Toward a conceptualization of personalized services in apparel e-commerce fulfillment

Abstract

Purpose

Today, customers’ perceived value does not only depend on the products, but also on the services provided by a firm. In e-commerce, it is important to shift the focus beyond the product and discuss the value of personalized services in the context of e-commerce fulfillment. Therefore, the purpose of this paper is twofold: to develop a conceptual framework proposing satisfaction through personalized services as a middle-range theory; and to suggest foundational premises supporting the theoretical framework, which in turn shape middle-range theory within the context of apparel e-commerce fulfillment.

Design/methodology/approach

In this theory-driven paper, the authors apply the scientific circle of enquiry, as it demonstrates the role of theorizing with the help of middle-range theory and empirical evidence and as such provides a methodological scaffolding that connects theory formulation and verification. The authors synthesize literature related to customer perceived value (CPV) and satisfaction, followed by abduction focusing on understanding the empirical domain as it occurred in practice from company cases. The presented case studies are based on semi-structured interviews with three Swedish online retailers within the apparel industry. The theory-driven analysis results in suggestions of foundational premises.

Findings

Based on the theoretical foundations and empirical generalizations, three propositions are suggested. The premises regarding satisfaction through personalized service applied in the domain of apparel e-commerce fulfillment are: to ensure customer satisfaction requires a value co-creation perspective using data during the pre-purchase phase; to ensure customer satisfaction and retention require added-value perspective during the post-purchase phase of the shopping journey; and to ensure satisfaction and convenience require an added-value perspective at the last mile.

Practical implications

The apparel firms lose a substantial amount of revenue because of poor online customer satisfaction, leading to e-commerce not reaching its full potential. To enhance customer value, online retailers need to find a resort in advanced technologies and analytics to address customer satisfaction, and it is suggested that retailers shift their focus beyond the products and find ways to improve personalized service offerings to gain market advantage, improve fulfillment, drive sales and increase CPV.

Originality/value

To consider personalized services as a source for improving e-commerce fulfillment and CPV, the main contribution of this study is conceptual as it presents a theoretical model developed from general theory, middle-range theory and verified with empirical claims.

Citation

Jain, S. and Sundström, M. (2021), "Toward a conceptualization of personalized services in apparel e-commerce fulfillment", Research Journal of Textile and Apparel, Vol. 25 No. 4, pp. 414-430. https://doi.org/10.1108/RJTA-06-2020-0066

1. Introduction

The advent of technology and increased globalization of apparel brands have transformed apparel online business models (Mollá-Descals et al., 2011; Hagberg et al., 2016). As an effect of globalization, cross-border restrictions have become less stringent, digital services have developed and conventional retailers face competition from both local and global brands (Holt et al., 2004; Dumitrescu and Vinerean, 2010). While as an effect of technology proliferation, contemporary customers are constantly connected through internet-enabled devices and have access to all the brands, increasing their choices. Because of this, customers’ awareness and demands are increasing, leading to higher expectations with the products and services offered (Botsman and Rogers, 2010; Wang and Zhang, 2012). This is forcing the industry to niche themselves, for instance, by producing individually tailored products and delivering higher value to the customer. Instead of just buying a branded product, the customers get to buy a product that is tailor-made for them.

Clearly, in a contemporary apparel market, it has become essential to increase perceived value and customer satisfaction by providing the best value offering and building stronger customer relationships. As a consequence, apparel retailers are finding a resort in new technologies such as the internet of things, artificial intelligence and big data analytics to gain a better understanding of consumers’ behaviors, needs and wants (Amed et al., 2017). Today’s technology, business models and social context allow for widespread use and development of big data. Big data, for one, offers unique opportunities to make the visions of a perfect apparel product for customers a reality. There have been instances in research trying to use the power of big data with advanced analytics and artificial intelligence to improve perceived value and satisfaction by focusing on the product offering. More of it is associated with improving the manufacturing operations or providing limited garment customization options (Fogliatto et al., 2012; Shang et al., 2013; Banica and Hagiu, 2016). There has been research focusing on the success factors of e-commerce, which shows personalization and improving the customer support system throughout the shopping process and during order fulfillment can benefit e-commerce businesses (Lei [Murray] et al., 2018; Bielozorov et al., 2019; Sharma and Aggarwal, 2019; Mushtaq et al., 2020). However, the application of digital technologies to tackle business-to-consumer challenges is scant (Giri et al., 2019), and there is a lack of research focusing on digital technologies and consumer-related services. The apparel industry is facing a pressing challenge with customer’s dissatisfaction with the current way it operates and requires new ideas expanding the view on customer demand and how to raise customer value and satisfaction with augmented service offerings. Also, apparel managers are facing new challenges and opportunities in COVID-19 pandemic times. The year of 2020 so far has proven particularly difficult for apparel businesses as revenue dramatically decrease as a result of this event.

It is suggested that creating an exceptional customer experience all through the customer journey is one of the main goals to drive business profitability. During the quarantine, people have had more time to stay at home and shop online, and as a result, online retailing have a potential to drive future apparel businesses to a much greater extent than before. It is thus important to understand people’s satisfaction with apparel e-commerce. The customer’s purchase experience does not only depend on the product itself, but retailers might also exploit big data into consumer insights, and transform such knowledge into augmented services integrated in the marketing strategies (Bonetti et al., 2020). In a purchasing process followed in a traditional fixed store setting, customers are responsible for unit-level fulfillment services such as picking products off the store shelf, moving these to the checkout lane and providing delivery to homes and other consumption points. Hence, in such settings, the customer has the first-hand experience with the product before the actual purchase, and the delivery point (i.e. when the customer takes their product home) is usually a routine task. However, in terms of e-commerce, the physical distribution activities are much more important to the customer as the delivery point will be the first time when the customer actually interacts with the product. It is also suggested that logistics and fulfillment services are the basis for improving customer satisfaction and loyalty in an e-commerce setting (Skurpel, 2020), and that the customers expect a similar level of personalization even during order fulfillment (Lei [Murray] et al., 2018). Therefore, it is plausible to focus on a personalized experience during order fulfillment, improving satisfaction and perceived customer value using non-product related experiences, and thus, making the relationship with the customer stronger (Davis-Sramek et al., 2008; Cao and Li, 2015). As an instance, Tian et al. (2020) presents a block-chain based evaluation of customer satisfaction in the context of urban fulfillment. Before and on delivery, apparel retailers need to provide customers with more than just the product. It is important to inculcate trust and loyalty toward the firm by also providing memorable experiences with the help of personalized services. Some services, however, might be an additional cost to the company, albeit if it increases customer engagement and loyalty, then it contributes to the firm’s overall growth. Although the interest in personalized products has grown considerably in recent years, little attention has been paid to analyze customer perceived value (CPV) and satisfaction of personalized services in the context of online apparel. Hence, for a firm to have a competitive advantage, it needs to think beyond the product and add value through different stages of the customer journey. This can be achieved through superior experiences by implementing personalized services during both pre-purchase and post-purchase phases.

These value-adding attributes and unique experiences across various buying channels and shopping phases are of major importance to the customer when they choose between different retailers (Verhoef et al., 2015). The probability of re-purchase will be greater if the retailer succeeds in providing something unique and of value to the customer. We believe that personalized services can contribute to unique value additions to a customer’s shopping journey, and identify the need for conceptualizing personalized services to tailor apparel e-commerce fulfillment. Hence, this paper suggests re-thinking CPV by extending its focus to personalized service offerings and more specifically, satisfaction through personalized services related to pre-purchase and post-purchase phases. It considers how an orderly application of middle-range theorizing, which extends particular attention to contexts and mechanisms, can be used to broaden current knowledge on CPV in research related to apparel e-commerce. In this regard, the purpose of this paper is to demonstrate the use of middle-range theorizing by exploring how empirical evidence from the industry can be used to inform the development of personalized services. The paper applies the scientific circle of enquiry (SCE) (Brodie et al., 2011; Kislov et al., 2019) for middle-range theorizing in the area of personalized services to develop a research framework that can guide future research in apparel e-commerce. It presents how CPV theory can provide foundation to personalized services, which acts as a middle-range theory, to bridge the empirical research within apparel e-commerce fulfillment using satisfaction and CPV theory. The SCE demonstrates the role of theorizing with the help of middle-range theory and empirical evidence and as such provides a methodological scaffolding that connects theory formulation and verification (Kislov et al., 2019). The rationale is that general theory is too broad and abstract to easily be linked to empirical research, alas the middle-range theories act as a bridge to connect them (Brodie et al., 2011; Kolyperas et al., 2019). Three Swedish business cases are used to suggest propositions to support the framework and serve as exemplars of the suggested middle-range theory.

The rest of the article is structured as follows. Section 2 describes the overall methodology followed for empirical data collection, analysis and model conceptualization. Section 3 presents the findings from the literature review on CPV and satisfaction through personalized services in the online customer journey, and the empirical generalizations of apparel e-commerce fulfillment as deduced from the three cases. Finally, Section 4 addresses the discussion and conclusion of the study.

2. Method

In general, there are three essential elements that are considered while conducting middle-range theorizing:

1. discovering research within a designated domain;

2. structuring directly on recognized findings within that domain; and

3. emphasizing on contexts in which they produce outcomes. (Pawson and Tilley, 1997; Stank et al., 2017; Pellathy et al., 2018).

With an integration of these elements, middle-range theories develop research grounded in empirical evidence and provide an understanding on actions that can produce results. In this study, to broaden conceptual thinking on personalized services, the authors sought a path of guidance from CPV literature and empirical studies from the field. As shown in Figure 1, satisfaction through personalized services is used to bridge the gap between CPV and the empirical domain of personalized services in apparel e-commerce fulfillment. The bridging role of middle-range theory can be exhibited in the SCE (Brodie et al., 2014) accentuating the bilateral connections between theories and empirical cases at different levels of conceptual abstraction as shown in Figure 1. Hence, an abductive way of theorizing was chosen where the focus was on understanding the empirical domain as it occurred in practice in the presented cases, reading, interpreting and comparing transcript interviews with the help of theory. The findings from the empirical cases then support the modification of mid-range theory (personalized services) with the help of propositions that can further be refined to expand the scope of the grand theory i.e. CPV theory in this article. This transitional role of middle-range theory makes their progress pivotal for the evolution of the social science (Merton and Merton, 1968). In the first phase of the study, relevant literature was used to bring an understanding of the concepts involved i.e. CPV and satisfaction through personalized services at pre- and post-purchase.

The authors analyzed the articles and searched for concepts and ideas that could support the challenges of providing apparel e-commerce fulfillment, and identified a pattern to interpret the interviews. The transcript interviews served as empirical evidence and claims. Finally, the conceptual understanding was used to fill in the “question marks” in the model by identifying empirical claims and to present foundational premises in this paper.

2.1 Data collection and analysis

The empirical data was part of a research project between 2016–2018 and commissioned at collecting practice-oriented cases that serve as illustrations and/or explorations of the retail phenomenon, customer experience and customer satisfaction. During the research project, semi-structured interviews were conducted with key-employees in ten different types of retail companies, including industries such as apparel, cosmetics, home textiles and home electronics. The companies operated different channel formats that included bricks-and-mortar stores, online and both online and offline selling. This study presents purposefully selected empirical findings from three of these companies as they are matching pairs and offer online strategies for apparel. These companies were selected based on their experience in the apparel e-commerce business, and are considered pioneers in providing tailored product offerings and are early adopters of latest digital technologies. The cases were audio-recorded and labeled according to the company name, informants’ designation and function, description of the session and duration (as depicted in Table 1). The interviews were done with key employees from three companies with minimum 3–4 years of experience, performed in Swedish, and then translated into English with the help of a professional translator to maintain the quality of the translation. To avoid bias, the informants were selected based on their experience and knowledge, and from different hierarchical levels and functions. The data consist of seven in-depth interviews with employees at the three firms, both at senior and junior management level, as well as handling operational functions such as logistics and supply chain management. The informants in the study are described below in Table 1. The lowercase “a” and “b” refer to different sessions of the interviews.

To ensure confidentiality in this paper, the three retailers are referred to as A, B and C. The online apparel retailers are particularly suitable for illuminating and extending relationships and logic among constructed propositions discussed in the next section. They provide a strong base for theoretical development, clarify the context of discovery and the proposed middle-range theory; thereby, enhancing the understanding of satisfaction through personalized services. An overview of the case exemplars regarding operations and the characteristics of the companies are presented in Table 2. For the analytical deepening of the data collected through the interviews, the interviews were transcribed, which is a common practice while conducting qualitative research (Davidson, 2009). A standard way of ensuring validity of a study is by using triangulation, where either more than one data source, method or researchers can be involved (Tobin and Begley, 2004; Bashir et al., 2008; Yin, 2018). As already mentioned, the data collected in this study is part of a research project from 2016–2018 involving various researchers. This study considered researcher triangulation where several researchers were included in the data collection. An in-depth analysis of the transcribed data and extensive review of the literature was conducted by breaking the interviews down and coding it in Microsoft Excel with the help of a general theoretical foundation bridging the domain with the help of middle-range theory. This resulted in an empirical generalization of personalized services within apparel e-commerce fulfillment that could be supported and verified using the suggested conceptual framework. Thus, the theory-driven analysis captures empirical claims with the help of foundational premises that could extend the notion of personalized services in apparel e-commerce, presented in Figure 1.

3. Foundational constructs and empirical claims

In theory’s most recent form, CPV is considered to be a general theory as it is broad in scope and more abstract in nature. CPV has been a popular concern both to researchers and business practitioners across disciplines (Zauner et al., 2015). Based on the extant literature related to CPV, it was noticed that CPV is mostly associated with the product (Suryadi et al., 2018), but has also been used within the service literature to understand service quality (Arslanagic-Kalajdzic and Zabkar, 2017; Behnam et al., 2020; Xuan Nguyen et al., 2020). The understanding of perceived customer value helps to explain different areas such as behavior and repeat purchasing as it describes the perceived net gains associated with the products/services acquired (Grewal et al., 2003). When the perceived value is higher than the perceived cost, customer satisfaction is positively influenced (Cronin et al., 2000), which in turn contributes to customer loyalty (Zeithaml et al., 1996; Colgate and Stewart, 1998; Tam, 2004).

3.1 Ideas of value

The value that customers perceive is different for different customers and is closely related to price, quality, sacrifice and satisfaction (Fazal-e-Hasan et al., 2018). In addition, for customers, value is an important attribute to make reasonable purchase decisions. Value for consumers involve both utilitarian and hedonic consequences as acknowledge by extensively cited studies by Sheth et al. (1991) and Holbrook (1999). While utilitarian value is the easiest to provide, the competitive advantage for any business lies in how they offer hedonic value to their customers and know the difference between hedonic and utilitarian value. Hence, customer value is “the fundamental basis for all marketing activity” (Holbrook, 1994, p. 22) and should be of concern to managers seeking to strengthen fulfillment.

Ever since the birth of modern marketing management, customer satisfaction has been a pursuit among the marketing community (Levitt, 1960; Kotler, 1968; Kohli and Jaworski, 1990; Piercy, 1995) and a critical focus for effective customer care (Yang and Peterson, 2004) and loyalty (Kumar et al., 2013). However, the definitions on customer satisfaction are not clear but the most popular perspectives are either a transaction-specific approach or a cumulative and overall approach. Regardless of which approach is chosen, satisfaction is usually described as an end-result and a desirable goal among most managers; companies want their customers to be satisfied. But to understand satisfaction, one needs to explore why and with what satisfaction has aroused. Therefore, when elaborating on fulfillment, CPV is the foundational construct, accompanied with utilitarian and hedonic value.

3.2 Ideas of customer involvement and engagement

CPV arises at nearly all phases in the customer journey, including but not limited to the pre-purchase phase, post-purchase phase and the last mile, while customer satisfaction is considered to be a post-purchase or post-use assessment (Chi and Kilduff, 2011). Traditionally, the pre-purchase phase took place in a brick and mortar store setting; where the customer could interact with the product as well as take help from the sales assistants to make the purchase decision. However, today, with a lot of sales taking place online (websites or social media platforms), the possibility to influence the purchase decisions largely falls under how well does a brand guide and handle the purchase experience. The possibility of improving perceived value at this stage is an important strategy that a brand has to develop to gain consumer confidence and trust. In such a context, it is important to examine value as perceived from personalized services (Roy et al., 2017; Pappas, 2018), and how such services lead to satisfaction. By considering personalizing services to be a resource for generating new forms of value, these services can be seen as a valuable source of gaining competitive advantage and attain customer loyalty. Today, apparel firms are struggling with immense competition because of globalization (Hagberg et al., 2016). By providing personalized services during the customer online journey, firms in the apparel industry can achieve higher CPV by engaging and involve their customers through the journey. This is in line with Harrison and Hoek (2008), who said the key to increasing the customer value is by focusing on service quality, which gives an additional competitive advantage, as it is difficult to imitate by the competitors. Customer involvement and engagement will allow apparel retailers to improve fulfillment in an era when customer journeys are dispersed across different retail channels and the route to purchase may take a few minutes or many weeks. Therefore, when elaborating on fulfillment, CPV is the foundational construct, accompanied with involvement and engagement.

3.3 Ideas of retention, loyalty and customer convenience

Personalization in retail is the process of using customer data to provide tailored experiences to customers during different stages of the shopping journey. Every path to purchase is different, and with personalization, each path can be served based on specific needs and behavior, which will increase the possibilities of retention and loyalty. However, most retailers are nowhere close to delivering the personalized experiences that their customers indicate when leaving digital footprints. In addition, many retailers are unclear about which capabilities to build and create a truly personalized experience (Mark Abraham et al., 2019) and how to create customer loyalty. Providing personalized services should be in line with the goal to use the latest technology to tailor critical touchpoints in a manner that support retention. To better understand and examine the CPV within personalized services at different shopping stages, it is important to identify the different stages. A customer’s shopping journey begins with searching for the required product, to placing an order and ends with the delivery of goods (Medini, 2015). This is a basic process, and if rightly understood, is an opportunity for providing a convenient shopping journey, which in turn might lead to both retention and loyalty. However, the criticality of this increases manifold when the shopping process is taken online as the customer can easily wander off to other retailers in search of a better value offering. For e-commerce businesses, the last mile is the only stage during which customers interact with the product for the first time, and is, therefore, a valuable determinant of customer experience (Croxton, 2003). A successful shopping process involves several activities, executed by different functional entities, and is heavily interdependent among the tasks, resources and agents involved (Lin and Shaw, 1998).

Customers, nowadays, seek value in personalized experiences and expect their occurrence much earlier in the shopping process (Walsh and Godfrey, 2000; Bilgihan et al., 2016). Hence, personalizing services involves knowing how to connect the customer with the product and by extension the firm as early as the customers search for the product. Providing such a level of personalization is challenging and requires extensive domain experience in product, service and order management with expert knowledge of digital business to evaluate existing technical outlook, recognize gaps and surface opportunities. One possibility of achieving the expected level of personalization is by finding a resort in the latest technologies and big data collected by businesses on the internet. This data can be used to deduce optimal shopping scenarios, create urgency to purchase and deliver the service personalization and convenience that the customers demand inherently driving perceived value. Therefore, when elaborating on fulfillment, CPV is the foundational construct, accompanied with retention, loyalty and convenience. The following are three instances of apparel retailers, who have tried to harness the essence of value by targeting one of the aforementioned dimensions.

3.4 Case A – empirical claims

Case A is an online retailer selling branded fashion to men with the promise to help them in designing a personalized wardrobe matching their style. Two entrepreneurs started this company, who believed there was a market for young men that wanted to buy high branded fashion but did not have the time/energy/skill/self-confidence to choose their outfit. The company wants to take care of its customers by helping them in expressing themselves with the help of fashion and providing personal service based on true commitment and concern. As one of the managers said: “We live by the idea of helping our customers and every day we try to think that caretaking and commitment make us unique” (Table 1, Interview 1a).

The system supporting this vision is based on a concept of mass customizing the shopping process by focusing on the individual customers’ profile. This is an advanced form of personalized service, which can help the customers in making decisions when shopping for apparel online. Customers are invited to enjoy a “diagnosis” (Table 1, Interview 2a) of their aesthetic preferences and the information is stored as “personal taste” (Ibid). This information is then processed to find suitable garments that can meet the customers’ individual preferences. In this way, the firm secures the possibility to offer customers individualized fashion styles and at the same time, reduce efforts for the customer in terms of the anxiety caused by the decision-making process. In addition, by including the customer more closely by capturing and responding to their preferences co-creates greater value. Moreover, when the customers realize that the retailer or brand is committed to listening, involving and providing their exact requirements, they are more engaged in the entire shopping process. Here, co-creation is the basis for providing unique experiences and value to each individual. In doing so, the rationale of the brand is that a firm must create value for their customers in a manner that engages them in designing their own experiences, and hence, deliver personalized experience during that moment.

3.5 Case B – empirical claims

Case B is a Swedish online actor selling fashion to female customers with a virtual store as the only retail channel, building their fulfillments on information flows and customer data. Two young entrepreneurs started the company in 2014. They built the company with the idea of personalization, as they use designed and handcrafted boxes to ship orders and invest a lot in the packaging process. One of the owners said he dislikes plastic bags: “I really find plastic bags ugly and I have always believed in using branded packaging” (Table 1, Interview 3a). Hence, while packaging a product, it is placed in a handcrafted box, silk paper is used for wrapping and a silk ribbon is used around the garment with a bow. The other owner added:

We really strive to visually convey each order as a personalized offering and we try to imagine the customer opening the package at home, it should be like Christmas Eve (Table 1, Interview 4a).

Both managers and owners talked about adding value at the packaging stage, and the importance of having a dedicated staff. They believe in building relationships based on basic personalization capabilities i.e. addressing the customer by their name on a handwritten card, put into the box, wishing the customer good luck with the new garment and a recommendation to wear the new product with something else bought from the firm. This offers a sense of closeness between the customer and the brand. This kind of personalization is often provided by luxury brands, with the loyalty of their customers being a benchmark for other retailers (Hur et al., 2014). It is still unusual to provide the customers with a product that is not packed in a brown cardboard box.

In addition, to bring extra value to the customers, in terms of personalized order information, when the order is placed, the customer receives a link and can follow the real-time product transportation on his or her mobile phone. The mobile application can help the customer to stay updated concerning their orders, and any new offers that the retailer might have designed for them. In fact, through mobile applications, the retailer can push personalized notifications, provide tailored recommendations on “what else to buy” or “what can go with the product they recently bought,” and can also track the customers’ past purchases. As one of the respondents explains:

When I get information from the CRM system that this customer bought a pair of jeans last year, I can give her the recommendation to wear this beautiful sweater together with her jeans. This is something a lot of our customers really like; they understand that we really care about them. (Table 1, Interview 3b).

Based on this kind of customer relationship management system that focuses on providing the customer additional value all through their shopping process as well as establishing interactions post-purchase enhances the overall customer experience with the brand. The point of delivery and the moment when the customer opens the package is central to the company and they not only encourage customers to enjoy that moment but also to spread the feeling to others by sharing their experience with their friends. Hence, on every handwritten customer card, the respondent reveal they write, “Spread the joy to others – take a selfie and contribute to happiness!” (Table 1, Interview 4b). The way that the firm works seizes the possibility to offer individualized services to enhance the customer experience both during pre- and post-purchase phases including the time of delivery, and builds value for the customer gradually over time.

3.6 Case C – empirical claims

Case C is a specialized fashion online store focusing on sports and street fashion. It also offers merchandise through brick-and-mortar stores in limited geographical areas. The idea of personalized services stems from the customers having different needs regarding delivery options. “The demand for individualized offerings is in fact our main challenge” (Table 1, Interview 5b). Other respondent underlines the importance of being a good listener “I believe part of our success is our willingness to talk and listen to our customers” (Table 1 Interview 6a). The target group is widespread in the Nordic countries but also in other European countries. With different countries having different distribution networks and regulations, the firm chose to invest in its delivery boxes, co-operating with Instagram. The “Instaboxes” are placed at hot spots in different localities, identified by the customer database in each country.

The delivery service to Instabox is chosen during order placement i.e. the customer chooses Instabox as the delivery option and identifies the most convenient place to pick up the order. The customer receives an SMS with a tracking link and a pin code, as management in the company discovered that up-to-date information was key:

Customers can wait, but they demand to know for how long and why. Think of a patient in a hospital. Some years ago he/she might have accepted that instruction. Today, they can wait if they know why (Table 1, Interview 7a).

After the delivery, the customer uses the pin code to unlock the box and pick up the parcel. One of the interviewees says:

We have noticed that our customers are very impatient and they want to have their delivery as soon as possible, but time is not the only variable. They also want their delivery in a convenient place, as most of our customers do not have a car. Therefore, they prefer public places such as the bus station, the mall, or subway station. I think it is necessary to offer a broad spectrum of delivery options, and the possibility to pick an order up at any time, not only during store hours. By using Instaboxes, we can do that (Table 1, Interview 5a).

The respondents in company C all believe that adding value at the delivery stage is very important expressed by one of the respondents as “freedom of choosing the delivery options can increase our customers’ perceived value and acquire loyal customers” (Table 1, Interview 6b).

4. Foundational premises and discussion

Based on the instances from the cases presented in the above section, the authors now present a model that portrays the essential ingredients required in conceptualizing personalized services during the customer journey to provide apparel e-commerce fulfillment. The context of discovery is depicted in Figure 2.

The retail landscape has drastically transformed over the past decade, and the rise of e-commerce is largely accountable for these changes (Goyal et al., 2019; Lin, 2019). Although many of today’s customers purchase through both traditional stores and online retailers, the shopping experience is very different for each. Making purchasing decisions and getting assistance when needed is more difficult with e-commerce. However, there are many ways to support customers through the online journey and improve fulfillment.

Personalization is the key to provide unique experiences to the customer and improve e-commerce fulfillment (Pappas, 2018), thereby raising the rate at which they translate a potential shopper into a loyal customer, and increase the lifetime value of customers. Nevertheless, so far, most retailers have not gotten as much traction from their personalization initiatives as they could have. Retailers that desire to get ahead and gain a competitive advantage will need to provide truly personalized services throughout the customer journey. By doing so, firms can drive their core business objectives, including building brand value, improving customer engagement, retention and loyalty.

This is also in line with enhancing perceived value of the customers, who not only expect quality goods and services, but convenience and unique experiences during the entire process from searching for a product to receiving and using it. Considering this, formulating customer-centric strategies becomes a necessity as this will ensure a positive experience or transform a bad one into a good experience, thereby, reinforcing customer loyalty. Hence, propositions from the conceptual model in this study are three.

The first proposition is:

The operations regarding providing personalized experiences to ensure customer satisfaction require a value co-creation perspective using data during the pre-purchase phase.

The second proposition is:

The operations regarding providing personalized experiences to ensure customer satisfaction and retention require added-value perspective during the post-purchase phase of the shopping journey.

The third proposition is:

The operations regarding providing personalized experiences to ensure satisfaction and convenience require an added-value perspective at the last mile.

The conceptual model presented in Figure 2 contributes to the theory of increasing CPV using personalized services provided by apparel e-commerce retailers. It should also be considered that the maturity of personalization differs across industries, where the apparel industry is considered to be at a mid-level, and there are industries like food and grocery that have achieved higher levels. Even though the case exemplars discussed are from apparel retailers, the model can be generalized for all e-commerce retailers. The idea of providing personalization is also dependent on the current capabilities of the retailer. To enhance customer value, retailers need to find a resort in advanced technologies and analytics to address customers’ needs. Simply put, retailers need to shift their focus beyond the products and find ways to improve service offerings to gain market advantage, drive sales and increase value to the customers.

4.1 Toward building a future research agenda

This study proposes a theoretical framework for apparel e-commerce fulfillment during pre-purchase, post-purchase and the last mile of the customer journey. The paper applied “the Scientific Circle of Enquiry” to show the bridging role of middle-range theories and the connections that exist between empirical observations and theories at different levels of conceptual abstraction. The middle-range theories, thus, govern and determine which empirical illustrations are best exemplified and illustrated. The empirical data presented is not central but is there to support modification of middle-range theories and thereby refining and expanding the scope of the grand theory i.e. CPV theory in this case.

The theoretical framework is built on satisfaction through personalized services as the principle of middle-range theory, which bridges CPV theory with empirical evidence. It is suggested that as per the theoretical and empirical findings, the perspective of the retailers should shift beyond the product to services. This is in line with the firms competing at a global level, striving to bring a competitive advantage and sustain the increasing customer demands. Adding a personalized service perspective to the e-commerce business strategy will support managers by providing unique experiences and increase overall value to the customer. A fine-tuned and unique shopping experience can go a long way in ensuring customer satisfaction and building loyalty in new and returning customers. Regardless of various changes in the industry, it remains evident that personalizing customer service in a way that improves fulfillment will always be relevant for a successful customer experience strategy.

The focus of the study was to build a conceptual model around the idea of providing personalized services. There are some limitations to the study, one of them concerning verifications from the case studies. Even the most detailed narratives are usually a simplification of what were told, and even though the transcripts from the cases were rich, the authors chose to present few quotes and took them of the context of the narratives. It is therefore likely that a revisiting of the data would reveal other issues and aspects of the data. However, as the study focuses on conceptualization and is theory-driven, this limitation was deemed appropriate. This study can be a starting point to further build personalized services as a middle-range theory. One of the future directions would be to undergo more in-depth empirical research supporting the model suggested. A cross-industry analysis with multiple retailers can be conducted to expand the implications of this research. Another perspective that can be adopted is of conducting a consumer-centric research and integrating with the findings of this study.

Figures

Figure 1.

A framework of the conceptual model for viewing and using satisfaction through personalized services, based on CPV

Figure 2.

Context of discovery – personalized services, empirical claims and foundational premises

Table 1.

Informants in the study

Company	Informant’s designation and function	Description of sessions	Duration
A	1. CEO, Senior Manager	In-depth interview 1a	60 min
A	2. Head of Logistics, Junior Manager	In-depth interview 2a	45 min
B	3. CEO, Founder, Senior Manager	In-depth interview 3a and 3b	60 min and 45 min
B	4. Business Developer, Founder, Senior Manager	In-depth interview 4a, and 4b	45 min and 45 min
C	5. CEO, Senior Manager	In-depth interview 5a and 5b	60 min and 60 min
C	6. Supply Chain Manager, Junior Manager	In-depth interview 6a and 6b	60 min and 60 min
C	7. COO, Senior Manager	In-depth interview 7a	60 min

Table 2.

An overview of the case exemplars

Company	Operational descriptions	Target group/groups	Personalized/tailored variables in shopping process	Sales 2015 (SEK)	Revenue (SEK)	No. of employees	Start date
A	Focusing on customer relationship marketing (CRM), using advanced customer data to tailor each offering to relevance. The most important moment in the customer journey is when the customer receives the suggested outfit (based on historical transactions and style/preferences)	Middle-aged customers, premium	Diagnosis of aesthetic preferences Personal taste regarding packaging	136,801,000	10,876,000	27	2010
B	Focusing on CRM where the delivery is seen as an important point of interaction. When the customer receives the package (a beautiful box), it should be a joyful event	Middle-aged customers, premium	Personal recommendations based on historical transactions Designed craft beautiful boxes	987,739	63,247	4	2014
C	Focusing on CRM, using data analysis to offer a convenient and smooth delivery option	Young customers (10–25 years), premium	A variety of delivery options located according to customer convenience	250,142,000	1,773,000	85	2002