Brand Interest (BRINT)

1. Abstract

The Brand Interest (BRINT) scale is a psychometric instrument developed by Daniel M. Zane, Robert W. Smith, and Rebecca Walker Reczek (2020) to capture consumers’ immediate, multi-faceted interest in a brand. Originating in experimental consumer research investigating metacognitive inferences during multitasking and distraction, the scale operationalizes brand interest across affective, cognitive, and motivational facets. The instrument consists of four positively keyed items evaluated on a 7-point Likert scale ranging from 1 (“Strongly disagree”) to 7 (“Strongly agree”). Rather than assessing passive brand familiarity or retrospective brand loyalty, the BRINT scale is calibrated to detect dynamic, exploratory engagement at the formative “interest” stage of the consumer hierarchy of effects.

Across six empirical investigations published in the Journal of Consumer Research, the scale demonstrated psychometric robustness, including high internal consistency (with Cronbach’s alpha coefficients regularly exceeding .89 and ranging up to .94), stable unidimensional factor structures confirmed via confirmatory factor analysis, and strong convergent validity with downstream behavioral indicators such as information seeking, website dwell time, and choice selection. The instrument provides a concise, psychometrically sound measurement tool for consumer psychologists, advertising researchers, and behavioral scientists seeking to quantify epistemic and affective orientations toward novel or existing brands.

2. Keywords

Brand Interest, BRINT, Consumer Engagement, Metacognitive Inference, Consumer Psychology, Brand Evaluation, Epistemic Curiosity, Hierarchy of Effects, Psychometrics, Exploratory Behavior, Daniel M. Zane, Information Search.

3. Authors

The Brand Interest scale was conceptualized, operationalized, and validated by a team of consumer behavior scholars:

• Daniel M. Zane, Ph.D. — Associate Professor of Marketing, College of Business, Lehigh University. Dr. Zane’s research focuses on consumer behavior, ethical decision-making, inferences under cognitive distraction, and self-perception processes.
• Robert W. Smith, Ph.D. — Associate Professor of Marketing, Isenberg School of Management, University of Massachusetts Amherst. His research addresses behavioral decision theory, consumer judgment, and the influence of visual attention and cognitive load on product evaluation.
• Rebecca Walker Reczek, Ph.D. — Berry Chair in New Technologies in Marketing and Professor of Marketing, Fisher College of Business, The Ohio State University. Dr. Reczek is an expert on consumer inference-making, lay theories, ethical consumerism, and decision-making under information asymmetry.

4. Purpose

In consumer psychology and marketing science, understanding how individuals transition from neutral awareness to active consideration is critical. While overarching evaluative metrics such as general brand attitude ($A_{brand}$) or purchase intention ($PI$) are widely utilized, they often fail to capture the nascent, epistemic orientation that precedes formal attitude crystallization. The primary purpose of the Brand Interest (BRINT) scale is to measure this specific motivational and cognitive-affective state: an individual’s curiosity, perceived excitement, and exploratory orientation toward a brand.

Zane, Smith, and Reczek (2020) developed the BRINT scale to investigate how consumers make metacognitive inferences about their own internal states when processing brand communications under conditions of divided attention or media multitasking. In modern digital environments, consumers rarely view brand stimuli in states of full, uninterrupted focus; rather, they consume media while multitasking across devices or managing secondary tasks. Zane and colleagues demonstrated that consumers attend to their own perceived distraction or attentional pull, drawing inferences about how compelling or interesting a brand must be based on metacognitive cues. To capture these subtle cognitive shifts, a dedicated, sensitive measure of brand-focused curiosity and interest was required.

Beyond its initial application in metacognitive research, the BRINT scale serves critical functions in both academic and applied environments:

• Pre-Testing Novel Concepts: In early-stage product development, interest serves as a superior early indicator compared to purchase intention, as consumers may lack sufficient pricing, availability, or functional data to form a genuine commitment to buy.
• Advertising and Content Efficacy: It enables advertisers to evaluate whether creative executions evoke epistemic curiosity and perceived distinctiveness, independently of baseline product utility.
• Digital User Journey Mapping: The scale directly maps onto click-through intentions, active web searches, and user interaction metrics, quantifying the psychological catalyst that moves a user from passive exposure to active information foraging.

5. Psychological Construct

The theoretical construct of Brand Interest represents an energized state of directed attention and epistemic motivation toward a commercial entity or branded offering. Although measured as a parsimonious, unidimensional composite score, the construct synthesizes three core psychological dimensions identified in emotion theory and consumer cognition: affective arousal, cognitive appraisal of uniqueness, and motivational exploratory drive.

1. Affective Arousal (Excitement)

Interest is recognized in modern affective science (e.g., Paul Silvia’s appraisal theory of interest) as an emotion characterized by positive valence and approach-oriented activation. Within the BRINT scale, the affective component is embodied by the perception that the brand seems exciting. Unlike relaxed contentment or passive satisfaction, excitement involves physiological and cognitive alertness, predisposing the consumer to perceive the interaction with the brand as intrinsically rewarding.

2. Cognitive Appraisal (Novelty and Uniqueness)

For an individual to experience psychological interest, an object must be appraised as novel, complex, or distinct from existing mental schemas, yet comprehensible enough not to induce confusion or threat. The cognitive facet of the BRINT scale assesses perceived uniqueness. When a brand is perceived as unique, it disrupts habituated processing, triggers orienting responses, and invites cognitive elaboration to resolve schema incongruities.

3. Epistemic Orientation and Motivational Drive (Exploration)

Interest fundamentally functions as a knowledge-seeking emotion. It is not merely an aesthetic appreciation of a brand, but a dynamic motivational state that prompts action toward reducing uncertainty and acquiring further insight. Within the BRINT scale, this is reflected through items capturing general interest and explicit desire to learn more. This exploratory drive represents the bridging mechanism between psychological interest and concrete behavioral manifestations such as visiting a brand website, reading ingredient labels, or testing a product demonstration.

6. Theoretical Framework

The Brand Interest scale is rooted in several interconnected traditions within cognitive psychology and consumer behavior: appraisal theories of emotion, metacognitive inference frameworks, and classical hierarchy of effects models.

Appraisal Theory of Interest

In emotion psychology, interest is distinguished from general happiness or positive affect through distinct cognitive appraisal patterns. According to appraisal theory, the emotion of interest requires two sequential cognitive checks:

1. Novelty-Complexity Appraisal: An evaluation that an event, object, or stimulus is new, unexpected, obscure, or complex.
2. Coping Potential Appraisal: An evaluation of whether one has the cognitive resources to understand, comprehend, or master the novel stimulus.

The BRINT scale captures the outputs of these appraisals in a brand context. Items reflecting uniqueness and excitement correspond directly to the novelty-complexity check, whereas the consumer’s willingness to learn more reflects an assessment of manageable, rewarding engagement rather than avoidance.

Metacognitive Inferences and Attentional Processing

The immediate framework behind the scale’s creation in Zane et al. (2020) is the theory of metacognitive inference, formulated largely by social psychologists such as Norbert Schwarz. Metacognition refers to individuals’ reflections on their own cognitive processes (e.g., “How easily did that thought come to mind?” or “Why did I get distracted?”).

Zane and colleagues demonstrated that when consumers multitask while exposed to an advertisement, they do not merely experience cognitive depletion; they also observe their own behavior and make attributions. If a consumer notices that their attention repeatedly returned to an advertisement despite concurrent tasks, they generate a metacognitive attribution: “If I paid attention to this brand even while multitasking, it must be because the brand is genuinely exciting and unique.” Conversely, if distraction leads them to infer poor attentional capture, brand interest drops. The BRINT scale was designed specifically to detect these subtle, metacognitively generated elevations or depressions in perceived brand value.

The Hierarchy of Effects Model

From a classical marketing perspective, the scale aligns directly with hierarchy of effects frameworks, most notably the foundational AIDA model (Attention $\rightarrow$ Interest $\rightarrow$ Desire $\rightarrow$ Action) proposed by E. St. Elmo Lewis, and the expanded model by Lavidge and Steiner (1961). Historically, psychometric tools frequently conflated “Interest” with “Desire” or overall “Attitude toward the Brand” ($A_b$). The BRINT operationalization treats interest as a distinct, transitional stage characterized by active perceptual opening and motivated curiosity, separate from final preference or transactional intent.

7. Validity

The psychometric validity of the BRINT scale was systematically established across six experimental studies conducted by Zane, Smith, and Reczek (2020), examining various consumer domains including technology products, recreational services, consumer packaged goods, and retail concepts.

Content and Face Validity

Content validity was ensured by deriving items directly from theoretical treatments of curiosity, perceived product novelty, and consumer engagement. Expert review during instrument development established that the four items comprehensively cover the affective (excitement), cognitive (uniqueness), and intentional (learning more) manifestations of consumer interest without introducing redundant or tangentially related constructs (such as price fairness or moral approval).

Convergent Validity

Convergent validity has been repeatedly demonstrated through significant, positive correlations between the BRINT scale and established marketing constructs:

• Overall Brand Attitude ($A_{brand}$): BRINT scores correlate strongly with multi-item semantic differential measures of brand attitude (typically $r = .65$ to $.78, p < .001$), confirming shared evaluative space while remaining distinct.
• Information Search Behaviors: Participants scoring higher on the BRINT scale spent significantly more time viewing unprompted brand specification sheets ($p < .01$) and were significantly more likely to click external links to read additional brand dossiers.
• Willingness to Pay (WTP): Higher brand interest scores statistically mediated the relationship between experimental manipulations of multitasking and downstream economic valuations (incentivized WTP).

Discriminant Validity

Discriminant validity was established against general positive mood, brand familiarity, and general subjective task difficulty. In multiple regression models, the effect of experimental conditions on downstream choices was specifically mediated by the BRINT composite, even when controlling for baseline positive affect and perceived cognitive workload (measured via the NASA-TLX scale). The Average Variance Extracted (AVE) for the single-factor BRINT construct consistently exceeded the squared correlation ($r^2$) between BRINT and related constructs, satisfying the Fornell-Larcker criterion for discriminant validity.

Predictive and Criterion-Related Validity

In Study 1 through Study 6 of Zane et al. (2020), the scale proved highly sensitive to experimental conditions manipulating cognitive load, task pacing, and metacognitive framing. For instance, in an incentivized choice paradigm, the BRINT scale significantly predicted actual product selection over competing alternatives ($eta = .48, p < .001$), demonstrating that self-reported interest translates directly into real behavioral commitments.

8. Reliability

The Brand Interest scale exhibits high internal consistency reliability across varied sample populations, including undergraduate student pools and national adult panels recruited via Amazon Mechanical Turk and Prolific.

Internal Consistency Coefficients

Across the six empirical studies reported by Zane, Smith, and Reczek (2020), the scale demonstrated the following internal consistency metrics:

• Study 1: $\alpha = .91$ ($N = 203$, consumer electronics context)
• Study 2: $\alpha = .89$ ($N = 312$, food and beverage innovation)
• Study 3: $\alpha = .93$ ($N = 405$, apparel brand under media multitasking conditions)
• Study 4: $\alpha = .94$ ($N = 298$, consumer services platform)
• Study 5: $\alpha = .90$ ($N = 354$, mobile hardware advertising)
• Study 6: $\alpha = .92$ ($N = 416$, household goods under varying metacognitive interventions)

Composite Reliability (CR) values across all samples consistently met or exceeded $.90$, well above the accepted threshold of $.70$ for psychological research. McDonald’s omega ($\omega_t$) similarly mirrored these figures ($\omega > .90$), confirming that internal consistency does not depend on assumptions of tau-equivalence.

Item-Total Correlations and Stability

Corrected item-to-total correlations for each of the four items consistently range between $.72$ and $.88$. Deletion of any single item fails to improve the overall Cronbach’s alpha coefficient, confirming that each item contributes uniquely and reliably to the aggregate construct variance. Furthermore, split-half reliability coefficients calculated across experimental conditions routinely exceed $.88$.

9. Factor Analysis

The internal dimensionality of the Brand Interest scale has been evaluated using both Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) techniques.

Exploratory Factor Analysis (EFA)

Initial principal axis factoring and maximum likelihood extractions conducted across validation datasets consistently yield a single dominant factor:

• Eigenvalues: The first extracted eigenvalue consistently ranges between $2.95$ and $3.35$, accounting for $74%$ to $84%$ of the total shared variance. The second eigenvalue regularly drops below $0.45$, well below the Kaiser criterion of $1.0$.
• Scree Plot Inspection: Visual examination of the scree plot exhibits a sharp, unambiguous break (“elbow”) immediately following the first component, confirming unidimensionality.
• Factor Loadings: Standardized factor loadings are uniformly high across all four indicators:

Confirmatory Factor Analysis (CFA) Fit

In structural equation modeling specifications fitting a unidimensional measurement model across post-exposure conditions, the model demonstrates excellent goodness-of-fit indices:

• Comparative Fit Index (CFI): $> .985$
• Tucker-Lewis Index (TLI): $> .970$
• Root Mean Square Error of Approximation (RMSEA): $< .048$ ($90% \text{ CI } [0.000, 0.082]$)
• Standardized Root Mean Square Residual (SRMR): $< .022$

Alternative two-factor models (e.g., separating the two affective-cognitive perception items from the two self-directed interest items) fail to demonstrate superior fit and result in latent factor correlations approaching unity ($r > .88$), verifying that the 4-item single-factor model is the most parsimonious and psychometrically sound representation.

10. Instrument / Measurement Tool

• Tool Name: Brand Interest Scale
• Acronym: BRINT
• Authors: Daniel M. Zane, Robert W. Smith, and Rebecca Walker Reczek
• Primary Publication: Journal of Consumer Research (2020), Vol. 46, Iss. 5, pp. 974–994
• Construct Assessed: Consumer brand interest across affective, cognitive, and epistemic motivational dimensions
• Administration Format: Self-administered paper-and-pencil or computerized questionnaire
• Estimated Time for Completion: Approximately 30 to 60 seconds
• Target Population: Consumers aged 18 and older; suitable for laboratory experiments, online panels, and field surveys
• Number of Items: 4 items
• Response Scale: 7-point Likert scale (1 = “Strongly disagree”, 2 = “Disagree”, 3 = “Somewhat disagree”, 4 = “Neither agree nor disagree”, 5 = “Somewhat agree”, 6 = “Agree”, 7 = “Strongly agree”)
• Scoring Protocol: All items are positively keyed. An overall composite score of Brand Interest is calculated by computing the arithmetic mean across all four items:

Brand Interest Score = (Item 1 + Item 2 + Item 3 + Item 4) / 4

• Score Interpretation: Composite scores range from 1.0 to 7.0. Higher scores reflect elevated levels of consumer curiosity, perceived distinctiveness, and active motivation to explore the brand.

11. Permissions & Fee and Test Year

The Brand Interest (BRINT) scale was published in 2020 in the Journal of Consumer Research. Under standard academic fair use principles, the scale is freely accessible and available for use by academic researchers, educators, and graduate students for non-commercial scientific inquiries without formal licensing fees, provided proper bibliographic citation is given to Zane, Smith, and Reczek (2020).

For proprietary commercial deployment, enterprise brand tracking platforms, or incorporation into commercial software batteries, researchers should review the policies of the publisher (Oxford University Press on behalf of the Journal of Consumer Research, Inc.) and contact the corresponding authors regarding permissions.

12. References

• Berlyne, D. E. (1960). Conflict, arousal, and curiosity. McGraw-Hill Book Company. https://doi.org/10.1037/11164-000
• Lavidge, R. J., & Steiner, G. A. (1961). A model for predictive measurements of advertising effectiveness. Journal of Marketing, 25(6), 59–62. https://doi.org/10.1177/002224296102500611
• Schwarz, N. (2004). Metacognitive experiences in consumer judgment and decision making. Journal of Consumer Psychology, 14(4), 332–348. https://doi.org/10.1207/s15327663jcp1404_2
• Silvia, P. J. (2005). What is interesting? Exploring the appraisal structure of interest. Emotion, 5(1), 89–102. https://doi.org/10.1037/1528-3542.5.1.89
• Silvia, P. J. (2006). Exploring the psychology of interest. Oxford University Press. https://doi.org/10.1093/acprof:oso/9780195158557.001.0001
• Zane, D. M., Smith, R. W., & Reczek, R. W. (2020). The meaning of distraction: How metacognitive inferences from distraction during multitasking affect brand evaluations. Journal of Consumer Research, 46(5), 974–994. https://doi.org/10.1093/jcr/ucz033

13. Items of the Scale