer: A Store Sales Cycle Model

Tibert Verhagen and Jesse Weltevreden

Abstract

In an increasingly technology-driven retail landscape, retailers face the challenge of making the most effective decisions regarding the selection and use of innovative technology. Although previous research provides insights into the added value of technology, it does not directly guide retailers in overviewing and selecting technology that supports their sales operations. This chapter contributes to the field of retail technology studies by introducing a sales-oriented model intended to assist retailers in inventorying available technologies and making decisions regarding the selection and use of these technologies for their physical stores. The model uses an updated version of the seven steps of selling as a foundation and, in line with the resource life cycle, decision support system and self-service technology literature streams, proposes applying technology in such a way that it supports the stages of the retailer's sales process. This chapter concludes with a discussion of practical guidelines for applying the model.

Keywords: Retail technology; sales; sales decision support; retailing; store innovation; technology selection

Learning Outcomes

• Recognise that retailers need guidance in overviewing and selecting emerging digital technologies.
• Understand the role and value of emerging digital technologies in enhancing the effectiveness of in-store sales efforts.
• Understand and describe the conceptualisation of the store as a sales decision support system.
• Make use of the introduced store sales cycle model (SSCM) to help retailers inventory and select the most effective available digital technologies.

Introduction

As a result of online competition and changing consumer behaviour in the late 2010s, retail sales have become increasingly erratic and have generated generally low profit margins, which has led many physical stores to go bankrupt (Adhi, Burns, Davis, Lal, & Mutell, 2019). At the same time, driven by rapid advancements in technology (Pantano & Vannucci, 2019) and an increasing demand for and use of technology across generations (Foroudi, Gupta, Sivarajah, & Broderick, 2018), a growing number of retailers have adopted technologies to attract store visitors (e.g., location-based marketing, store window displays, loyalty apps), provide them with an enhanced shopping experience (e.g., smart dressing room, 3D mirror, robotics) and facilitate actual purchase of goods or services (e.g., digital shopping assistant, digital ticketing, mobile payments). To help retailers understand the value of emerging technologies, researchers have begun investigating the effects of technologies in physical retail settings. Except for a few studies that adopt a retailer's perspective (e.g., Inman & Nikolova, 2017; Renko & Druzijanic, 2014), however, the majority of extant studies adopt a consumer behaviour perspective; that is, they have categorised technologies in terms of their value and/or stage in the purchase decision process (e.g., Willems, Smolders, Brengman, Luyten, & Schöning, 2018), they have connected the use of technology with observable behavioural outcomes (e.g., Roggeveen, Nordfält, & Grewal, 2016) or they have examined how consumers perceive technology and how these perceptions translate into behavioural outcomes (e.g., Adapa, Fazal-e-Hasan, Makam, Azeem & Mortimer, 2020; Garaus, Wagner, & Manzinger, 2017).

Although the academic contributions of these studies are undisputable, their explicit focus on consumer behaviour implies that they cannot directly guide retailers in overviewing and selecting technologies that support their primary activities – that is, selling products to consumers. The relevance of such pragmatic retailer-focused guidance is echoed in the work of Edelman and Singer (2015), who introduce what they refer to as a ‘fresh way of thinking’. Instead of reactively anticipating consumers’ next moves by positioning themselves in the decision-making journey that consumer themselves design, retailers should adapt their thinking and focus more on using emerging technologies to shape and innovate consumers' buying process to be more in line with their own sales and marketing interests (Edelman & Singer, 2015). As such, in this chapter, we introduce a practice-oriented model intended to assist retailers in inventorying available technologies and making decisions regarding the selection and use of these technologies for their physical stores. The model, which we term the SSCM, draws on the concepts of customers' resource life cycle (Ives & Learmonth, 1984), customer decision support systems (O'Keefe & McEachern, 1998) and self-service technology (SST) (Meuter, Ostrom, Roundtree, & Bitner, 2000). The model uses an adapted version of the seven steps of selling (Dubinsky, 1980) as a foundation and maps possible technologies onto each of the seven steps. The model not only provides retailers with a framework that they can use to understand and choose technology but also serves the overarching purpose of advocating the use of technology in retail settings not as a goal per se but rather as cog in the overall sales machine.

In the remainder of this chapter, we first consider the conceptual background of the model by examining key concepts from the sales and decision support system literature. Then, using the literature and input obtained from an expert panel, we introduce the SSCM. We elaborate on the model, suggest guidelines for using it and conclude with limitations and recommendations for future research.

Conceptual Background

The Sales Process

Since the beginning of the 20th century, researchers and practitioners have sought to understand the process salespeople go through when selling to customers. One of the most widely accepted and well-cited frameworks discussing this process is the ‘seven steps of selling’ (Moncrief & Marshall, 2005), as introduced by Dubinsky (1980). In this framework, the sales process consists of (1) locating and prospecting customers, (2) collecting information about the prospects, (3) contacting prospects and triggering interest, (4) presenting the sales offering, (5) removing any sales objections/resistance, (6) closing the sale and (7) engaging in postsale follow-up. Although some works slightly adapt the conceptualisation, wording and composition of the seven steps, their essence still holds today and is dominant in sales theory (Moncrief & Marshall, 2005) and in most sales textbooks (Borg & Young, 2014).

As part of the conceptualisation of the sales process, researchers have addressed the evolution of various selling approaches, also referred to as sales strategies (Paesbrugghe, Rangarajan, Sharma, Syam, & Jha, 2017). A rather monadic transactional approach was introduced in the early 1900s, in which the primary objective of selling was to persuade customers to buy the products offered (Borg & Young, 2014; Scott, Avila, & Talbert, 2019). In the 1980s (Moncrief, 2017), a dyadic relationship selling strategy began to gain traction (see, e.g., Spiro, Perreault, & Reynolds, 1977). The main objective of relationship selling is to become a trustworthy preferred partner, rather than a one-time supplier, by building long-term customer relationships that are beneficial to both parties engaged (Scott et al., 2019). Subsequently, alternative selling strategies rooted in relationship selling have emerged, of which adaptive selling and solution selling are the most widely mentioned in the literature (Arli, Bauer, & Palmatier, 2018; Paesbrugghe et al., 2017). Whereas adaptive selling entails ‘the altering of sales behaviours during customer interaction or across customer interactions based on perceived information about the nature of the selling situation’ (Weitz, Suhan & Sujan, 1986, p. 175), solution selling, also referred to as problem-solving selling or consultative selling, involves the salesperson working with the customer as an adviser to identify needs and devise customer-centred solutions (Moncrief & Marshall, 2005).

Although the seven steps of selling and sales strategies are grounded in research and practice today, a consensus in the sales literature is that future evolution and effectiveness of the sales process and techniques will largely depend on the extent to which salespeople are capable of adopting and using emerging technologies such as mobile devices, social media, artificial intelligence and data analytics (Herjanto & Franklin, 2019; Román, Rodríguez, & Jaramillo, 2018; Schrock, Zhao, Hughes, & Richards, 2016). These technologies have been touted for their potential to more effectively identify customer wants (Trainor, 2012), provide more and better information about customers (Román & Rodríguez, 2015) and offer improved capabilities to create and maintain relationships with customers (Trainor, 2012). As such, these technologies increasingly will determine how salespeople connect and interact with customers, apply selling techniques and build relationships – that is, how they go through the seven steps of selling (Marshall, Moncrief, Rudd, & Lee, 2012).

The Store as Sales Decision Support System

In addition to the sales field, the information systems and marketing literature streams have addressed the influence of emerging technologies in sellers' and buyers' processes. In information systems research, Ives and Learmonth (1984) introduce the so-called customer resource life cycle. Basically, this cycle illustrates how suppliers can use technology to service the stages of their customers' decision-making process, which helps them differentiate themselves from competitors and build returning business. The life cycle view on using technology has been echoed in multiple follow-up studies, which confirm the advantages of supporting customers' online decision processes with technological functions and features, as customers can use these aids themselves to arrive at purchase decisions, which makes it a rather effective, competitive way of selling (Cenfetelli, Banbasat & Al-Natour, 2008; Cenfetelli & Benbasat, 2002; Piccoli, Brohman, Watson, & Parasuraman, 2004). O'Keefe and McEachern's (1998) seminal work draws comparable conclusions, adopting a decision support system perspective of websites to study online shopping. In particular, they advocate viewing a website as one web-based customer decision support system in which a multitude of web-based technologies can be applied to support customers as they move through the stages of their decision-making process. Such an approach not only can make for a more effective sales process, due to the richness of online technology (see Lightner, 2004), but also could lead to more efficient selling, as technological applications ensure the continuous availability of the selling actor.

In addition to the life cycle and decision support system views on using technology to facilitate sales and support buying processes, marketing scholars have introduced what is ...