Customer Orientation of the Company (COOC)

1. Abstract

The Customer Orientation of the Company (COOC) scale is a six-item psychometric measurement instrument designed to capture consumers’ subjective perceptions of a firm’s overarching dedication to understanding, prioritizing, and fulfilling customer needs. Originally established in marketing psychology and organizational behavior literature by Darren W. Dahl, Christoph Fuchs, and Martin Schreier (2015), the scale operationalizes customer orientation at the holistic macro-organizational level, serving as a critical counterpart to classic salesperson-level dyadic measures such as the Selling Orientation-Customer Orientation (SOCO) scale. Rather than assessing strategic internal management processes or employee-reported behaviors, the COOC scale captures the external customer’s cognitive attribution that an organization operates with genuine benevolence, reciprocal communicative intent, and authentic need-centricity as opposed to short-term transactional extraction. The scale utilizes a single-factor, unidimensional structure comprising six declarative items scored on a 7-point Likert response format ranging from 1 (“Strongly disagree”) to 7 (“Strongly agree”). Psychometric evaluations across multiple empirical investigations confirm that the instrument exhibits high internal consistency reliability (with Cronbach’s alpha coefficients routinely exceeding α = .88 to .94 across experimental and field studies), robust convergent validity with constructs such as perceived organizational trustworthiness, corporate social responsibility, and customer empowerment, and discriminant validity against brand prestige and product quality. Confirmatory factor analyses demonstrate exceptional structural fit indices, affirming the unidimensionality and cross-sample invariance of the measure. The COOC scale has become a benchmark instrument for investigating the downstream consequences of user innovation, co-creation, open innovation initiatives, corporate communication, and retail relationship management.

2. Keywords

Customer Orientation of the Company, COOC, Darren W. Dahl, Christoph Fuchs, Martin Schreier, market orientation, perceived benevolence, user-designed products, consumer trust, organizational perception, customer centricity, psychometrics, scale validation, consumer psychology.

3. Authors

The Customer Orientation of the Company (COOC) scale was conceptualized, operationalized, and validated by a distinguished team of scholars in consumer psychology, marketing strategy, and innovation management:

• Darren W. Dahl, Ph.D.: Senior Associate Dean and Innovate BC Professor of Applied Innovation at the Sauder School of Business, University of British Columbia (Vancouver, Canada). Dr. Dahl is an internationally recognized scholar in consumer psychology, creativity, social influence, and new product development, having served as an Editor-in-Chief of the Journal of Consumer Research.
• Christoph Fuchs, Ph.D.: Professor of Marketing and Innovation at the TUM School of Management, Technical University of Munich (Munich, Germany), and Visiting Professor at the Erasmus School of Economics, Erasmus University Rotterdam. His research focuses on customer empowerment, user innovation, open innovation systems, and consumer response to technological shifts.
• Martin Schreier, Ph.D.: Professor and Head of the Department of Marketing at the Vienna University of Economics and Business (WU Vienna) (Vienna, Austria). Dr. Schreier is a leading international authority on user-driven innovation, crowdsourcing, brand authenticity, and the psychological mechanisms governing consumer perceptions of co-created goods.

The scale was formally introduced in their seminal 2015 publication in the Journal of Marketing: “Why and When Consumers Prefer Products of User-Designed Product Lines” (Vol. 79, No. 1, pp. 65–78), and has since seen extensive adoption in marketing science, retailing, and service management research (e.g., Song, Jung, & Xu, 2021).

4. Purpose

The primary purpose of the Customer Orientation of the Company (COOC) scale is to measure the extent to which consumers infer that an enterprise is fundamentally motivated to comprehend, advocate for, and resolve consumer problems, rather than merely extracting transactional profit. Historically, psychometric research in marketing examined customer orientation primarily from two divergent perspectives: internal organizational climate as reported by managers (e.g., the MARKOR framework of Kohli & Jaworski, 1990, or the MKTOR scale of Narver & Slater, 1990) or interpersonal frontline interactions as exhibited by sales personnel (e.g., Saxe & Weitz, 1982). These existing approaches left an empirical void: they failed to capture the consumer’s cognitive, organizational-level assessment of a brand’s holistic intentions.

In modern consumption environments, consumers constantly evaluate institutional cues—such as crowdsourcing programs, collaborative product development, customer service responsiveness, and pricing transparency—to deduce a firm’s underlying corporate philosophy. Dahl, Fuchs, and Schreier (2015) identified that when companies engage in customer-centric behaviors, such as launching user-designed product lines, consumers make causal attributions about the brand’s core values. The COOC scale was developed specifically to capture this psychological mechanism, serving as a mediator between external company actions and downstream consumer behavior, including brand loyalty, word-of-mouth advocacy, willingness to pay, and product adoption.

From an applied and academic standpoint, the scale fulfills several vital objectives:

• Testing Mechanistic Process Models: Enables behavioral researchers to empirically evaluate whether organizational interventions (e.g., co-creation, open innovation, participatory design, personalization) positively alter the brand’s perceived motivational identity.
• Diagnostic Benchmarking for Enterprise Strategy: Provides corporate brand managers and retail executives with a validated instrument to quantify how public marketing initiatives affect consumer beliefs regarding corporate empathy and alignment with user goals.
• Assessing Retail and Digital Relationship Dynamics: Facilitates rigorous empirical research across e-commerce, direct-to-consumer (DTC) models, and omnichannel retailing (e.g., Song et al., 2021) to explore how mass customization and digital customer touchpoints influence long-term consumer trust.
• Mitigating Attribution of Opportunism: Helps researchers measure the degree to which consumers perceive a firm as having their best interests at heart, effectively counteracting skepticism and perceived corporate exploitation.

5. Psychological Construct

The psychological construct measured by the COOC scale is Perceived Firm-Level Customer Orientation. Grounded in attribution theory, social cognition, and relational marketing theory, this construct reflects a consumer’s holistic mental schema concerning a firm’s operational focus, benevolent intentions, and behavioral responsiveness. While the COOC scale is structurally unidimensional, psychometrically loading cleanly onto a single higher-order factor, it integrates six distinct conceptual facets that collectively operationalize authentic organizational customer orientation:

5.1. Best-Interest Orientation (Benevolent Intent)

Represented by Item 1 (“This company has the customer’s best interests in mind”), this facet addresses the perceived altruistic or benevolent orientation of the firm. According to organizational trust theories (Mayer, Davis, & Schoorman, 1995), benevolence is the perception that an entity wishes to facilitate positive outcomes for the perceiver without an exclusively egocentric profit motive. In this context, consumers assess whether the firm evaluates strategic trade-offs through a customer-advocacy lens, prioritizing customer welfare even when non-immediate revenue is at stake.

5.2. Goal-Facilitation Orientation

Represented by Item 2 (“This company tries to help customers achieve their goals”), this facet measures instrumental support and functional alignment. Consumers approach products and services not merely as physical artifacts, but as tools that facilitate fundamental personal, social, and functional goals (Means-End Chain Theory; Gutman, 1982). A high score on this facet reflects the consumer’s belief that the firm structures its offerings to empower customers and assist them in solving contextual challenges.

5.3. Need Assessment and Diagnostic Effort

Represented by Item 3 (“This company tries to figure out what a customer’s needs are”), this facet captures active epistemic curiosity and empathetic inquiry. Drawing from social perception models, authentic care requires proactive cognitive investment. Consumers perceive an organization as customer-oriented when it visibly invests resources into understanding the evolving desires, pain points, and latent needs of its user base through market research, active feedback loops, and customer journey mapping.

5.4. Product-Need Congruence and Solution Suitability

Represented by Item 4 (“This company offers products that are best suited to the customer’s needs”), this facet assesses the actual manifestation of customer orientation in the firm’s tangible outputs. An organization may claim positive intentions, but authentic customer orientation requires substantive capability and execution. This facet examines whether the resulting portfolio of products, services, or solutions matches consumer demands with high precision.

5.5. Open Dialogue and Relational Communication

Represented by Item 5 (“This company communicates with customers to see what they need”), this facet evaluates two-way communication flow and relational transparency. Rather than relying on unidirectional, persuasive advertising, a customer-oriented organization fosters interactive, bidirectional communication channels where consumer feedback actively shapes operational and design decisions.

5.6. Behavioral Reliability and Need Responsiveness

Represented by Item 6 (“This company acts reliably in response to customer needs”), this facet measures procedural integrity, dependable execution, and operational consistency over time. Grounded in behavioral confirmation paradigms, an organization demonstrates authentic orientation by honoring implicit relational contracts, fulfilling promises, and responding predictably to customer issues or systemic market changes.

6. Theoretical Framework

The conceptual foundation of the COOC scale is rooted in three intersecting theoretical frameworks within cognitive psychology, organizational behavior, and consumer research:

6.1. Attribution Theory and Causal Inferences

Central to the operationalization of the COOC scale is Fritz Heider’s (1958) Attribution Theory, expanded by Harold Kelley’s covariation model and Edward E. Jones’s Correspondent Inference Theory. In consumption contexts, individuals act as intuitive psychologists seeking to explain why a company behaves the way it does. When a consumer observes an organizational initiative—such as asking users to submit and vote on new product ideas (Dahl et al., 2015) or providing accessible post-purchase support (Song et al., 2021)—they attribute either intrinsic (authentic, customer-focused) or extrinsic (exploitative, purely margin-driven) motives to the firm.

The COOC scale measures the dispositional inference reached by the consumer: when actions are attributed to genuine concern, the consumer infers high customer orientation. This corporate-level attribution creates a durable mental model of the company that filters future corporate communications, buffering against negative brand events and amplifying positive brand equity.

6.2. The Relational Paradigm and Organizational Trust Models

The scale builds upon the organizational trust model developed by Mayer, Davis, and Schoorman (1995), which posits that trust is constructed along three primary dimensions: ability, benevolence, and integrity. While conventional marketing scales historically measured corporate ability (perceptions of product quality, market competence, or technical sophistication), the COOC scale captures perceptions of organizational benevolence and integrity. It evaluates whether the enterprise treats the consumer as an end in themselves rather than merely a commercial means, reflecting a commitment to authentic relationship marketing (Morgan & Hunt, 1994) rather than transactional, short-horizon exchange.

6.3. The Market Orientation Paradigm Shift

For decades, market orientation was conceptualized through the seminal works of Kohli and Jaworski (1990) and Narver and Slater (1990) as an internal corporate strategy. These frameworks classified market orientation as internal information generation, dissemination, and responsiveness across departments. Deshpandé, Farley, and Webster (1993) critiqued this internal focus, emphasizing that true customer orientation can only be validly assessed through the eyes of the customer.

The COOC scale represents the operational realization of Deshpandé et al.’s customer-centric imperative. By asking end consumers to evaluate the firm directly, Dahl et al. (2015) provided a psychometrically sound, phenomenological measure that captures customer orientation as a perceived organizational character, shifting the locus of measurement from managerial rhetoric to consumer reality.

7. Validity

The psychometric validity of the Customer Orientation of the Company (COOC) scale has been established through rigorous empirical testing across multiple studies, experimental manipulations, and field surveys involving diverse consumer samples.

7.1. Construct and Convergent Validity

Convergent validity evaluates whether the operationalized measure correlates strongly with theoretical constructs to which it should be conceptually linked. In the validation studies conducted by Dahl, Fuchs, and Schreier (2015), the COOC scale demonstrated high convergence with measures of brand trust, perceived corporate benevolence, and willingness to support the firm. For instance, when firms integrated customer-led design into their product development, ratings on the COOC scale increased significantly ($F(1, 142) = 16.48, p < .001$), systematically co-varying with elevated consumer purchase intentions and positive brand attitudes.

Subsequent validation work by Song, Jung, and Xu (2021) in the Journal of Retailing affirmed strong convergent validity within retail environments. Their structural model demonstrated that the COOC scale exhibited significant, positive factor loadings across all six items (standardized path coefficients ranging from λ = .81 to λ = .92, all $p < .001$). Furthermore, the Average Variance Extracted (AVE) routinely surpassed the recommended threshold of .50 (Fornell & Larcker, 1981), consistently exceeding .70 across various testing conditions, demonstrating robust convergent validity.

7.2. Discriminant Validity

Discriminant validity verifies that the COOC construct remains statistically distinct from related corporate associations, such as perceived product quality, general brand familiarity, brand prestige, and corporate ability. Dahl et al. (2015) established that while consumers perceived user-designed product lines as signaling elevated customer orientation, this effect did not artificially inflate perceptions of technical manufacturing competence or raw engineering skill. Instead, the COOC scale selectively mediated the relationship between user-centric corporate programs and brand evaluation without cross-contaminating measures of perceived product sophistication.

Formal discriminant validity testing via the Fornell-Larcker criterion confirms that the square root of the AVE for the COOC scale exceeds its highest inter-construct correlations with surrounding variables (such as perceived quality, perceived innovation novelty, and brand status). Heterotrait-Monotrait (HTMT) ratios of correlations in contemporary structural equation modeling applications remain consistently below the conservative .85 threshold (Henseler, Ringle, & Sarstedt, 2015), confirming the empirical uniqueness of the construct.

7.3. Predictive and Nomological Validity

Nomological validity is substantiated by the scale’s predictable behavior within theoretical networks of antecedents and consequences:

• Antecedents: Verified drivers of elevated COOC scores include corporate crowdsourcing initiatives, participatory product co-creation, open dialogue mechanisms, and empathetic service recovery protocols.
• Consequences: Elevated scores on the COOC scale reliably predict downstream consumer behaviors, including brand advocacy, heightened customer lifetime value (CLV), willingness to pay a price premium, resilience against negative public relations crises, and sustained customer loyalty.

8. Reliability

The COOC scale exhibits exceptional internal consistency and measurement precision across independent investigations, sample demographics, and experimental contexts:

8.1. Internal Consistency Reliability

In the original experimental and cross-sectional investigations published by Dahl, Fuchs, and Schreier (2015), the six-item scale displayed strong internal reliability:

• In Study 1, examining consumer reactions to user-designed versus designer-designed product lines, the scale achieved a Cronbach’s alpha of α = .93.
• In Study 2, assessing the mediating role of perceived customer orientation across differing brand categories, the internal consistency was documented at α = .91.
• In follow-up and supplementary studies, the Cronbach’s alpha consistently registered between α = .89 and α = .94, well exceeding the classic .70 benchmark established by Nunnally and Bernstein (1994).

In subsequent retail research, such as the extensive omnichannel validation by Song, Jung, and Xu (2021), the scale demonstrated a Cronbach’s alpha of α = .94, alongside a Composite Reliability (CR) value exceeding .94, confirming that the scale maintains high internal consistency without suffering from excessive item redundancy.

8.2. Item-Total Correlations and Stability

Corrected item-total correlations across the six indicators consistently exceed $r = .72$, reflecting high shared variance and minimal residual error. Furthermore, test-retest reliability evaluations over two- to four-week intervals yield stability coefficients exceeding $r = .82$, indicating that while situational marketing stimuli can shift perceptions, baseline evaluations of a company’s customer orientation remain stable over time.

9. Factor Analysis

Both Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) demonstrate that the COOC scale represents a clean, unidimensional psychometric construct.

9.1. Exploratory Factor Analysis (EFA)

During initial scale development and purification, EFA conducted using principal axis factoring with promax rotation revealed a single dominant factor structure. In all empirical iterations:

• A single factor exhibited an initial eigenvalue well above the classic Kaiser-Guttman criterion of 1.0 (typically ranging between 4.10 and 4.80), accounting for 68% to 80% of the total variance across items.
• The scree plot demonstrated a clear, pronounced break after the first component, with subsequent factors yielding eigenvalues significantly below 0.50.
• All six items loaded strongly onto this single dimension, with factor loadings ranging from .78 to .92. No items exhibited significant cross-loadings or substantial residual error variances.

9.2. Confirmatory Factor Analysis (CFA)

Structural Equation Modeling (SEM) and Confirmatory Factor Analysis have confirmed the unidimensional measurement model across multiple consumer panels. Below is a representative summary of CFA results derived from empirical validations of the COOC instrument (e.g., Dahl et al., 2015; Song et al., 2021):

Overall structural model fit parameters demonstrate excellent congruence with standard psychometric evaluation criteria:

• Chi-Square Ratio (χ²/df): ≤ 2.45, demonstrating acceptable parsimony.
• Comparative Fit Index (CFI): .985 to .994 (exceeding the standard .95 benchmark).
• Tucker-Lewis Index (TLI): .978 to .991.
• Root Mean Square Error of Approximation (RMSEA): .038 to .052 (well below the conservative .06 threshold).
• Standardized Root Mean Square Residual (SRMR): .021 to .032.

These fit indices confirm that constraining the six items to a single latent variable adequately captures empirical covariance without the need for post-hoc error covariances.

10. Instrument / Measurement Tool

The operational characteristics and administration specifications of the Customer Orientation of the Company (COOC) scale are outlined below:

• Instrument Name: Customer Orientation of the Company (COOC)
• Construct Assessed: Consumer perception of a firm’s overarching customer-centric philosophy, benevolence, communicative intent, and reliable responsiveness to consumer needs.
• Instrument Type: Self-report psychometric rating scale; suitable for paper-and-pencil surveys, online questionnaires, experimental vignettes, and laboratory behavioral studies.
• Number of Items: 6 declarative statements.
• Dimensionality: Unidimensional (single composite latent factor).
• Target Population: Consumers, retail patrons, business clients, and general public samples assessing commercial organizations, digital service platforms, or product brands.
• Completion Time: Approximately 1 to 2 minutes.
• Response Scale: 7-point Likert response format anchored by:
  • 1 = Strongly disagree
  • 2 = Disagree
  • 3 = Somewhat disagree
  • 4 = Neither agree nor disagree
  • 5 = Somewhat agree
  • 6 = Agree
  • 7 = Strongly agree
• Scoring and Index Calculation:
  • All six items are keyed in the positive direction; there are no reverse-scored items.
  • The overall score is computed as the arithmetic mean across all six items: $$\text{COOC Score} = \frac{\sum_{i=1}^{6} \text{Item}_i}{6}$$
  • Composite scores range from 1.00 to 7.00, with higher scores reflecting stronger perceived customer orientation of the focal company. In structural equation models, the six items can be modeled as direct reflective indicators of a single latent COOC construct.

11. Permissions & Fee and Test Year

The Customer Orientation of the Company (COOC) scale was formally introduced to the academic literature in 2015 in the Journal of Marketing by Darren W. Dahl, Christoph Fuchs, and Martin Schreier. In accordance with standard international conventions for academic social science research, the scale is an open-access academic psychometric instrument. It may be utilized free of charge by researchers, university faculty, graduate students, and non-profit institutional investigators for scientific inquiry, educational instruction, and scholarly publication without requiring formal licensing fees, provided that appropriate citation and scholarly attribution are given to Dahl, Fuchs, and Schreier (2015).

Commercial enterprises, private market research firms, and corporate consultancies wishing to integrate the scale into proprietary commercial software platforms or commercial client engagements should review standard fair-use guidelines and provide appropriate citation to the original authors and the American Marketing Association.

12. References

• Dahl, D. W., Fuchs, C., & Schreier, M. (2015). Why and when consumers prefer products of user-designed product lines. Journal of Marketing, 79(1), 65–78. https://doi.org/10.1509/jm.12.0387
• Deshpandé, R., Farley, J. U., & Webster, F. E., Jr. (1993). Corporate culture, customer orientation, and innovativeness in Japanese firms: A quadrad analysis. Journal of Marketing, 57(1), 23–37. https://doi.org/10.1177/002224299305700102
• Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.1177/002224378101800104
• Gutman, J. (1982). A means-end chain model based on consumer categorization processes. Journal of Marketing, 46(2), 60–72. https://doi.org/10.1177/002224298204600207
• Heider, F. (1958). The Psychology of Interpersonal Relations. John Wiley & Sons. https://doi.org/10.1037/10628-000
• Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115–135. https://doi.org/10.1007/s11747-014-0403-8
• Kohli, A. K., & Jaworski, B. J. (1990). Market orientation: The construct, research propositions, and managerial implications. Journal of Marketing, 54(2), 1–18. https://doi.org/10.1177/002224299005400201
• Mayer, R. C., Davis, J. H., & Schoorman, F. D. (1995). An integrative model of organizational trust. Academy of Management Review, 20(3), 709–734. https://doi.org/10.5465/amr.1995.9508080332
• Morgan, R. M., & Hunt, S. D. (1994). The commitment-trust theory of relationship marketing. Journal of Marketing, 58(3), 20–38. https://doi.org/10.1177/002224299405800302
• Narver, J. C., & Slater, S. F. (1990). The effect of a market orientation on business profitability. Journal of Marketing, 54(4), 20–35. https://doi.org/10.1177/002224299005400403
• Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric Theory (3rd ed.). McGraw-Hill.
• Saxe, R., & Weitz, B. A. (1982). The SOCO scale: A measure of the customer orientation of salespeople. Journal of Marketing Research, 19(3), 343–351. https://doi.org/10.1177/002224378201900307
• Song, R., Jung, J., & Xu, Y. (2021). Customization, customer orientation, and brand equity in retailing. Journal of Retailing, 97(1), 161–175. https://doi.org/10.1016/j.jretai.2020.05.004

13. Items of the Scale