When do customers perceive customer centricity? The role of a firm’s and salespeople’s customer orientation

Abstract

The concept of customer centricity is frequently debated by sales and marketing researchers and practitioners. However, to date no validated scale exists that measures to what extent customers perceive companies as customer centric. Against this backdrop, drawing on prior literature, qualitative interviews, and a customer survey (N = 246), the authors develop and validate a measurement scale for perceived customer centricity. In addition, using matched survey and financial data from industrial customers (N = 1,089), the authors examine antecedents and consequences of perceived customer centricity. Results show that customers perceive firms as customer centric if the supplier is customer oriented on both the overall firm level and the salesperson level. Furthermore, perceived customer centricity is strongly linked to customers’ loyalty intentions and objective sales revenue, particularly if customers perceive a firm to exhibit high prices. Thus, this article equips managers with a validated and easy-to-use measurement that allows monitoring a firm’s progress toward customer centricity.

Keywords:

• customer centricity
• measurement scale development
• firm’s customer orientation
• salesperson customer orientation

To achieve a competitive advantage, companies increasingly strive to be perceived by their customers as customer centric (e.g., Selden and MacMillan 2006; Shah et al. 2006; Lee et al. 2015). For example, Amazon states in its marketing communication that it aims to be Earth’s most customer-centric firm (Amazon 2019). Similarly, Hewlett Packard and Fresenius emphasize that they put their customers first in everything they do (Hewlett Packard 2019; Fresenius 2019). Furthermore, the number of Google searches for the term “customer centricity” more than doubled from 2008 to 2018 (Google Trends 2019), and several prestigious business schools included courses on customer centricity in their executive education programs (e.g., Kellogg 2019; Stanford 2019).

Managers’ growing interest in being perceived as customer centric is reflected by academic research. Customer centricity is defined as putting customers’ interests at the center of a firm’s actions (e.g., Burmann, Meurer, and Kanitz 2011; Gummesson 2008a, b; Shah et al. 2006; Sheth, Sisodia, and Sharma 2000; see also Table 1) and can be achieved by implementing customer-centric organizational structures (e.g., Galbraith 2005; Shah et al. 2006; Lamberti 2013), customer-centric information technologies (e.g., Wagner and Majchrzak 2006; Waisberg and Kaushik 2009), and customer-centric marketing strategies (e.g., Lenskold 2004; Gurău, Ranchhod, and Hackney 2003; Sheth, Sisodia, and Sharma 2000). Implementing such changes to instill customer centricity can improve firm performance (e.g., Sheth, Sisodia, and Sharma 2000; Fader 2012; Lee et al. 2015; Crecelius et al. 2019; see Figure 1).

Figure 1. Extant research on customer centricity and focus of our paper.

Table 1. Definitions of customer centricity.

Reference	Definition of customer centricity	Unit of analysis	Focus on customers’ interests	Active prioritization of customers	Measure perceived by customer
Bolton (2004)	Customer-centric business processing: All business processes and all individuals are focused on identifying and meeting the needs of customers	Firm	✓	✓
Burmann, Meurer, and Kanitz (2011)	Customer centricity: Focusing all marketing activities and processes of the corporation on the customer	Firm	✓	✓
Cheng and Dogan (2008)	Customer-centric marketing: Refers to the practice in which “marketers assess each customer individually and make a determination of whether to serve that customer directly or via a third-party,” and one that “focuses on the needs, wants, and resources of customers as the starting point of the planning process”	Marketing	✓
Crecelius et al. (2019)	Firm's customer-centric structure: Degree to which the firm’s business units are aligned to distinct customer groups	Firm	✓
Frankenberger, Weiblen, and Gassmann (2013)	Solution customer centricity: Degree to which a company focuses on customers in the joint delivery of solutions	Firm	✓
Jayachandran et al. (2005)	Customer-centric management system: Consists of structural aspects that ensure that organizational actions are driven by customer needs and not by the internal concerns of functional areas	Firm	✓	✓
Kumar, Venkatesan, and Reinartz (2008)	Customer-focused sales campaigns: Reflect sales campaigns where salespeople coordinate their contact strategy across product categories, salespeople, and time to address customers’ underlying, dynamically changing needs	Sales campaign	✓
Lamberti (2013)	Customer-centric firm: Manifests a continuous interaction with customers aimed at generating intelligence and at understanding customer explicit and hidden needs; a systematic involvement of customers in marketing and NPD decision making; strongly coordinated organizational structures, gathering and sharing information about the customer responsively, and managing the interface all along the touch-points; and the presence of a supply chain coordinated with the firm and able to face the customization required by customers	Firm	✓
Lee et al. (2015)	Customer-centric structure: An organizational design that aligns each business unit with a distinct customer group	Firm	✓
Lee, Sridhar, and Palmatier (2017)	Customer-aligned structural designs: Structures that seamlessly align their internal units with their external customers	Firm	✓
Liang and Tanniru (2006)	Customer-centric information system: An information system that is able to configure four major components – customer, process, technology, and product/service – to satisfy a customer need	Information system	✓
Shah et al. (2006)	Customer centricity: All decisions start with the customer and opportunities for advantage	Firm	✓	✓
Sheth, Sisodia, and Sharma (2000)	Customer-centric marketing: Understanding and satisfying the needs, wants, and resources of individual consumers and customers rather than those of mass markets or market segments	Firm	✓
This article	Perceived customer centricity: The degree to which a customer perceives a firm to put customers’ interests at the center of all of its actions	Firm	✓	✓	✓

Visible in this short depiction of existing literature, extant studies have mostly adopted a firm-centered view on customer centricity, examining effective management levers to enhance customer centricity. Interestingly, however, extant research has not conceptualized and empirically explored customers’ perceptions of customer centricity. More specifically, to our best knowledge, no study has developed a validated scale that measures customers’ perceptions of customer centricity, which we define as the degree to which customers perceive a firm to put customers’ interests at the center of all of its actions. We consider this omission as striking for two reasons.

First, without a validated scale, sales and marketing managers cannot monitor how their intentions and measures to develop customer centricity in fact translate into customer perceptions. Importantly, the difference between a firm’s intended customer centricity and the customer centricity perceived by the customer is essential: While firms may make honest efforts to act in a customer-centric manner (e.g., by adjusting organizational structures, information technology, or marketing strategies), these efforts may not necessarily pay off, leading to stagnating customer perceptions of customer centricity. Thus, to track their progress in becoming customer centric, managers require a measurement they can readily employ in customer surveys. Given the nature of customer centricity, we consider it paradoxical if companies aim to improve customer centricity yet neglect to consider customers’ feedback on their progress.

Second, given the lack of a validated measurement scale, academics have been unable to analyze (a) the consequences and (b) the antecedents of perceived customer centricity. As to the first, improving our understanding of consequences of perceived customer centricity is necessary to evaluate whether setting customers’ perceptions of customer centricity as a firm objective is sensible (see the case of Amazon 2019). This notion follows Shah and colleagues (2006, 122), who suggested that “a major research stream relevant to customer centricity is warranted in the context of exploring its financial implications.” In addition, improving our understanding of antecedents of perceived centricity helps companies decide which measures to implement if they intend to be perceived as customer centric. We consider it particularly interesting to explore how salespeople, as key intermediaries between firms and customers, forge customers’ perceptions of a firm’s overall customer centricity. This question seems highly relevant considering that firms put substantive effort into orienting their sales departments to their customers (e.g., Lee et al. 2015) and sales managers regard articulating a solution that centers on customers’ needs as the most significant sales practice (CSO Insights 2017).

In summary, developing a validated scale of perceived customer centricity has merits both for academic research and for sales and marketing practice. Against this backdrop, we set out to develop and empirically validate a scale of customer centricity as perceived by customers. Building on established scale development and validation procedures (e.g., Churchill 1979; Gerbing and Anderson 1988; DeVellis 2003), our final measurement scale comprises six items that exhibit good convergent and discriminant validity. We then conceptualize potential antecedents and consequences of perceived customer centricity and test our hypotheses using survey data matched with firm records from 1,089 industrial customers. Results show that customers’ perceptions of a firm as customer centric are decisively driven by the firm’s customer orientation both on the firm level and on the level of individual salespeople. Furthermore, perceived customer centricity increases customers’ loyalty intentions and purchase volume, particularly if customers perceive the firm to exhibit high prices.

Our study makes three important contributions to academia. First, our study is the first to conceptualize customers’ perceptions of a firm’s customer centricity and provides a validated measurement scale. Future studies may employ this scale to deepen our understanding of customer centricity. Second, our study provides insights into consequences of customer centricity as perceived by customers. Seeing its effects on customer loyalty and sales revenue, our results imply that perceived customer centricity may in fact be an important addition to models exploring the effectiveness of customer centricity initiatives (e.g., Lee et al. 2015; Burmann, Meurer, and Kanitz 2011). Furthermore, by showing that perceived customer centricity is not equally beneficial for all customers, we contribute to literature that examines contingent effects of customer centricity (Frankenberger, Weiblen, and Gassmann 2013). Third, our study contributes to literature on how to implement customer centricity. While prior literature has particularly examined strategic decisions affecting organizational structures, information technology, and marketing strategies (e.g., Galbraith 2005; Waisberg and Kaushik 2009; Lenskold 2004), our study shows that customers’ perceptions of customer centricity crucially depend on specific behaviors of a firm and its salespeople.

For sales and marketing managers, our study provides three key recommendations. First, as perceived customer centricity increases sales revenue, managers should strive to establish that their customers perceive the firm as customer centric. This is especially true for firms with a high price positioning, for which perceived customer centricity most strongly increases sales revenue and customer loyalty. Second, to be perceived as customer centric, managers need to foster customer orientation both on the level of the firm and on the level of individual salespeople. Put differently, rather than trying to foster customer centricity through marketing communications, managers need to remind themselves that actions speak louder than words. Third, managers may use the measurement scale developed in our study to monitor the degree to which their firm is perceived as customer centric. The scale requires little effort to complete, yet has good psychometric properties, including predictive validity.

Conceptualizing perceived customer centricity

To anchor our conceptualization of perceived customer centricity in prior research, we provide a literature review on established definitions of customer centricity (see Table 1). While these definitions differ across studies, we identified three recurring themes that seem to be well-accepted characteristics of customer centricity: (1) the firm unit of analysis, (2) the focus on customers’ interests, and (3) the active prioritization of customers. In the following, we elaborate on these themes and subsequently use them to develop our own definition of perceived customer centricity.

First, most articles that we reviewed analyzed customer centricity as a phenomenon on the level of the firm (e.g., Sheth, Sisodia, and Sharma 2000; Shah et al. 2006; Crecelius et al. 2019). This means that extant research typically conceptualized firms (rather than specific functions or individuals within these firms) as the entities that exhibit customer centricity. Few studies conceptualized customer centricity on a functional level. For example, Cheng and Dogan (2008) focused on customer-centric marketing, Kumar, Venkatesan, and Reinartz (2008) investigated customer-focused sales campaigns, and Liang and Tanniru (2006) examined customer-centric information systems.

Second, most definitions emphasized that high customer centricity is characterized by a strong focus on addressing customers’ interests (e.g., Bolton 2004; Shah et al. 2006; Kumar, Venkatesan, and Reinartz 2008). Seeing that these interests are typically not universal for all customers, some works considered customer centricity to entail a customer-segment-specific consideration of customers’ interests (Burmann, Meurer, and Kanitz 2011; Frankenberger, Weiblen, and Gassmann 2013; Lee et al. 2015; Crecelius et al. 2019).

Third, some studies conceived customer centricity as entailing the active prioritization of customers and their interests over internal firm concerns (Jayachandran et al. 2005; Shah et al. 2006; Burmann, Meurer, and Kanitz 2011). For example, Shah et al. (2006, 115) stated that “all decisions start with the customer,” and Jayachandran et al. (2005, 179) understood a customer-centric management system as a management system where “actions are driven by customer needs and not by the internal concerns of functional areas.” Other studies however did not go this far and merely conceptualized customer centricity as adaptations of firm structures and processes to customer interests (e.g., Bolton 2004; Lee et al. 2015; Crecelius et al. 2019).

In summary, while extant studies differ in the nuances of definitions of customer centricity, three recurring themes across these definitions are the firm unit of analysis, focus on customers’ interests, and a prioritization of customers. Interestingly, however, none of these studies conceptualized customer centricity as a customer perception. To incorporate this notion and deduce a conceptual definition of perceived customer centricity as a first important step in this article, we merge the three themes of previous definitions with our notion of customer centricity as a customer perception (see Figure 2). Essentially, we define perceived customer centricity as the degree to which a customer perceives a firm to put customers’ interests at the center of all of its actions.

Figure 2. Definition of perceived customer centricity.

Two questions arise when considering the conceptualization of customer centricity. First, how is customer centricity different from customer orientation? Both concepts are similar because they can be conceptualized on the level of firms and on the level of subunits (e.g., salespeople, functions) and entail a strong focus on customer needs. A major difference between the concepts is the degree to which they entail a prioritization of customers. Whereas customer orientation is characterized as a tendency to meet customer needs (Brown et al. 2002), customer centricity may be viewed as wider reaching by giving customer interests priority and putting them at the center of all of a firm’s actions (Jayachandran et al. 2005; Shah et al. 2006; Burmann, Meurer, and Kanitz 2011).

Second, is perceived customer centricity a multidimensional or a unidimensional construct? For example, following Lamberti (2013), customer centricity may comprise three elements: customer intelligence generation, co-creation, and experience marketing; Shah et al. (2006) propose nine dimensions that differentiate a customer-centric approach, such as product positioning, organizational structure, and performance metrics. However, we deliberately decided for a unidimensional definition and measure for three reasons. First, our study focuses on customer perceptions rather than structural elements of a firm’s customer centricity. While customers may consolidate perceptions of multiple aspects to an overall perception of a firm’s customer centricity, we hold that such aspects would constitute antecedents rather than dimensions of perceived customer centricity. Second, we strove to develop a measure that is easy to apply for both academics and practitioners. However, measuring various dimensions limits the applicability of the scale due to an increasing number of measurement items. Furthermore, certain dimensions may be more or less relevant depending on a firm’s industry and target market (e.g., co-creation; Lamberti 2013), rendering benchmarking more difficult. Third, previous research questioned the validity of higher-order formative latent variables (e.g., Cadogan and Lee 2013; Lee and Cadogan 2013). Thus, we decided to refrain from defining and operationalizing perceived customer centricity as a multidimensional construct.

Study 1: Developing a customer centricity scale

In our first study, we developed a scale to measure customer centricity as perceived by customers in accordance with our definition. When developing the new scale of perceived customer centricity, we aimed for parsimony, readability, and simplicity of the measurement items (e.g., Churchill 1979; Gerbing and Anderson 1988; DeVellis 2003). Following prior research on scale development, we applied well-established scale development procedures (e.g., Churchill 1979; Gerbing and Anderson 1988; DeVellis 2003).

In the following three sections, we describe the measurement development process we adopted to generate a set of items for a measurement scale of perceived customer centricity: (1) generation of an initial measurement pool, (2) refinement and reduction of the initial item pool, and (3) quantitative measure validation of the remaining items (e.g., Churchill 1979; Gerbing and Anderson 1988; DeVellis 2003).

Generation of the initial item pool for measuring perceived customer centricity

In a first step, based on the procedure proposed by Churchill (1979), we generated an initial item pool for the measure of perceived customer centricity. We deduced items for our initial item pool from academic literature (e.g., Lee et al. 2015; Gummesson 2008a; Shah et al. 2006; Bolton 2004), managerial literature (e.g., Selden and MacMillan 2006; Rust, Zeithaml, and Lemon 2004; Galbraith 2005; Lenskold 2004), and firms’ vision statements (e.g., Amazon 2019; Hewlett Packard 2019; Fresenius 2019). Furthermore, we initiated discussions with four marketing academics of several institutions and asked them to propose items to measure customer perceptions of a firm’s customer centricity. After consolidating items from the three sources, our initial pool comprised 12 items. To reduce items during scale refinement, we followed the approach of DeVellis (2003). Specifically, “by using multiple and seemingly redundant items, the content that is common to the items will summate across items while their irrelevant idiosyncrasies will cancel out” and “you want considerable more than you plan to include in the final scale” (DeVellis 2003, 65–66).

Refinement and reduction of the initial item pool (Study 1.1 to Study 1.3)

In a second step, we pretested the initial pool of 12 scale items with 10 customers for comprehension, logic, and relevance (Study 1.1). This procedure is well established in scale development and in line with the procedure of Churchill (1979). We provided our definition of perceived customer centricity as well as the initial pool of items to our group of customers and asked them to rate each item concerning (1) its ability to assess the item, that is, whether they had the necessary insights to assess the item, (2) the comprehensibility and clarity of the item compared to the other items, and (3) the general ability of the item to measure a customer’s perceptions of a firm’s customer centricity. Drawing on the feedback of the group of customers, we made several adaptions to the initial items regarding wording and eliminated three of the initial 12 items.

In a third step, we presented the remaining items to a panel of four academic experts of marketing and sales faculties (Study 1.2) to examine face validity based on the same questions we asked the group of customers. Besides further adaptions regarding the wording of the items, the panel suggested eliminating one further item, resulting in a list of eight scale items.

In a fourth step, we administered the remaining scale items to a panel of four managers, from the consulting, automotive, banking, and online platform operator industries, for further screening of content and face validity (Study 1.3). We asked the managers to rate each item as clearly representative, somewhat representative, or not representative for a scale that measures the degree to which a customer perceives a firm to put customers’ interests at the center of all of its actions. We followed Bearden, Netemeyer, and Teel (1989), Tian and McKenzie (2001), and Zaichkowsky (1985) by selecting the items that remained in the scale. Specifically, to remain in the scale, an item had to be rated as clearly representative by all managers, or it had to be rated as clearly representative by at least three-quarters of the managers and as somewhat representative by the remaining managers. Using this well-established scale development process step, we eliminated two additional items. The remaining six items were considered for further refinement as described in the next process step. The remaining six items represent 50% of the initial large pool of items, which is still valued as suitable in scale development research (e.g., Babin, Darden, and Griffin 1994; Toncar et al. 2006; Yi and Gong 2013). Table 2 provides sample characteristics of our three different panels.

Table 2. Study 1: Sample characteristics.

	Criterion	Characteristics
Group 1: Customers (N = 10)	Age (years)	M	37.00
		SD	10.51
	Gender	female	40.00%
		male	60.00%
	Professional experience (years)	M	13.00
Group 2: Academics (N = 4)	Age (years)	M	34.00
		SD	10.03
	Gender	female	50.00%
		male	50.00%
	Professional experience (years)	M	5.50
Group 3: Managers (N = 4)	Age (years)	M	34.25
		SD	1.71
	Gender	female	25.00%
		male	75.00%
	Professional experience (years)	M	10.00

Note: M = mean; SD = standard deviation.

Study 2: Verifying the scale’s construct, convergent, and discriminant validities

Data collection and sample

We conducted Study 2 to test the construct validity, convergent validity, and discriminant validity of the perceived customer centricity scale developed in Study 1. Furthermore, we sought to verify that the scale and the concept of perceived customer centricity were understood by survey participants and customers. For this purpose, we administered a survey to 246 customers (mean age of 33 years, 45.5% female; detailed demographics in Table 3a) via a crowdsourcing Internet marketplace. Whereas the data for Study 1.1 to Study 1.3 were collected in Europe, data for Study 2 were collected from consumers in the United States. The participants were asked to think about the bank with which they conduct their main share of banking business. Then we asked participants to evaluate the bank using our newly developed items of perceived customer centricity as well as established and widely used measurements of a firm’s customer orientation (Im and Workman 2004; Narver and Slater 1990) and salespeople’s customer orientation (Saxe and Weitz 1982; Dwyer, Hill, and Martin 2000; Homburg, Müller, and Klarmann 2011a,b). All questions in Study 2 used 7-point Likert scales (a list of all items is provided in Appendix 1). In what follows, we describe the approach we used to analyze the data.

Table 3. Studies 2 and 3: Sample characteristics.

Criterion	Characteristics
a – Study 2 (246 U.S. consumers)
Age (years)	M	33.06
	SD	10.83
Gender	Female	45.50%
	Male	54.50%
Region	Northeast	15.90%
	Midwest	20.30%
	South	52.80%
	West	11.00%
Education	No college	3.70%
	Some college, but no degree	16.70%
	College graduate	65.90%
	Graduate school	13.80%
Income	<$40k	37.80%
	$40k to $80k	50.80%
	>$80k	11.40%
b – Study 3 (1,089 European B2B customers)
Number of employees	<50	94.00%
	50 to <100	2.80%
	100 to <500	2.40%
	500 to <1,000	.30%
	1,000 and more	.60%
Own revenue (not related to IT firm)	<10 m€	94.80%
	10 m€ to <25 m€	3.00%
	25 m€ to <50 m€	1.00%
	50 m€ to <100 m€	.40%
	100 m€ to <500 m€	.40%
	500 m€ to <1.000 m€	.20%
	1.000 m€ to <5.000 m€	.10%
	5.000 m€ and more	.20%
Revenue related to IT firm	<10 m€	99.00%
	10 m€ to <25 m€	.50%
	25 m€ to <50 m€	.10%
	50 m€ to <100 m€	.30%
	100 m€ to <5,000 m€	.00%
	5.000 m€ and more	.20%
EBIT in % (average past 3 years)	Negative	2.60%
	0% to <2%	6.20%
	2% to <4%	12.50%
	4% to <6%	10.80%
	6% to <8%	12.20%
	8% to <10%	17.10%
	10% to <12%	12.70%
	12% and more	25.90%
Position of respondent	Member of the Board	51.70%
	Head of business unit	18.60%
	Head of purchasing	7.50%
	Employee operational purchasing	5.20%
	Employee strategic purchasing	1.80%
	Others	15.10%
Length of business relationship with IT firm (years)	M	12.34
	SD	7.73

Note: M = mean; SD = standard deviation.

Tests for construct, convergent, and discriminant validities

To assess discriminant validity, we tested our measure of perceived customer centricity against well-established scales of a firm’s customer orientation and salespeople’s customer orientation. Because the concepts of customer orientation and perceived customer centricity are closely related, yet distinct (Lamberti 2013; Sheth, Sisodia, and Sharma 2000), we aimed to test our scale’s discriminant validity.

First, results of an exploratory factor analysis with Promax rotation including the six items of perceived customer centricity, four items of a firm’s customer orientation, and four items of salespeople’s customer orientation revealed that three factors with eigenvalues greater than 1 were extracted (e.g., Kaiser 1960; see Table 4). All items loaded on their corresponding factors, and no cross-loadings were greater than .29. Whereas every item of perceived customer centricity loaded on its corresponding factor with no smaller factor loadings than .69 and no cross-loadings greater than .15, the well-established scales of a firm’s customer orientation and salespeople’s customer orientation indicated factor loadings that were smaller than .70. Web Appendix W1 provides further insights that reveal that these results do not affect the construct validity, convergent validity, and discriminant validity of perceived customer centricity. Furthermore, Web Appendix W2 establishes the discriminant validity of perceived customer centricity against alternative operationalizations of customer orientation (Brown et al. 2002).

Table 4. Studies 2 and 3: Results of exploratory factor analyses.

Item no.	Item	Study 2			Study 3
		Factor 1: Perceived customer centricity	Factor 2: Firm’s customer orientation	Factor 3: Sales- people’s customer orientation	Factor 1: Perceived customer centricity	Factor 2: Firm’s customer orientation	Factor 3: Sales- people’s customer orientation
CC1	We as a customer are at the center of [firm]’s actions.	.73			.88
CC2	[Firm] caters its actions entirely to us as a customer.	.88			.93
CC3	For [firm] we play the undeniable primary role.	.82			.86
CC4	The customers are the top priority for [firm].	.95			.94
CC5	[Firm] is a customer-centric firm.	.69			.86
CC6	[Firm] lives the idea of “customer centricity.”	.78			.87
FCO1	[Firm] measures customer satisfaction systematically and frequently.		.88			.93
FCO2	[Firm] constantly monitors my level of commitment and orientation to serve my needs.		.95			.85
FCO3	[Firm] understands my needs better than its competitors do.		.51			.60
FCO4	[Firm] tries to understand its customers’ needs.		.61			.80
SCO1	[Salespeople of the firm] try to understand my needs.			.69			.81
SCO2	[Salespeople of the firm] try to influence me by information rather than by pressure.			.82			.92
SCO3	[Salespeople of the firm] focus the sales talk on the product or service and the benefits it offers.			.81			.97
SCO4	[Salespeople of the firm] particularly focus on those benefits that are of particular relevance for me.			.78			.91

Note: All items were measured on 7-point Likert-type scales, anchored “strongly disagree” and “strongly agree.” Extraction method: Principal axis factoring. Rotation method: Promax with Kaiser normalization. Rotation converged in three iterations. Coefficients with an absolute value below .30 are suppressed.

Second, we tested for internal consistency, composite reliability, and average variance extracted for the measurement scales of perceived customer centricity, a firm’s customer orientation, and salespeople’s customer orientation. Internal consistency was given seeing that no Cronbach’s alpha values were lower than .87. Furthermore, we conducted a confirmatory factor analysis indicating a good fit of the model (e.g., RMSEA = .08; CFI = .94; TLI = .93; SRMR = .04). No composite reliabilities were lower than .87 and no values for average variance extracted were lower than .62, thus meeting or exceeding the recommended thresholds (Bagozzi and Yi 1988). We additionally assessed the discriminant validity of the construct measures by using Fornell and Larcker’s (1981) criterion. The squared estimated correlation of every pair of factors was smaller than each factor’s average variance extracted. In summary, these analyses confirm our scale’s construct validity, convergent validity, and discriminant validity.

Tests for face validity

In addition, we tested whether participants of Study 2 understood the meaning of perceived customer centricity and each of its six items. Therefore, we provided participants our definition of perceived customer centricity and asked them whether they understood the concept, using both a binary and a Likert-scaled question; 97.2% of participants indicated that they understood the meaning of the concept of perceived customer centricity, and the mean on a 7-point Likert scale was 5.85 (from 1 = strongly disagree to 7 = strongly agree). Furthermore, we asked participants how easy it was for them to answer each of the items of perceived customer centricity. The lowest mean on all items was 5.15 (7-point Likert scale, from 1 = very difficult to answer to 7 = very easy to answer). These results indicate that participants understood our measurement items and the concept of perceived customer centricity.

Antecedents and consequences of perceived customer centricity

Our newly developed and validated measurement scale enables us to examine (1) how companies can engender perceptions of customer centricity and (2) what consequences perceptions of customer centricity have for firms. To this end, we initially review prior literature on antecedents and consequences of customer centricity and subsequently derive hypotheses on the construct of perceived customer centricity.

Literature review on customer centricity

Antecedents of customer centricity

To our best knowledge, no prior study has examined customer perceptions of customer centricity. Instead, previous research predominantly focused on specific ways of implementing customer centricity, such as adjusting organizational structures, information technologies, and marketing strategies. In the following, we elaborate on key findings of prior studies.

First, several studies examined how firms can adapt their organizational structure to customers and their needs to achieve higher customer centricity. Organizational structures reflect the extent to which a firm’s organizational design aligns with its customers or customer groups (e.g., Imhoff, Loftis, and Geiger 2001; Wind and Rangaswamy 2001; Galbraith 2002, 2011; Shah et al. 2006; Lee et al. 2015). Academic marketing literature on customer-centric organization structures claims that aligning organizational structures to customers instead of having functional or product-oriented structures increases customer centricity and firm success (e.g., Burmann, Meurer, and Kanitz 2011; Shah et al. 2006). However, Lee et al. (2015) indicated that aligning organizational structures to customers to become more customer centric comprises an inherent cost–benefit tradeoff. Specifically, for firms being organized in large divisions or for firms competing in different markets, customer-centric organization structures do pay off financially. By contrast, for firms that are already aligned with their customers, with small divisions serving less-diverse markets, or for firms competing in only few markets, the additional infrastructure costs and communication complexity outweigh the benefits of being organized customer centric (Lee et al. 2015).

Second, prior literature focused on how firms can use information technologies that consider customers and their needs to implement customer centricity (e.g., Lessmann and Voß 2009; Wagner and Majchrzak 2006; Kaushik 2009; Liang and Tanniru 2006). Lessmann and Voß (2009) show that analyzing a firm’s data streams helps firms gain insights into customer behavior, needs, and preferences and thereby can improve decision making in customer-centric planning tasks. Furthermore, Wagner and Majchrzak (2006) illustrated that firms can use “customer wikis” to become more customer centric. Customer wikis allow customers to not only access but also change a firm’s online presence and enable collaborative content and joint solution development.

Last, prior literature offers important insights on how firms can improve their performance through customer-centric marketing strategies. Sheth, Sisodia, and Sharma (2000, 65) implied that customer-centric marketing will increase efficiency in marketing processes not by influencing people in terms of what to buy, when to buy, and how much to buy, but by being more concerned to better respond to customer demands (Sharma and Sheth 2004). Specifically, firms may improve profits and return on marketing communications through the appropriate identification of customers for customized communications, collaborative development of campaigns, and the matching of the channel of communication with customers’ preferences (e.g., Sheth, Sisodia, and Sharma 2000; Venkatesan and Kumar 2004; Lenskold 2004; Cheng and Dogan 2008). Customer-centric sales campaigns not only may increase firm profits and return on investment but may additionally have a positive impact on the relationship quality between the customer and the firm (Kumar, Venkatesan, and Reinartz 2008). Nonetheless, Venkatesan and Kumar (2004) indicated that financial benefits of customer-centric marketing strategies may not be realized immediately because firms need to incur costs to move their organization toward customer centricity.

Consequences of customer centricity

Although customer centricity has been regarded as important for firms for several decades (e.g., Sheth, Sisodia, and Sharma 2000; Shah et al. 2006; Gummesson 2008a), research investigating consequences of customer centricity empirically is relatively scarce. Existing marketing literature mainly concentrates on how objective firm characteristics classified as customer centric affect firm performance (e.g., Lee et al. 2015; Sheth, Sisodia, and Sharma 2000; Fader 2012; Crecelius et al. 2019) and on how customer-centric marketing strategies perform (e.g., Homburg, Workman, and Jensen 2000; Kumar, Venkatesan, and Reinartz 2008).

Research on consequences of customer-centric firm characteristics indicates that structuring divisions around customer groups improves financial performance by increasing customer satisfaction but harms financial performance through coordinating costs (Lee et al. 2015). Lee et al. (2017) showed that, when considering investments in personal selling and advertising, the payoff of such investments improves if a firm exhibits a customer-aligned structure. Furthermore, customer-centric management systems have been shown to enhance relational information processes with customers and, thus, customer relationship performance (Jayachandran et al. 2005). In addition, Crecelius et al. (2019) found that suppliers that exhibit customer centricity by proactively assessing the structure of their customers can enhance revenue and mitigate costs.

Hypotheses on perceived customer centricity

Aiming to extend prior literature, we propose that a firm’s customer orientation and that of its salespeople foster customers’ perceptions of customer centricity, which in turn increase customers’ sales revenue and loyalty. Customer orientation entails behaviors related to understanding and meeting customer needs and should therefore reflect an important cue for customers to perceive firms as customer centric. Furthermore, we suggest that the consequences of perceived customer centricity on sales revenue and customer loyalty depend on customers’ perceptions of a firm’s prices. Specifically, we suggest that customers who perceive a company’s prices as high might place a higher importance on customer centricity and are thus more likely to purchase and to be loyal when they perceive the firm to be highly customer centric. Figure 3 provides our conceptual framework and displays all proposed hypotheses. We proceed by developing these hypotheses and subsequently empirically test them in Study 3.

Figure 3. Study 3: Conceptual framework.

We draw on diagnosticity theory (Feldman and Lynch 1988) to derive the effects of a firm’s customer orientation and salespeople’s customer orientation on perceived customer centricity. According to diagnosticity theory, to make inferences, individuals rely on the most useful (i.e., “diagnostic”) cues available and refrain from using other, less useful, cues (e.g., Feldman and Lynch 1988; Skowronski and Carlston 1987). For example, customers may base their evaluation of a seller’s product quality on their own experiences with the seller’s products rather than on advertising claims (Feldman and Lynch 1988). Prior research has applied diagnosticity theory to customer decision making (e.g., Alavi, Bornemann, and Wieseke 2015; Dick, Chakravarti, and Biehal 1990) and customers’ evaluations of corporate messages (e.g., Biehal and Sheinin 2007; Habel et al. 2016).

In the following, we use diagnosticity theory to propose antecedents of perceived customer centricity. Our argument builds on the notion that it is difficult, if not impossible, for customers to evaluate whether a firm genuinely places customers’ interests in the center all of its actions because most of these measures are not directly visible and accessible to customers. Therefore, customers need to base their evaluation of customer centricity on diagnostic cues that they are in fact able to access (Feldman and Lynch 1988). A firm’s customer orientation may serve as a diagnostic cue in this respect. Specifically, a firm’s customer orientation reflects the degree to which a firm tends to collect intelligence about customers and addresses customers’ needs (e.g., Im and Workman 2004; Kohli and Jaworski 1990; Narver and Slater 1990; Verbeke et al. 2008; Franke, Keinz, and Steger 2009). Such behavioral tendencies both are accessible to customers and may be interpreted as signals of a firm’s customer centricity. To illustrate, imagine a customer who is regularly asked by a firm to give feedback and experiences that the firm intensively uses her feedback to improve its products and services. This customer is likely to infer from her experience that the firm regards customers’ interests as central. Therefore, we hypothesize the following:

H₁: A firm’s customer orientation has a positive effect on perceived customer centricity.

Beyond the organizational level, customer orientation has been conceptualized on the individual customer-contact level (e.g., Cross et al. 2007). Salespeople’s customer orientation focuses on this individual customer-contact level and reflects salespeople’s tendency or predisposition to meet customer needs (Brown et al. 2002, 111). Customer-oriented salespeople focus on the understanding of customer needs, low-pressure selling, and problem-solution selling approaches (Saxe and Weitz 1982).

Parallel to our argument regarding a firm’s customer orientation, we expect that customers base their evaluation of a firm’s customer centricity on salespeople’s customer orientation as a diagnostic cue (Feldman and Lynch 1988). Specifically, if a firm’s salespeople aim to identify customers’ needs, engage in problem-solution selling approaches, and conduct low-pressure selling (Saxe and Weitz 1982; Homburg, Müller, and Klarmann 2011b), customers might conclude that the firm regards customers’ interests as central.

The potentially crucial role of salespeople in this respect has also been highlighted by prior research. In particular, as salespeople are the key intermediary between the firm and customers, they have the crucial role to cater to customers’ interests throughout the sales process (Sirdeshmukh, Singh, and Sabol 2002; Palmatier, Scheer, and Steenkamp 2007). They are therefore a key resource for the implementation of a firm’s customer centricity, which is highly palpable for the customer (Sheth, Sisodia, and Sharma 2000; Shah et al. 2006). Therefore, we propose the following:

H₂: Salespeople’s customer orientation has a positive effect on perceived customer centricity.

Customers who perceive a firm as customer centric experience their interests to reside in the center of the firm’s actions and are thus likely to expect increased benefits along their relationship with the firm. Specifically, customer-centric firms tailor their activities to better respond to customer demands, which enables them to meet customer needs and thus engender customer satisfaction (Sheth, Sisodia, and Sharma 2000; Shah et al. 2006). As a result, customers should be motivated to purchase a higher share of their overall demand from that firm (e.g., Kumar, Venkatesan, and Reinartz 2008; Palmatier et al. 2006). Furthermore, if a firm is perceived to prioritize its customers and to offer superior customer value, customers are likely to develop loyalty intentions (Gulati 2007; Lee et al. 2015). Therefore, we suggest the following:

H₃: Perceived customer centricity has a positive effect on (a) sales revenue with a customer and (b) customer loyalty.

We expect the effects of perceived customer centricity on sales revenue and customer loyalty to depend principally on customer perceptions of the firm’s prices. In line with equity theory, customers are likely to have higher expectations of a firm’s performance if a firm demands high prices (e.g., Rao and Monroe 1989; Dodds et al. 1991). Such elevated expectations are more likely to be confirmed by firms perceived as customer centric because these firms tend to offer additional value by putting customers’ interests at the center of all of their actions. Therefore, we suggest that customers who perceive the prices of the firm as high might be more demanding and, thus, might ascribe a greater importance to high customer centricity for remaining loyal and extending business with the firm.

By contrast, customers who perceive the prices of the firm as low might particularly remain loyal and extend business because of their economic benefits rather than their perception of being the center of the firm’s attention (Oliver 1999; Gustafsson, Johnson, and Roos 2005; Wieseke, Alavi, and Habel 2014). Therefore, higher perceptions of customer centricity might transfer less to increases in sales revenue or customer loyalty if customers perceive the prices of the firm as low. We hypothesize the following:

H₄: A customer’s price perception moderates the effect of perceived customer centricity on (a) sales revenue and (b) customer loyalty. Specifically, the effect of perceived customer centricity on sales revenue and customer loyalty is more positive when customers perceive prices as high.

Study 3: Examining antecedents and consequences of perceived customer centricity

Data collection and sample

Study design and procedure. To collect the data for Study 3, we collaborated with a multinational information technology firm (IT firm). The IT firm provided us with the contact data of 9,566 of their German customers’ key informants. Key informant surveys like ours are a well-established data source in sales and marketing research to provide reliable and valid survey results (e.g., Homburg et al. 2012; John and Reve 1982). When dispatching the survey to the IT firm’s customers we used a well-established online survey tool and provided a lottery for a tablet as incentive for the participants of the survey. We matched survey responses of the IT firm’s customers with corresponding data on sales revenue from the company’s database by using a unique identifier for each customer.

Measures

This study employs measurements that are established in the marketing literature with adjustments to suit our study’s context (see Appendix 1). Our key dependent variables are sales revenue and customer loyalty. In line with prior works, we chose customer’s sales revenue with the IT firm over one year as the dependent variable (e.g., Habel, Alavi, and Pick 2017). Customer loyalty was measured by using a two-item scale that was administered to customers of the IT firm and was based on Zeithaml, Berry, and Parasuraman (1996).

We incorporated a firm’s customer orientation and salespeople’s customer orientation as independent variables in our model. To measure a firm’s customer orientation, we used a four-item scale based on Im and Workman (2004) and Narver and Slater (1990). Salespeople’s customer orientation was assessed by four items based on Saxe and Weitz (1982) and Dwyer, Hill, and Martin (2000) that have been shown to be highly reliable by previous research (e.g., Homburg Müller, and Klarmann 2011a,b). Our moderator variable customer price perception was measured by two items that are based on Bornemann and Homburg (2011). To reduce omitted variable bias, we controlled for respondents’ quality perception, competition intensity, length of relationship with the supplier, and size of respondents’ firm. Importantly, because all customers evaluated the same supplier, by design we additionally control for a firm’s organizational structure, information technologies, and marketing strategies.

Sample characteristics

The data set of Study 3 comprises responses from a total of 1,089 customers (of 9,566), reflecting a response rate of 10.91%. A comparison of early and late respondents indicated that nonresponse bias was not an issue in our data (Armstrong and Overton 1977). All participating customers are system vendors in a business-to-business context that obtain products and services from the IT firm. The customers offer these products and services to their own customers, who are mostly end customers such as small- and medium-sized companies. Table 3b presents details on the sample characteristics.

Psychometric properties of measurement variables

Table 5 presents descriptive statistics, psychometric properties, and intercorrelations of the study’s core variables. Overall, the results of the confirmatory factor analysis indicate that the hypothesized model fits the data well (e.g., RMSEA = .063; CFI = .944; TLI = .933; SRMR = .032). No Cronbach’s alpha value is smaller than .68, and no average variance extracted is below .60, thereby exceeding the recommended thresholds (Bagozzi and Yi 1988). In addition, we assessed discriminant validity by using the criterion developed by Fornell and Larcker (1981). All average variances extracted exceeded the squared correlations between all pairs of constructs and met this criterion.

Table 5. Study 3: Correlations and psychometric properties of variables.

	1	2	3	4	5	6	7	8	9	10
1. Firm’s customer orientation	(.916)
2. Salespeople’s customer orientation	.641**	(.956)
3. Perceived customer centricity	.676**	.582**	(.962)
4. Price perception	.351**	.271**	.377**	(.684)
5. Sales revenue	.058	.046	.082**	−.001	–
6. Customer loyalty	.313**	.357**	.365**	.263**	.052	(.955)
7. Quality perception	.522**	.447**	.575**	.414**	.041	.467**	(.805)
8. Length of relationship with supplier	−.001	−.014	−.036	−.001	.039	.085**	−.011	–
9. Competition intensity	.014	−.001**	.037	−.031	.040	−.004	.000	.082**	(.862)
10. Customer size	−.008	.025	.031	.049	.173**	−.010	−.009	−.002	.024	–
Mean	3.55	4.03	3.41	3.93	27,377.8	5.65	4.72	12.34	5.39	1.11
Standard deviation	1.41	1.59	1.40	.95	132,505.0	1.25	1.05	7.73	1.30	.55
Average variance extracted	.73	.85	.81	.67	–	.91	.60	–	.69	–
Composite reliability	.92	.96	.96	.78	–	.96	.81	–	.87	–

Note: Cronbach’s (1951) internal consistency reliability reported on the diagonal.

* p < .05; **p < .01 (two-tailed).

Model estimation and results

Model specification

We conducted a path model approach to test our hypotheses. In our main effects model, we investigated the effects of a firm’s customer orientation and salespeople’s customer orientation on perceived customer centricity and examined how perceived customer centricity affects sales revenue and customer loyalty. To examine whether customers’ price perception influences the effects of perceived customer centricity on sales revenue and customer loyalty, we included corresponding interaction effects. Therefore, we followed the procedure outlined by Aiken and West (1991, 9) and included the interaction term of perceived customer centricity and price perception as an additional predictor on sales revenue and customer loyalty in our model. We calculated the interaction term by multiplying the mean-centered variables perceived customer centricity and price perception. Furthermore, we employed the procedure by Ganzach (1998) by additionally including quadratic effects of perceived customer centricity and price perception on sales revenue and customer loyalty to account for potential collinearity of predictors and moderators. In addition, we controlled for the effects of a firm’s and salespeople’s customer orientation on sales revenue and customer loyalty and included several control variables (customers’ quality perception, length of relationship with the IT firm, competition intensity, and customer size).

Results

Table 6 presents our results of Study 3. Model 2 is the full model including interaction effects as illustrated in Figure 3. The effect of firm’s customer orientation on perceived customer centricity is positive and significant (b_{Firm’s customer orientation → perceived customer centricity} = .40, p < .01). This offers support for H₁ and suggests that in line with our reasoning, a firm’s customer orientation is associated with higher levels of perceived customer centricity. Furthermore, the effect of salespeople’s customer orientation on perceived customer centricity is positive and significant (b_{Salespeople’s customer orientation → perceived customer centricity} = .17, p < .01). Thus, H₂ is supported.

Table 6. Study 3: Results of path modeling.

	Hypothesis	Model 1		Model 2
		Estimate	S.E.	Estimate	S.E.
Structural effects
Firm’s customer orientation → perceived customer centricity	H1	.403**	(.028)	.403**	(.028)
Salespeople’s customer orientation → perceived customer centricity	H2	.174**	(.024)	.174**	(.024)
Perceived customer centricity → sales revenue	H3a	.745*	(.424)	.828*	(.424)
Perceived customer centricity → customer loyalty	H3b	.075*	(.035)	.093**	(.035)
Price perception → sales revenue		.690	(.466)	.848*	(.464)
Price perception → customer loyalty		−.081*	(.039)	−.094**	(.038)
Two-way interaction effects
Perceived customer centricity × price premium → sales revenue	H4a			1.321**	(.342)
Perceived customer centricity × price premium → customer loyalty	H4b			.054*	(.028)
Controlled effects
Perceived quality → perceived customer centricity		.364**	(.028)	.364**	(.032)
Length of relationship → perceived customer centricity		−.007*	(.004)	−.007*	(.004)
Competition intensity → perceived customer centricity		.036*	(.022)	.036*	(.022)
Company size → perceived customer centricity		.077	(.051)	.077	(.024)
Firm’s customer orientation → sales revenue		.222	(.426)	.125	(.423)
Salespeople’s customer orientation → sales revenue		−.140	(.339)	−.136	(.336)
Perceived quality → sales revenue		−.035	(.051)	−.071	(.503)
Length of relationship → sales revenue		.076	(.055)	.071	(.055)
Competition intensity → sales revenue		.289	(.305)	.257	(.304)
Company size → sales revenue		4.127**	(.712)	4.182**	(.707)
Firm’s customer orientation → customer loyalty		−.052	(.035)	−.043	(.035)
Salespeople’s customer orientation → customer loyalty		.139**	(.028)	.131**	(.027)
Perceived quality → customer loyalty		.410**	(.040)	.389**	(.040)
Length of relationship → customer loyalty		.016**	(.005)	.018**	(.004)
Competition intensity → customer loyalty		−.011	(.025)	.009	(.025)
Company size → customer loyalty		−.038	(.059)	−.054	(.058)
Quadratic effects^a
Perceived customer centricity quadratic → sales revenue				.561**	(.201)
Perceived customer centricity quadratic → customer loyalty				−.072**	(.016)
Price perception quadratic → sales revenue				1.210**	(.349)
Price perception quadratic → customer loyalty				−.005	(.029)
R² sales revenue		.042**		.062**
R² customer loyalty		.260**		.289**

Note: We report unstandardized coefficients. S.E. = standard error.

* p < .05; **p < .01 (one-tailed).

^a Ganzach’s (1998) procedure.

Results of the consequences of perceived customer centricity offer support for H_3a and H_3b by revealing that perceived customer centricity has a positive and significant impact on sales revenue (b_{Perceived customer centricity → sales revenue} = .83, p < .05) and customer loyalty (b_{Perceived customer centricity → customer loyalty} = .09, p < .01). Furthermore, we examined whether customers’ price perceptions influence the effects of perceived customer centricity on sales revenue and customer loyalty. Our results offer support for H_4a by showing that the interaction effect of perceived customer centricity and price perception on sales revenue is positive and significant (b_{Perceived customer centricity × price perception → sales revenue} = 1.32, p < .01). Figure 4.1 reveals further insights by indicating that the effect of perceived customer centricity on sales revenue is positive and significant if customers perceive a firm’s prices as high (ω_High = 2.03, p < .01) but becomes nonsignificant when customers perceive a firm’s prices as low (ω_Low = -.37, p > .10). Thus, customers who perceive firm prices as high tend to have a higher sales revenue when they perceive the firm to be highly customer centric. Furthermore, our results offer support for H_4b by showing that the interaction effect of perceived customer centricity and price perception on customer loyalty is positive and significant (b_{Perceived customer centricity × price perception → customer loyalty} = .05, p < .05). Figure 4.2 offers further support for the reasoning that customer loyalty can be based either on prices of a firm or on the performance that a firm offers. Specifically, Figure 4.2 reveals that the effect of perceived customer centricity on customer loyalty is not significant when customers perceive a firm’s prices as low (ω_Low = .04, p > .10) whereas it is significant and positive if customers perceive a firm’s prices as high (ω_High = .14, p < .01).

Figure 4. Study 3: Interaction plots and simple slope analyses.

In addition, we conducted mediation analyses to explore whether the effects of a firm’s and salespeople’s customer orientation on sales revenue and customer loyalty are explained by perceived customer centricity. Table 7 presents our results. We find significant and positive indirect effects of firm’s and salespeople’s customer orientation on both sales revenue and customer loyalty. Thus, perceived customer centricity mediates the influence of firm’s and salespeople’s customer orientation on sales revenue and customer loyalty. Specifically, the effect of salespeople’s customer orientation on customer loyalty is partially mediated by perceived customer centricity, and the effects of firm’s customer orientation on sales revenue and customer loyalty and the effect of salespeople’s customer orientation on sales revenue are fully mediated by perceived customer centricity.

Table 7 Study 3: Results of mediation analyses.

Predictor (X)	Mediator (M)	Outcome (Y)	X → M	M → Y	X → Y	Indirect effect
Firm’s customer orientation	Perceived customer centricity	Sales revenue	.403***	.745**	.222	.334**
		Customer loyalty		.075**	−.052	.037***
Salespeople’s customer orientation		Sales revenue	.174***	.745**	−.140	.144**
		Customer loyalty		.075**	.139***	.016**

Note: We report unstandardized coefficients.

* p < .1; **p < .05; ***p < .01 (one-tailed).

Supplemental analyses

We conducted two robustness checks to ensure the validity of our findings and of the perceived customer centricity scale. First, to ensure that common method variance does not affect our results, we followed the procedure outlined by Ramani and Kumar (2008; see also, e.g., Griffith and Lusch 2007; Josiassen 2011) and conducted both a confirmatory factor analytical approach to Harman’s one-factor test and the marker-variable approach developed by Lindell and Whitney (2001). Results of the factor analytical approach to Harman’s one-factor test show a poor fit of the one-factor model (e.g., RMSEA = .17; CFI = .54; TLI = .50), which offers first indications that common method variance does not affect our findings. To substantiate these findings, we conducted the marker-variable approach (Lindell and Whitney 2001) and considered the length of the relationship between the IT firm and its customer as a marker variable. Using the lowest positive correlation between the marker variable and one of the core variables (i.e., firm’s customer orientation r = .001; p > .10) to adjust the other correlations does not change the significance of any correlation between the core variables of the model. This result offers further support that common method variance is not an issue in our analyses.

Second, we conducted tests to evaluate the extent to which participants in Studies 2 and 3 attributed the same meaning to the latent construct (Brown 2014; Van de Schoot, Lugtig, and Hox 2012) and, thus, whether the items have equal factor loadings in both studies (i.e., metric invariance). We therefore merged the data sets of both studies and reran our factor analysis with two factors of perceived customer centricity. The loadings emerged as highly comparable for both factors, with differences ranging between .035 and .075. Results of model comparison tests revealed that metric invariance between both groups can be assumed when one factor loading of item five (“[Firm] is a customer-centric firm.”) was allowed to differ between groups (Δχ² = 7.28; p > .10; Δ(−2*log-likelihood) = 3.64; p > .10). When all factor loadings were constrained as equal between both samples, results were mixed (Δχ² = 20.35; p < .01; Δ(−2*log-likelihood) = 10.18; p > .10), which is not surprising given the large study sample of more than 1,300 observations. Thus, in summary, our scale exhibits at least partial metric invariance across two vastly different study contexts (Study 2: business-to-customer (B2C), financial services; Study 3: business-to-business (B2B), information technology). We consider this outcome as satisfactory seeing that full measurement invariance is unlikely (e.g., Steenkamp and Baumgartner 1998; Banerjee, Iyer, and Kashyap 2003; Erdem, Swait, and Valenzuela 2006; Tellis, Prabhu, and Chandy 2009).

Discussion

Research issues

Academia and practice have put a growing focus on the concept of customer centricity (e.g., Crecelius et al. 2019; Google Trends 2019). However, extant research has not yet provided a validated scale to measure the extent to which customers perceive a firm to be customer centric, that is, the degree to which a customer perceives a firm to put customers’ interests at the center of all of its actions. Our study takes this step and hereby contributes to academia in at least three ways.

First, our study is the first to conceptualize and operationalize customer centricity as perceived by customers. Prior research on customer centricity has mainly focused on objective firm characteristics commonly associated with customer centricity while neglecting customer perceptions (e.g., Lee et al. 2015, 2017; Sheth, Sisodia, and Sharma 2000; Fader 2012). Complementing prior research, we developed a valid and easily applicable measurement scale of customer centricity as perceived by customers. We verified the scale’s validity in two studies using different industries (banking and IT) in different cultural contexts (United States and Europe). Future sales and marketing research can build on our scale and deepen the understanding of customer centricity. Moreover, a common operationalization of customer centricity as perceived by customers makes research results comparable.

Second, our study contributes to the emergent literature stream on consequences of customer centricity (e.g., Crecelius et al. 2019; Lee et al. 2015, 2017; Shah et al. 2006). For example, Lee et al. (2015) and Jayachandran et al. (2005) showed that a firm’s customer-centric organizational structure improves customer relationships. Our article corroborates these results by showing that perceived customer centricity positively affects a customer’s loyalty as well as the revenue a firm generates with this customer.

Importantly, we find that these effects are not equal in size for all customers, but stronger (weaker) for customers who perceive a firm to exhibit high (low) prices. We attribute this effect to the notion that if prices are low, customer loyalty and sales revenue should particularly depend on the economic benefits provided to customers (Wieseke, Alavi, and Habel 2014; Gustafsson, Johnson, and Roos 2005), which can render perceptions of customer centricity less important. We hereby contribute to literature on contingent effects of customer centricity on desired consequences. For example, previous research identified tie strength and centrality as moderators of the effectiveness of customer centricity on firm performance (Frankenberger, Weiblen, and Gassmann 2013). To our best knowledge, however, ours is the first study to add customers’ perceptions of price to the literature on contingent effects of customer centricity.

Third, our study contributes to literature on how to foster customer centricity. Prior literature has examined the implementation of customer centricity through customer-centric organizational structures (e.g., Galbraith 2005; Shah et al. 2006; Lamberti 2013), customer-centric information technologies (e.g., Wagner and Majchrzak 2006; Waisberg and Kaushik 2009), and customer-centric marketing strategies (e.g., Lenskold 2004; Gurău, Ranchhod, and Hackney 2003; Sheth, Sisodia, and Sharma 2000). Adding to these findings, we show that perceived customer centricity is decisively driven by customer orientation that entails behaviors aimed at identifying and addressing customers’ needs both on the level of the firm and on the level of the salesperson (Im and Workman 2004; Narver and Slater 1990; Saxe and Weitz 1982). Importantly, our study illustrates the outstanding significance of the sales force when aiming to increase customers’ perceptions of customer centricity.

Limitations and avenues for future research

Like any research, ours exhibits limitations that provide interesting avenues for future study. First, our evidence of antecedents and outcomes of perceived customer centricity is correlational rather than causal. One can easily conceive arguments that the causality between our constructs is reverse to what we hypothesized. Specifically, customers who are highly loyal and have a high purchase volume may be more apt to feel that they are a priority for the supplier, and a supplier may be more apt to act in a customer-oriented way toward these valuable customers. Like other cross-sectional studies (e.g., Brown et al. 2002; Im and Workman 2004; Narver and Slater 1990), we cannot empirically rule out such alternative explanations.

However, we hold that it is reasonable to assume that the causality between our constructs is unlikely to be fully reversed for both theoretical and empirical reasons: (a) A causal effect of customer orientation via perceived customer centricity on customer loyalty and purchase volume can be deduced from well-established theories, such as diagnosticity theory (Feldman and Lynch 1988) and social exchange including equity theories (Blau 1964; Homans 1974). (b) Experimental studies have provided strong evidence that focusing on customers improves financial outcomes (e.g., Kumar, Venkatesan, and Reinartz 2008). Thus, contrary to fully reversed causality, we would expect bidirectional causal relationships between our constructs. This argument suggests that the coefficients in our model may be inflated and would have to be adjusted downward to understand the magnitude of the causal effects we hypothesized. We therefore urge readers to interpret the sizes of our coefficients with care.

Second, we hold that further research is needed to distinguish the concept of customer centricity from the concept of customer orientation. This seems particularly important seeing that prior literature has not provided a commonly accepted definition of customer centricity. Our literature review suggests that a key differentiator may be the active prioritization of customer interests. Future research may build on this notion and refine the conceptualization of customer centricity, particularly in comparison with customer orientation. In addition, future research might explore how companies can effectively prioritize customers to engender perceived customer centricity without undermining firm profitability.

Third, we conducted Study 3 in an information technology business-to-business context. Therefore, it is questionable to which extent these results generalize to other contexts. Future research might address this limitation by replicating our results in other industries including business-to-customer markets as well as for smaller firms. Furthermore, future research may examine the role of perceived customer centricity in services rather than in goods contexts. It may well be that the effect of customer centricity on sales revenue is stronger for services than for goods because of the higher importance to involve and co-create with customers (Lamberti 2013).

Fourth, we conducted Study 3 with customers of a single firm. This approach had the benefit of providing a relatively controlled environment for testing our hypotheses. However, it also precluded us from testing firm-specific antecedents of customer centricity, such as a firm’s organizational structure (e.g., Galbraith 2005; Shah et al. 2006) and information technologies (e.g., Wagner and Majchrzak 2006; Waisberg and Kaushik 2009). Future research could use our scale in cross-company and cross-industry contexts to explore such antecedents and verify the generalizability of our findings across contexts.

Managerial implications

Our study provides several actionable implications for managerial practice. First, because being perceived as customer centric is linked to customer loyalty and sales revenue, managers should strive to optimize perceived customer centricity. Thus, our study confirms that companies such as Amazon, Fresenius, and Hewlett Packard are working toward effective positionings (Amazon 2019; Fresenius 2019; Hewlett Packard 2019). Notably, fostering customers’ perceptions of customer centricity seems particularly sensible for companies with a high price positioning relative to competitors because customers of these companies are likely to expect special treatment (e.g., Wetzel, Hammerschmidt, and Zablah 2014).

Second, to foster customers’ perceptions of customer centricity, managers are well advised to foster customer orientation both on the level of the firm and on the level of salespeople. Specifically, managers should establish systems and processes to measure and address customers’ needs. They should furthermore enable and motivate their sales force to accomplish the same in individual interactions with customers. This recommendation is in line with CSO Insights (2017, 7), according to which a key performance driver is salespeople’s capability to “consistently and effectively articulate a solution that is aligned to the customer’s needs.”

Notably, the previous recommendation is neither surprising nor new. Customer orientation is an extremely well-established key success factor for both companies and salespeople (e.g., Franke and Park 2006; Im and Workman 2004) and by definition closely linked to the concept of customer centricity – even to the extent that researchers have wondered whether “marketing primarily applies old and well-tried tricks” when talking about customer centricity (e.g., Gummesson 2008a, 326). However, interestingly, the recent surge in managers’ interest in customer centricity (e.g., Google Trends 2019; Kellogg 2019; Stanford 2019) suggests that managers may not necessarily make the connection between customer orientation and customer centricity. Our study may thus serve as a reminder to refocus on the fundamentals of sales and marketing when aiming to be perceived as customer centric: identifying and addressing customers’ needs rather than treating customer centricity as a matter of marketing communications. This recommendation seems particularly warranted because “customer-orientation has been applied half-heartedly and […] is supplier ego-centric rather than customer-centric” (Gummesson 2008b, 15). Put differently, we encourage managers to “walk the talk” when it comes to fostering perceptions of customer centricity.

Third and last, managers may use the scale developed in our study to measure perceived customer centricity. As our scale items are easy to understand and independent of a firm’s industry or context, and because the scale consists of only six items, it requires little effort to complete. Measuring perceived customer centricity may also be a means to drive organizational change. As outlined in the beginning, fostering customer centricity assumes a high priority for firms yet questions employees’ current practices – which may well evoke employees’ reactance. Firms may alleviate this reactance by measuring and communicating perceived customer centricity as well as effects of perceived customer centricity on desirable consequences. To illustrate, customers of the IT firm in Study 3 that perceived customer centricity as higher than 3.5 (the median of perceived customer centricity) generated on average 1.9 times the revenue of customers who perceived customer centricity as lower than or equal to 3.5.

Declaration of interest

No potential conflict of interest was reported by the authors.

Appendix 1. Survey constructs: Definitions and measures

Perceived customer centricity/Studies 1–3

Definition: The degree to which a customer perceives a firm to put customers’ interests at the center of all of its actions (our own definition).

• We as a customer are at the center of [firm]’s actions.^a

• [Firm] caters its actions entirely to us as a customer.^a

• For [firm] we play the undeniable primary role.^a

• The customers are the top priority for [firm].^a

• [Firm] is a customer-centric firm.^a

• [Firm] lives the idea of “customer centricity.”^a

Firm’s customer orientation/Studies 2 and 3

Definition: The degree to which a firm collects intelligence about customers to satisfy their needs and desires (based on Im and Workman 2004; Narver and Slater 1990)

• [Firm] measures customer satisfaction systematically and frequently.^a

• [Firm] constantly monitors our level of commitment and orientation to serve our needs.^a

• [Firm] understands our needs better than its competitors do.^a

• [Firm] tries to understand its customers’ needs.^a

Salespeople’s customer orientation/Studies 2 & 3

Definition: Salespeople’s tendency or predisposition to meet customer needs (based on Saxe and Weitz 1982; Dwyer, Hill, and Martin 2000).

• [Salespeople] try to understand customer needs.^a

• [Salespeople] try to influence customers by information rather than by pressure.^a

• [Salespeople] focus the sales task on the product or service and the benefits it offers.^a

• [Salespeople] particularly focus on those benefits that are of particular relevance for the customer.^a

Customer loyalty/Study 3

Definition: Customer’s intention to perform a diverse set of behaviors that signal a motivation to maintain a relationship with the focal firm (based on Zeithaml, Berry, and Parasuraman 1996).

• We will remain loyal to [firm].

• We will continue to do business with [firm] in the next few years.

Price perception/Study 3

Definition: A customer’s perception of the degree of a firm’s price level (based on Bornemann and Homburg 2011).

• How do you assess the price level of [firm] compared to its competitors?^b

• How do you rate the overall price/performance ratio of [firm] compared to its competitors?^b

Quality perception/Study 3

Definition: A customer’s perception of the degree of a firm’s product performance (based on Sweeney and Soutar 2001).

• How do you evaluate [firm]’s product quality compared to its competitors.^a

• How do you evaluate [firm]’s service quality compared to its competitors.^a

• How do you evaluate [firm]’s quality of customer-related business processes compared to its competitors.^a

Competition intensity/Study 3

Definition: The degree to which a market is characterized by competitive behavior by its market participants (based on Jaworski and Kohli 1993).

• Competition in our business is severe.^a

• The number of our direct competitors is very high.^a

• In our market, one hears of competitive moves almost every day.^a

Length of relationship/Study 3

• For how many years has the business relationship with [firm] existed?^c

Customer size/Study 3

• How many employees work at your business unit?^d

^aScale from “strongly disagree” to “strongly agree.”

^bScale from “significantly worse” to significantly better.”

^cOpen text field.

^dFewer than 50; 50 to <100; 100 to <500; 500 to <1,000; 1,000 to <2,500; 2,500 to <5,000; 5,000 to 10,000 or more.