The customer orientation of customer contact employees is very important to the implementation of the marketing concept (Martin and Bush 2006). A rich stream of research provides evidence that it positively affects outcomes such as employee performance (e.g., Siders et al. 2001), customer satisfaction (e.g., Brady and Cronin 2001; Goff et al. 1997), and customer trust (e.g., Swanson et al. 1997; Williams 1998). However, as Franke and Park (2006) note in their recent meta-analysis, there is still no answer to a question raised 30 years ago by Saxe and Weitz (1982, p. 343): “Is customer-oriented behavior universally effective, or does its effectiveness depend on context factors?”

The lack of attention to this issue is surprising, as it is likely that the effectiveness of customer-oriented behaviors depends on characteristics of the purchasing situation. For example, as customer perceived risk is higher for important products (Bloch and Richins 1983), customer information needs are also higher (Murray 1991). Customers purchasing important products are thus likely to place more value on customer-oriented salesperson behaviors (such as adapting a sales presentation to their needs) than customers purchasing products not perceived as important.

Therefore, this study investigates moderators of the link between salespeople’s customer orientation and customer loyalty. In our choice of moderators we draw on Sheth (1976), who proposed looking at style of communication and content of communication as context variables when analyzing buyer–seller interactions. Regarding the former, we consider customer communication styles (McFarland et al. 2006). Regarding the latter, we turn our attention to product characteristics (e.g., product individuality, product importance, product complexity, and brand strength). In sum, the first goal of this research is to empirically study the effect of the purchasing situation on customer orientation effectiveness.

To achieve this goal, it is important to also address the conceptualization of the focal construct. Most importantly, since the introduction of salesperson customer orientation to the literature (Saxe and Weitz 1982), sales environments have changed dramatically (Weitz and Bradford 1999), whereas its conceptualization has not. As Schwepker (2003, p. 152) notes in his literature review: “[T]he core meaning of customer-oriented selling has remained relatively consistent across studies.” In this tradition, customer orientation is viewed as a set of task-oriented behaviors (e.g., describing products accurately or identifying customer needs). We will refer to this conceptualization as “functional customer orientation”, as it is limited to behaviors that customers are likely to expect from the salesperson in the role of a businessperson.

However, today’s emphasis on establishing sustainable long-term business relationships between buyer firms and supplier firms (Cannon and Perreault 1999) has created an environment that also nurtures the development of strong personal relationships between salespeople and customers (Price and Arnould 1999). Therefore, in many interactions with their customers salespeople also play the role of a friend in addition to their traditional role as a businessperson (e.g., Heide and Wathne 2006). Only recently a few studies on customer orientation, mostly originating from the services literature, have started to acknowledge this development. Here, customer orientation also comprises behaviors aiming at establishing a personal relationship with the customer, such as getting to know a customer personally (e.g., Donavan et al. 2004). We will refer to these behaviors as “relational customer orientation”.

This distinction reinforces the need to consider the impact of context factors in customer orientation research. As customer expectations regarding the two salesperson roles (businessperson and friend) may diverge, salespeople face new dilemmas (Heide and Wathne 2006). In particular, in some situations customers may perceive relational salesperson behavior as an attempt to instrumentalize a personal relationship to simply close a deal (Grayson 2007). For instance, when purchasing a complex product, customers could perceive relational behavior (e.g., extended informal communication) as an attempt to distract them from complicated issues with the product. However, this reaction is unlikely when the salesperson sells a product which is easy to evaluate. Hence, drawing on role theory, our second research goal is to study which type of customer orientation is more effective, given the specific situation of the interaction.

A notable characteristic of our study is that the considered constructs relate to three different levels of analysis. That is, product characteristics relate to the sales unit level, customer orientation relates to the salesperson level, and customer communication styles and customer loyalty relate to the customer level. Therefore, we support our propositions empirically by applying multilevel analysis to triadic data from a cross-industry sample of 56 sales managers, 195 sales representatives, and 538 customers.

By addressing the issues described above using this type of empirical analysis, this study makes at least three important contributions to the literature on salesperson customer orientation. We have visualized these contributions in Fig. 1.

Fig. 1
figure 1

Categorization of previous research on salesperson customer orientation (CO)

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First, this study is one of the first to address the impact of context characteristics on the effectiveness of salesperson customer orientation. As evidenced by the studies listed in Fig. 1, most previous studies in this domain have analyzed the effects of customer orientation by assuming their independence of context factors. Moreover, the few studies that did consider moderating effects of situational variables have only focused on salesperson characteristics, particularly salesperson skills (Wachner et al. 2009), salesperson personality traits (Stock and Hoyer 2005), and a salesperson’s ability to help (Saxe and Weitz 1982). Thus, to the best of our knowledge, this study is the first to analyze the impact of customer characteristics and product characteristics on the effectiveness of customer orientation. It is worth noting that through this approach our study also applies a key implication of the adaptive selling literature to research on salesperson customer orientation, namely that the effectiveness of specific sales behaviors is contingent on the sales situation (Spiro and Weitz 1990).

Second, as evidenced by Fig. 1, previous research has predominantly viewed customer orientation as a set of functional behaviors. Despite the growing emphasis on buyer–seller relationships, only a few studies from the services literature have started to consider customer orientation as a set of functional and relational behaviors. Moreover, they all rely on the conceptualization proposed by Brown et al. (2002), where relational behaviors are part of a larger “enjoyment” dimension of customer orientation, referring to the degree to which service workers enjoy providing service. Thus, to the best of our knowledge, this study is the first to explicitly distinguish functional from relational customer orientation.

Third, this is the first study to investigate the impact of context variables on customer orientation effectiveness, while considering both its functional and its relational dimension. Drawing on role theory, we arrive at a number of hypotheses predicting differential effects of the two types of customer orientation, depending on whether customers expect the salesperson to play the role of a businessperson or a friend. Thus, other than earlier research, we do not expect functional and relational elements of customer orientation to always have similar effects. Moreover, we adopt a theoretical perspective that even allows for possible negative effects of salesperson customer orientation, particularly with regard to its relational dimension.

Theoretical background and framework

A role theory perspective on salesperson customer orientation

While relying on the metaphor of the theater (Hindin 2007), the basic postulate of role theory is that similar to actors, individuals exhibit behaviors that can be ascribed to their specific role in a particular interaction. In this context, roles are shared expectations about how an individual ought to behave in a given situation. However, while—similar to actors—individuals can take on multiple roles, unlike their metaphorical counterparts they often occupy multiple roles at once. As a consequence, they may experience role conflict, i.e., a strong tension between diverging expectations regarding their different roles (e.g., Ivey and Robin 1966). If they do not succeed in resolving such an apparent role conflict, the corresponding social system (e.g., an interaction episode) “will be disrupted” (Biddle 1986, p. 82).

A number of recent studies have successfully applied role theory to further our understanding of interactions between salespersons and customers in the age of relationship selling (e.g., Grayson 2007; Heide and Wathne 2006). In particular, the emerging focus on developing strong buyer–seller relationships has also favored the development of close personal relationships between salespeople and customers (Yim et al. 2008). As a result, for many customers, salespeople play two roles: the role of a partner in a business endeavor and the role of a social acquaintance, often even a friend (Jones et al. 2008).

However, depending on the situation, role expectations regarding these two roles may substantially differ. As Heide and Wathne (2006) point out, expectations regarding a business partner follow a “logic of consequences”, emphasizing the extrinsic motivation of the partner to stay in a relationship. At the same time, expectations regarding the behavior of friends are guided by a “logic of appropriateness”. Here it is expected that the other party stays in the relationship for intrinsic motives, i.e., for the sake of the relationship itself. These diverging expectations are an important source of tension and ambiguity in salesperson–customer interactions (Price and Arnould 1999). At times, they may even become a liability, particularly if the customer fears that a personal relationship is instrumentalized for business purposes (Grayson 2007).

These theoretical considerations have at least four implications for this study. First, they suggest that the functional behaviors that are at the core of most previous conceptualizations of salesperson customer orientation (e.g., the identification of customer needs or the customization of products) only reflect customer expectations regarding the business role of the salesperson. However, given the social role of many salespeople, it is also necessary to consider behaviors aiming at establishing a personal relationship with the customer. Therefore, in our conceptual framework we consider functional customer orientation and relational customer orientation.

Second, they highlight that the diverging customer expectations regarding the different salesperson roles may lead to salesperson role conflict, which—if not resolved adequately—will result in a disruption of the relationship. Thus, the theory points to the importance of including customer loyalty as key outcome of customer orientation in our framework.

Third, role theory posits that the situational context is an important driver of the roles that individuals are expected to play. Therefore, the effectiveness of functional customer orientation and relational customer orientation is likely to depend on the context. Consistent with this view, Beatty et al. (1996) find that the effects of functional and social benefits customers obtain from interactions with salespersons depend heavily on the value customers place on these benefits. Similarly, the effect of a salesperson’s relationship-building behaviors strongly hinges on a customer’s willingness to engage in a relationship (Beverland 2001). Consequently, our study focuses on developing moderator hypotheses regarding the link between customer orientation and loyalty. As according to Sheth (1976), customer expectations regarding salesperson behaviors are largely dependent on customer characteristics and product-specific factors, both types of variables are included in the framework.

Fourth, role theory points to the possibility that customer-oriented behaviors may sometimes even have negative consequences if they do not meet customer expectations of appropriate salesperson behavior. This is particularly true for relational customer orientation. For instance, in situations where customers strongly expect the salesperson to take on a business role and exhibit a functional customer orientation, attempts to establish a personal connection may backfire, because they are perceived as insincere (Hennig-Thurau et al. 2006). Therefore, this study focuses on developing moderator hypotheses.

Overview of framework

The framework resulting from our theoretical considerations is presented in Fig. 2. In the following, we will provide definitions for its key elements.

Fig. 2
figure 2

Conceptual framework

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Consistent with previous research, we define customer orientation as a set of behaviors indicating a high concern for customer interests and needs and ensuring long-term customer satisfaction (Franke and Park 2006). While this basic definition is widely acknowledged, there are differing views regarding the conceptualization of the construct (Stock and Hoyer 2005).

In the sales literature, researchers have mainly adopted Saxe and Weitz’s (1982) conceptualization of customer-oriented selling as relying on customer-oriented behaviors that relate to the selling task, such as offering products that will satisfy customer needs (e.g., Goff et al. 1997; Siguaw et al. 1994). Consistent with this view, we define functional customer orientation as a set of task-related behaviors aimed at helping customers make satisfactory purchase decisions.

A different perspective on customer orientation has recently emerged from the services literature, where researchers have considered an employee’s interpersonal behaviors to be another aspect of customer orientation. From this perspective, customer orientation also includes an employee’s tendency to build a personal relationship with customers (Brown et al. 2002; Donavan et al. 2004). Based on this research, we define relational customer orientation as a set of behaviors aimed at establishing a personal relationship with a customer.

Such a distinction between functional and relational customer orientation is consistent with the distinction between functional and personal influence strategies in customer contact situations (e.g., Weitz 1981). From a customer’s perspective, a functional or relational customer orientation may lead to functional or social benefits from a relationship with a customer contact employee (Dwyer et al. 1987; Reynolds and Beatty 1999).

According to the literature, the primary goal of a customer orientation—whether functional or relational—is the creation of long-term, mutually beneficial relationships with customers (e.g., Keillor et al. 2000; Swanson et al. 1997). Therefore, this study investigates under which conditions a functional or relational customer orientation actually leads to customer loyalty. We define customer loyalty as a customer’s expressed preference for a company and intention to continue to purchase from it and to increase business with it in the future (Zeithaml et al. 1996).

Now definitions will be provided regarding the characteristics of the purchase situation included in the framework. Regarding customer characteristics, we consider a customer’s communication style as a potential moderator of the effects of customer orientation on customer loyalty. A communication style is a relatively stable communication pattern indicating a person’s communication preferences in social interactions (McFarland et al. 2006). Paralleling the distinction between relational and functional customer orientation, two customer communication styles are particularly relevant: interaction orientation and task orientation. We define interaction orientation as a customer’s tendency to socialize with a salesperson in sales conversations. Task orientation refers to a customer’s tendency to focus on the buying task and to be highly goal-oriented.

Regarding product-specific factors, we investigate the potential moderating influence of product individuality, importance, complexity, and brand strength. We define product individuality as the degree to which a supplier’s products are customized to meet specific needs of the customers (Syam and Kumar 2006). Product importance is defined as the general impact of a supplier’s products on customer goal achievement (McQuiston 1989). Product complexity is defined as the degree to which specific expertise is necessary to be able to evaluate a supplier’s products (McQuiston 1989), whereas brand strength is defined as the degree to which a brand is superior relative to competitive brands (François and MacLachlan 1995).

Hypotheses development

Moderating effects of customer characteristics

It is the key objective of this study to investigate the effect of characteristics of the purchasing situation on customer orientation effectiveness. Therefore, the hypotheses proposed below focus on moderator effects. In this section, we will propose a reasoning regarding the effects of interaction orientation and task orientation on the customer orientation-loyalty link.

Generally, a person with an interaction orientation is interested in establishing strong personal relationships in social interactions (Williams and Spiro 1985). “The buyer or the seller motivated by the interaction-oriented style is often compulsive in first establishing a personal relationship with the other person and then only getting involved in the specific content of the interaction” (Sheth 1976, p. 385). Thus, customers with a pronounced interaction orientation highly value salesperson behaviors that correspond to the salesperson’s role as a friend. In other words, with highly interaction-oriented buyers, a salesperson’s relational customer orientation may support the formation of a trustworthy, personal relationship with customers, leading to an increase in customer loyalty (Macintosh and Lockshin 1997).

At the same time, customers with a low interaction orientation are not likely to be very receptive to salespeople’s attempts at building a personal relationship. Instead, they will tend to expect the salesperson to behave in a way that corresponds to his or her role as a businessperson. Given these expectations, it is more probable that they will perceive salesperson attempts at establishing a personal relationship as a nuisance (e.g., Fournier et al. 1998) or even as insincere, which may prompt negative reactions (Hennig-Thurau et al. 2006). Consequently, for customers with a low interaction orientation, the effect of relational customer orientation on customer loyalty is less pronounced and may even be negative.

Task-oriented customers are highly goal-oriented in sales conversations and prefer to accomplish the buying task as efficiently as possible (McFarland et al. 2006). Here, we expect a functional customer orientation to have an above-average effect on customer loyalty with task-oriented customers because it matches their communication preferences (Williams et al. 1990). In particular, by precisely determining a customer’s needs and providing product-related facts that are relevant for the customer, a salesperson comprehensively assists the customer in satisfactorily completing the buying task. Thus, a task-oriented customer may strongly appreciate a salesperson’s help in making a satisfactory purchase decision and may reward those efforts with stronger loyalty intentions. This leads us to the following hypotheses:

  1. H1a:

    A customer’s interaction orientation has a moderating effect on the link between relational customer orientation and customer loyalty, such that relational customer orientation is more strongly linked to customer loyalty if a customer’s interaction orientation is high.

  2. H1b:

    A customer’s task orientation has a moderating effect on the link between functional customer orientation and customer loyalty, such that functional customer orientation is more strongly linked to customer loyalty if a customer’s task orientation is high.

Moderating effects of product characteristics

In the following, we argue that specific product characteristics influence a customer’s expectations regarding the salesperson’s appropriate role and consequently the effectiveness of functional and relational customer orientation.

With regard to product individuality, we propose that customers are more likely to expect a salesperson to act according to the friend role if product offerings are highly customized. In particular, product customization creates a mutual dependency, because it requires specific investments from both parties (e.g., Ghosh and John 1999). For instance, customers need to invest considerable time to get the supplier to understand their requirements (e.g., Franke et al. 2009), whereas suppliers face investments such as employee trainings or modifications of established production processes (e.g., Ganesan 1994). As a result, both parties find themselves in a relationship, where a “solidarity norm manifests itself in the form of a ‘we’ feeling or shared identity between the exchange partners” (Rokkan et al. 2003, p. 213). This norm closely resembles the “logic of appropriateness” followed in close personal relationships, which emphasizes cooperative behavior (Heide and Wathne 2006).

At the same time, when selling standardized products, relational customer orientation is likely to be less effective. In this case exchanges are much more likely to follow a transactional logic with little interdependency between buyers and suppliers (Lusch and Brown 1996), often carried out on online marketplaces (Grewal et al. 2001). Thus, there is little room for personal exchanges and personal relationships to develop. Therefore, relational customer orientation is likely to be more effective, if a salesperson sells highly individualized products as opposed to standardized products.

Given that it is more important to correctly identify customer needs if products are highly customized as opposed to standardized, it is also likely that functional customer orientation will be more effective in creating customer loyalty for highly individualized products. In particular, by assisting customers in the purchase process, focusing on their needs, and drawing attention to the relevant product features and advantages, salespeople using a functional customer orientation are more likely to arrive at true solutions for the customer (Tuli et al. 2007). As a result, the perceived utility of the product is higher (e.g., Dellaert and Stremersch 2005), which leads to higher customer loyalty (e.g., Lam et al. 2004). Thus, we hypothesize the following:

  1. H2a:

    Product individuality has a moderating effect on the link between relational customer orientation and customer loyalty, such that relational customer orientation is more strongly linked to customer loyalty if product individuality is high.

  2. H2b:

    Product individuality has a moderating effect on the link between functional customer orientation and customer loyalty, such that functional customer orientation is more strongly linked to customer loyalty if product individuality is high.

Product importance is associated with a customer’s functional risk. Functional risk describes the magnitude of adverse consequences of buying an inappropriate product and a buyer’s uncertainty as to whether a product or service will meet performance requirements (Dowling 1986). More specifically, a customer’s functional risk will be greater for highly important products than for less important products. With highly important products, the adverse consequences of buying an inappropriate product are more substantial, such as monetary losses due to replacement costs or, in business-to-business settings, due to production downtimes (Bloch and Richins 1983; McQuiston 1989). As a result, with highly important products, customers will have higher information needs with regard to product features and advantages that satisfy their requirements (Murray 1991). Accordingly, with highly important products, customers are more likely to expect the salesperson to act in his or her role as a businessperson. Thus, they will place an above-average value on a salesperson’s functional customer orientation and may reward efforts to reduce their functional risk with higher loyalty intentions.

Regarding the impact of product importance on the effectiveness of relational customer orientation, a reverse effect can be expected. When purchasing highly important products, customers are likely to be particularly wary regarding any attempts to instrumentalize personal relationships for business purposes. Also, firms are particularly vulnerable to possible conflicts of interests of their purchasing employees arising through personal relationships with supplier employees. Consequently, when purchasing important products, it is more likely that firms implement formal routines to ensure that buying decisions are not based on personal interests of their employees (e.g., Handfield and Baumer 2006). This implies that for products that buyers perceive as important, the effectiveness of relational customer orientation is lower. At the same time, when purchasing products of less importance, where functional considerations play a smaller role in choosing the supplier, a strong personal relationship with the salesperson could become a decisive argument to remain in a business relationship. Hence, the effectiveness of relational customer orientation is higher. There, we hypothesize:

  1. H3a:

    Product importance has a moderating effect on the link between relational customer orientation and customer loyalty, such that relational customer orientation is more strongly linked to customer loyalty if product importance is low.

  2. H3b:

    Product importance has a moderating effect on the link between functional customer orientation and customer loyalty, such that functional customer orientation is more strongly linked to customer loyalty if product importance is high.

Product complexity is a further characteristic that influences risk perceptions. Compared to simple products, products that need a great deal of explanation require more of a customer’s cognitive resources (Thompson et al. 2005). Hence, a customer’s functional risk may be larger with complex products, as the customer has more difficulty to understand the product, its features, and potential applications. Thus, with increasing product complexity, we propose that customers face greater uncertainty as to whether a product meets their needs. Consequently, they have a higher need for specific expertise to reduce their uncertainty (McQuiston 1989). Thus, customers purchasing complex products will value a salesperson’s functional customer orientation more highly, leading to a stronger impact of functional customer orientation on customer loyalty with complex products than with simple products.

At the same time, if—as is the case with complex products—customers expect the salesperson to act as a businessperson, rather than a friend or close acquaintance, they will be less receptive (and maybe even resistant) to a salesperson’s relational behaviors. This is particularly so because the difficulties in evaluating complex products make customers more susceptible to missing hidden issues with the product, which strongly reduces their confidence (Heitmann et al. 2007). In this situation, a salesperson’s attempts at establishing a personal relationship with the customer may easily be perceived as an attempt to distract from the real issues at hand. In contrast, regarding simple products customers expend less energy processing product-related facts and focus more on the “periphery” of the purchase situation (Andrews and Shimp 1990). Thus, with regard to loyalty intentions, we expect customers to place relatively more weight on relational issues than on functional issues in simple purchase situations. This leads to the following hypotheses:

  1. H4a:

    Product complexity has a moderating effect on the link between relational customer orientation and customer loyalty, such that relational customer orientation is more strongly linked to customer loyalty if product complexity is low.

  2. H4b:

    Product complexity has a moderating effect on the link between functional customer orientation and customer loyalty, such that functional customer orientation is more strongly linked to customer loyalty if product complexity is high.

Brand strength is the fourth product characteristic considered in this study. Strong brands enjoy a high level of brand awareness and strong, favorable, and unique brand associations, such as superior product quality and beneficial product attributes. As a result, the brand itself provides customers with valuable information about the product, while reducing the perceived risk associated with a purchase (e.g., Erdem et al. 2006). Therefore, customers of low strength brands are likely to perceive the added value of functional customer orientation as higher. This is also consistent with the finding of Sharma (1990) that for product evaluations customers only consider salesperson credibility as information when buying a weak brand.

At the same time, as customer information needs are higher for low strength brands (Erdem and Swait 1998), there is a greater risk that customers will perceive salesperson attempts to establish a personal relationship as insincere. In particular, not unlike the situation when salespeople are selling complex products, a strong reliance on relational behaviors may be interpreted as an attempt to avoid addressing important issues regarding products with low brand strength. Thus, for weak brands relational customer orientation is not likely to strongly influence customer loyalty and may even have a negative effect.

Customer expectations regarding the salesperson’s role are likely to change for strong brands. In particular, strong brands typically also provide an emotional value (Keller 1993), even in B2B contexts (Lynch and de Chernatony 2004). These emotions associated with strong brands also influence customer expectations regarding salesperson behavior, as frontline employees in general are perceived as key representatives of a brand (Morhart et al. 2009). Thus for strong brands, customers are more likely to expect affective salesperson behaviors, such as establishing a personal relationship with the customer. As a result, in this situation, relational customer orientation is likely to have a stronger impact on customer loyalty. This leads us to the following hypotheses:

  1. H5a:

    Brand strength has a moderating effect on the link between relational customer orientation and customer loyalty, such that relational customer orientation is more strongly linked to customer loyalty if brand strength is high.

  2. H5b:

    Brand strength has a moderating effect on the link between functional customer orientation and customer loyalty, such that functional customer orientation is more strongly linked to customer loyalty if brand strength is low.

Methodology

Collection of triadic data

As already indicated, the focal constructs of our study relate to three hierarchical levels—the sales unit level, the salesperson level, and the customer level. Accordingly, to test our hypotheses on a broad empirical basis, we conducted a large-scale survey among sales managers, sales representatives, and customers. To obtain those data, we invited companies from different industries to participate in the study. We first contacted chief executives from various companies and asked them to cooperate on this research project. As incentives, we offered each company an individualized report of the results of our study (including benchmark analyses) and a workshop to discuss options for improvement. Twelve companies agreed to participate, each having multiple sales units and operating mainly in B2B markets in six industries (financial services, logistics, health care, machine building, chemicals, and information technology).

We collected data for our study in two steps within each participating sales unit. First, we surveyed sales managers responsible for the participating sales units and their sales representatives. After informing them about the goals and scope of the research project, we mailed questionnaires with a request for completion within 4 weeks. We obtained usable responses from 56 sales managers (a response rate of 84.9%) and 195 sales representatives (a response rate of 67.2%).

In a second step, we obtained the contact data of, on average, ten customers per participating sales representative. This allowed us to survey multiple customers per sales representative. To identify key informants in the customer organizations, the participating suppliers employed one of two approaches. First, in most supplier firms, customer names and addresses were selected at random from central CRM databases. Second, in companies where this approach could not be employed due to lack of adequate databases, salespeople were directly asked to provide contact data for ten randomly selected customers.

After informing these customers by mail about the goals of the study, we contacted them by telephone to obtain their responses to our survey questions, resulting in usable responses from 538 customers. Data from the three sources were matched using code numbers. Table 1 presents respondents’ characteristics.

Table 1 Sample characteristics
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Measure development and assessment

We adapted most of the scales used in this study from previous research. We pretested the resulting questionnaires for sales managers, sales representatives, and customers and further refined them on the basis of comments obtained during the pretest. A complete list of items (including previous applications of the scales) appears in the “Appendix”.

We used salesperson data to measure the components of customer orientation. We determined a salesperson’s functional customer orientation with nine items adapted from Saxe and Weitz (1982), Schurr et al. (1985), and Dubinsky (1980). To measure relational customer orientation we adapted four items from Donavan et al. (2004).

We used customer data to evaluate customer loyalty. Consistent with Zeithaml et al.’s (1996) definition of customer loyalty, our measure of customer loyalty consists of three facets—customer intention to repurchase, customer intention to increase share of wallet, and customer word of mouth—and we measured each facet using two items adapted from Zeithaml et al. (1996).

Regarding moderator variables, we used evaluations from the participating customers to measure a customer’s communication style. We determined a customer’s interaction orientation with three items and a customer’s task orientation with four items. These items were adapted from the work of McFarland et al. (2006). We also asked the participating sales managers to assess characteristics of the products they bring to market. We used sales manager evaluations because we intended to investigate the impact of characteristics of products typical of the respective sales unit. We measured product individuality with four items, with item generation inspired by Stump (1995). We determined product importance with three items adapted from Porter et al. (2003) and product complexity with four items adapted from McQuiston (1989). Finally, on the basis of previous research (e.g., Keller 1993), we asked participating sales managers to evaluate the general strength of their product brands in comparison to their competitors.

Owing to the heterogeneous nature of the cross-industry sample, we included a number of control variables in our model to account for potential structural differences in customer loyalty. In particular, we controlled for a potential impact of product type—that is, whether customers purchase services or physical goods—by using a dummy variable with values of 1 for services and 0 for physical goods. Using single-item measures, we included the length of a customer’s relationship with the supplier and account manager as further control variables. As the distributions of these two variables were highly skewed, we applied a logarithmic transformation before data analysis (e.g., De Luca and Atuahene-Gima 2007). A further control variable was a customer’s perceived status at his or her supplier. Finally, we controlled for the impact of the size of a customer’s organization with two items—number of employees and total sales. Table 2 provides an overview of correlations and measurement information relating to the focal constructs of our study.

Table 2 Correlations and measurement information
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To assess measure reliability and validity of our constructs, we ran confirmatory factor analyses for each factor individually using Mplus 4.1 (Muthen and Muthen 2006). Overall, the results indicate good psychometric properties for all constructs. More specifically, all composite reliabilities are well above the recommended threshold of .70 (see Table 2). Furthermore, with few exceptions, item reliabilities are above the recommended value of .40 (Bagozzi and Baumgartner 1994; see “Appendix”).

Results

Owing to the hierarchical structure of our data—customers are nested in their account managers that are themselves nested in their sales units directed by their sales managers—we applied multilevel regression using the MLwiN software (Version 2.10; Rabash et al. 2009). In this context, we centered all constructs on their grand mean.

To test our hypotheses, we used a stepwise approach. In a first step, we estimated a basic model that includes only direct, average effects of the constructs considered in our study, without any cross-level interaction effects. In a second step, to test H1a and H1b we included interaction effects between level 1 (a customer’s communication style) and level 2 variables (a salesperson’s customer orientation) in our regression model. In a final step, to test H2a to H5b we considered interaction effects between level 2 (a salesperson’s customer orientation) and level 3 variables (general characteristics of a supplier’s products). Table 3 shows the results of our hypotheses testing.

Table 3 Results of multilevel regression
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Results of the basic model already indicate that functional and relational customer orientation have differential effects on customer loyalty. More specifically, there is a strong effect of a salesperson’s functional customer orientation (b = .255, p < .01) on customer loyalty, whereas there is no such effect of relational customer orientation (b = .034, p > .05).

At the same time, the results from the additional models strongly corroborate our moderator hypotheses. With regard to the influence of a customer’s communication style, a positive interaction effect exists between a salesperson’s relational customer orientation and a customer’s interaction orientation (b = .056, p < .05). Thus, our results support H1a. Moreover, consistent with H1b, the interaction effect between functional customer orientation and a customer’s task orientation is significant and positive (b = .209, p < .05).

With regard to the moderating influence of general characteristics of a supplier’s products on customer orientation effectiveness, a positive interaction effect exists between product individuality and a salesperson’s relational customer orientation (b = .082, p < .05), thus supporting H2a. However, our data do not support H2b, as we do not find a significant interaction effect between product individuality and functional customer orientation (b = .020, p > .05). Furthermore, there is no support for H3a, because we do not find a significant interaction effect between product importance and relational customer orientation (b = .030, p > .05). On the other hand, H3b is supported, because our results show a strong and positive interaction effect between product importance and functional customer orientation (b = .318, p < .05). Moreover, the interaction effect between product complexity and relational customer orientation is significant and negative (b = −.070, p < .05), although the interaction effect between product complexity and functional customer orientation is not significant (b = −.141, p > .05). Thus, we find empirical support for H4a, but not for H4b. Finally, our results reflect a positive interaction effect between relational customer orientation and brand strength (b = .117, p < .05) and a negative interaction effect between functional customer orientation and brand strength (b = −.293, p < .01). Thus, the data support H5a and H5b.

Discussion

Research issues

As investigators generally consider a firm’s customer orientation to be an important driver of corporate success (e.g., Deshpandé et al. 1993), there is extensive research on direct, linear effects of salesperson customer orientation on several performance indicators. However, this rich stream of research is largely silent with regard to moderating influences on the effectiveness of customer-oriented behaviors (Franke and Park 2006). This is surprising, because customer expectations regarding salesperson behaviors are likely to depend on the specific situation of the purchase. Against this background, this study analyzes the effect of situational variables on the effectiveness of salesperson customer orientation. It advances academic knowledge in several ways.

First, this study is one of the first to explore how characteristics of the purchase situation moderate the effectiveness of customer orientation. We find that customer communication styles as well as product characteristics have a substantial influence on the effectiveness of customer oriented behaviors. Thus, these results suggest that the key implication of the adaptive selling literature also applies to salesperson customer orientation. It suggests that the effectiveness of specific sales behaviors is contingent on the sales situation (Spiro and Weitz 1990). While previous research typically considers the concepts of customer orientation and adaptive selling separately, the results of this study shed light on how customer-oriented behaviors should be adapted given a specific purchase situation.

Against this background, the findings of this study suggest that researchers (as well as practitioners) should much more actively question a tacit assumption of most previous research on salesperson customer orientation, namely that customer orientation is universally effective. Moreover, while previous research on situational influences on customer orientation effectiveness has mainly looked at salesperson characteristics (e.g., Stock and Hoyer 2005; Wachner et al. 2009), our results suggest that other characteristics of the purchase situation may even be more important. In addition to the customer communication styles and product characteristics considered in this study, future research could look more closely at the impact of relationship characteristics (e.g., relationship age or customer-salesperson similarity). It would also be very interesting to consider intercultural differences. For instance, the importance of “Guanxi” in China is likely to increase the effectiveness of relational customer orientation (e.g., Xin and Pearce 1996).

In this context, it is worth emphasizing that our study is among the very first to consider branding as a context factor that may affect salesperson-customer interactions. In particular, we find that brand strength enhances the effectiveness of relational customer orientation, whereas it reduces the effectiveness of functional customer orientation. Therefore, future research should address the impact of other drivers of brand equity, such as the uniqueness of the brand associations or brand awareness (Keller 1993). Moreover, a very interesting future study could also look at the direct effect of branding variables on salesperson behaviors.

Second, the growing emphasis on establishing long-term buyer–seller relationships strongly favors the development of close personal relationships between salespeople and employees in customer organizations. Thus, salespeople often play two roles in interactions with customers: the role of a businessperson and the role of a friend (Heide and Wathne 2006). Despite these changes, research on salesperson customer orientation typically employs variations of the scale proposed by Saxe and Weitz (1982), i.e., nearly 30 years ago. This conceptualization views customer orientation as a set of functional behaviors, such as customizing an offer. Drawing on role theory, we advance and test a model, where in addition to this type of customer orientation, a second type of customer orientation is considered, namely relational customer orientation. Thus, in this study we modify the conceptualization of customer orientation to account for the challenges of today’s sales environment.

In this context, it is worth emphasizing that this conceptualization does not imply that customer orientation is either functional or relational in nature. Thus, salespeople cannot be compartmentalized in a manner, where there are functionally customer-oriented salespeople and relationally customer-oriented salespeople. Instead, salespeople are likely to almost always employ a blend of the two orientations. This expectation is based on both, theoretical considerations and empirical findings. More specifically, role theory predicts that individuals often need to play multiple roles at once, to meet the expectations of others. Empirically, we find a correlation of r = .22 between functional and relational customer orientation. Thus, salespeople who employ one strategy may also employ the other, although there is no necessary association between the two.

Third, our empirical analysis confirms that it is worthwhile to make the distinction between relational and functional customer orientation. In particular, as hypothesized, the effectiveness of functional customer orientation is differently influenced by context variables than the effectiveness of relational customer orientation. Here, Fig. 3 provides more information, because it visualizes the overall effects of a salesperson’s functional or relational customer orientation on customer loyalty depending on the values of the moderating variable.

Fig. 3
figure 3

Graphical illustration of the moderating influence of communication style and product characteristics on the effects of functional and relational customer orientation on customer loyalty

Full size image

As Fig. 3 shows, the effects of a salesperson’s functional or relational customer orientation strongly depend on characteristics of the purchase situation. In particular, the impact of a salesperson’s functional customer orientation on customer loyalty is more pronounced with task-oriented buyers, weak brands, and highly important products. At the same time, the salesperson’s relational customer orientation supports the creation of customer loyalty with interaction-oriented buyers, strong brands, customized products, and less complex products.

What’s intriguing about Fig. 3 is that some of the slopes are slightly negative, particularly with regard to relational customer orientation. Thus, in some situations, relational customer orientation may even reduce customer loyalty. Based on role theory and recent applications to the literature on salesperson-customer interaction (e.g., Price and Arnould 1999), we have predicted these negative effects at numerous instances throughout the paper. Our recurrent theme is that if customers expect the salesperson to exhibit behavior typical for their role as a businessperson, they may be wary of salesperson attempts to establish a personal relationship. Particularly, in these situations they may view relational behaviors as an attempt to distract them from more urgent issues with the offering. Additionally, if salespeople attempt to establish personal relationships in situations where they are seemingly at a disadvantage regarding functional arguments, this may be misconstrued as an attempt to use a personal relationship to maximize economic gains. However, as this does not follow the “logic of appropriateness” that is expected to guide personal relationships (Heide and Wathne 2006), it will generally induce negative reactions and reduce commitment to the relationship as a whole.

It is worth noting that Fig. 3 reveals that there are also many situations when relational customer orientation has a positive effect on customer loyalty. In fact, it is highly likely that these positive and negative effects cancel each other out across the entire sample, which would explain why we only find a very weak main effect of relational customer orientation, but many significant interactions.

It is important to discuss how these results relate to recent research on establishing relationships with customers (e.g., Cannon and Perreault 1999; Hunter and Perreault 2007; Palmatier et al. 2007a, b). In particular, these studies typically find positive effects of relationship-building activities. At the first glance, this might seem to contradict our results. However, these studies mostly focus on behaviors that could be classified as functional rather than relational in the terminology of our study. For instance, the “relationship-enhancing activities” construct in the Palmatier et al. (2007b) study comprises behaviors such as “This customer often receives special reports and/or information” or “Our policies and procedures are often adapted for this customer.” Thus, our finding that functional customer orientation has a strong positive main effect on customer loyalty is consistent with the results from this research stream. In other words, while our results do imply that it is advisable to strictly distinguish between the personal and professional level of buyer–seller relationships, they do not question the importance of the concept as a whole.

Against this background, we also encourage researchers to continue distinguishing between the functional and relational components of customer orientation. For example, previous research on the effects of personality traits on customer orientation has used an aggregated construct (Brown et al. 2002). Given the differential effects of functional and relational customer orientation, we recommend that researchers investigate which personality traits may lead to higher functional customer orientation (e.g., an employee’s conscientiousness) and to higher relational customer orientation (e.g., an employee’s agreeability).

It needs to be noted that we do not find support for some of our moderating hypotheses: Other than product importance, product individuality and product complexity have no impact on the effectiveness of functional customer orientation. A possible explanation is that product importance affects the magnitude of adverse consequences attached to buying an inappropriate product. This is an important element of customer perceived risk, but it is in all likelihood not associated with product individuality and product complexity. Thus, maybe the effectiveness of functional customer orientation mostly hinges on this type of risk associated with a purchase.

Fourth, while previous research focused on potential effects of customer orientation on outcomes like employee performance and customer satisfaction (e.g., Donavan et al. 2004; Schneider et al. 2005), empirical studies investigating the direct impact of customer orientation on customer loyalty are relatively sparse. Our study provides deeper insight into the relationship between customer-oriented behaviors and customer loyalty. These findings are of particular relevance because customer loyalty is a key element in linking customer attitudes to sales outcomes (Zeithaml et al. 1996). Therefore, increases in customer loyalty represent a strong indicator that customer orientation pays off. This way, our study’s results may also help to explain the mixed findings of previous research regarding the effect of customer orientation on salesperson performance (Jaramillo et al. 2007). While some studies found a positive relationship between customer-oriented selling and salesperson performance (e.g., Boles et al. 2001), others failed to do so (e.g., Howe et al. 1994). The major reason for these inconsistent findings may be that, in some contexts, the benefits of customer orientation (e.g., increases in customer referrals, share of wallet, and, consequently, sales performance) offset its costs (e.g., salespeople’s time investments), while in other situations they do not (Saxe and Weitz 1982). Indeed, our empirical results show that the selling situation strongly determines whether the benefits outweigh the costs of customer orientation.

Finally, to account for the hierarchical structure of our data, we relied on multilevel regression. This approach is in line with a growing body of research using multilevel modeling in sales and service contexts (e.g., Liao and Chuang 2004; Wieseke et al. 2008). As a hierarchical composition is typical for sales contexts—customers are nested within sales representatives that are themselves nested within sales managers, etc.—we encourage academics to apply this technique to analyze cross-level effects. In this study we have measured customer communication styles and customer loyalty at the customer level, salesperson customer orientation at the salesperson level, and product characteristics at the managerial level.

It must be noted that measuring product characteristics through managers does not account for heterogeneity in customer perceptions of product importance and product complexity. Thus, these measures need to be interpreted as managerial perceptions of their “typical” customers. While it is likely that these impressions form the basis of many managerial decisions regarding the design of the sales environment, this data collection approach may justifiably be viewed as a limitation of this study. Therefore, future research should address the impact of customer product perceptions on the effectiveness of salesperson customer orientation.

Managerial implications

The results of our study question at least two widely held tacit assumptions about customer orientation, namely that it is universally effective and cannot have negative effects. Our results suggest that these assumptions are not fully justified. Therefore we believe that they have a number of important implications for sales practice.

Our results show that the situational context is a strong driver of salesperson effectiveness. In particular, high levels of functional customer orientation are especially beneficial with task-oriented buyers, highly important products, and weak brands. Moreover, a relational customer orientation increases customer loyalty with interaction-oriented buyers, strong brands, and individualized products. This finding has important implications for the internal design of the sales environment, such as salesforce control systems. They should be designed to account for the specific blend of customer-oriented behaviors appropriate in a given sales unit (Anderson and Onyemah 2006). For instance, it could be worthwhile to establish behavioral targets emphasizing interaction content for salespeople selling weak brands, where targets referring to interaction quantity need to be emphasized more for salespeople selling strong brands.

This is particularly important for firms serving multiple markets. Here, instead of employing a “one size fits all” approach to salesperson-customer interactions, practitioners are advised to develop specific interaction models, depending on the characteristics of the customers and products in a specific market. Deiser (2009) describes how BASF (a firm with a very heterogeneous product portfolio) has implemented such an approach. They have developed six different “customer interaction models” (CIMs). Each of these CIMs “follows a different relationship rationale from none to low intensity (trader/transactional supplier) to a highly interdependent one (customized solutions provider/value chain integrator)” (Deiser 2009, p. 109). For each sales unit the appropriate CIM is identified and then used to derive specific implications for designing the sales environment with regard to aspects such as sales force organization and sales force compensation.

In this context, practitioners need to pay special attention to relational customer orientation. We find that relational approaches are very ineffective and may even harm customer loyalty in some situations. This is particularly the case when salespeople are in a relatively weak competitive position, e.g., when selling complex and/or highly standardized products, while brand strength is low. In these situations, relational behaviors are more likely to be perceived as purely instrumental, which may cause negative reactions. Hence, we advise practitioners to be very cautious when employing relational as opposed to task-related behaviors. Also, in trainings, salespeople’s awareness for first signs of negative reactions to relational approaches (e.g., evasive reactions to personal questions) should be sharpened.

However, even in situations where relational behaviors do increase customer loyalty, they carry additional risks. First, they are likely to increase customer commitment to the salesperson (Jones et al. 2008), which increases the risk of losing the customer when the salesperson leaves the organization (Palmatier et al. 2007b). Second, they will also increase salesperson commitment to the customer (Siders et al. 2001), which may well lead to unwelcome consequences, such as exaggerated price concessions. Third, for many buyer firms, close personal relationships of a purchasing employee with a salesperson constitute a “conflict of interest” (Handfield and Baumer 2006), which may well result in loosing instead of winning deals.

Thus, beyond raising their salespeople’s awareness regarding possible negative outcomes of relational customer orientation, firms are also advised to manage the risk associated with the success of this strategy. For instance, to reduce the risk of losing important customers if a salesperson leaves the firm, firms should seek to introduce multiple employees to the customer using informal encounters (Bendapudi and Leone 2001). To prevent salespeople from making exaggerated price concessions to customers, firms could consider reducing the pricing authority of the salesperson or linking variable compensation to achieved margins instead of sales.