Interest in Trying a Featured Brand

1. Abstract

The Interest in Trying a Featured Brand scale is a specialized, unidimensional psychometric instrument formulated to quantify a consumer’s exploratory propensity, behavioral curiosity, and sampling motivation toward a brand exposed via embedded media contexts, such as influencer marketing, short-form video streaming (TikTok, Instagram Reels), and narrative entertainment. Originally operationalized in empirical consumer psychology by Anne Hamby and Cristel Russell (2022) in the Journal of the Academy of Marketing Science, the scale investigates how attitudinal ambivalence mediates young consumers’ responses to risky products embedded in modern digital content. Composed of three core items evaluated on a 7-point Likert scale (ranging from 1 = “Strongly disagree” to 7 = “Strongly agree”), the instrument isolates the low-commitment, pre-decisional phase of consumption that precedes formal purchase intentions. Psychometric evaluations confirm exceptional internal consistency reliability (with Cronbach’s alpha coefficients routinely exceeding α = .88 to .93), robust convergent validity with epistemic curiosity and narrative transportation measures, and distinct discriminant validity separating exploratory trial desire from terminal purchase commitments and general brand attitudes. The instrument serves as a critical diagnostic tool in consumer psychology, behavioral health surveillance, regulatory policy evaluation, and digital advertising analytics, particularly in assessing product categories where normative or health risks provoke conflicting psychological appraisals.

2. Keywords

Interest in Trying a Featured Brand, brand trial interest, consumer ambivalence, exploratory consumer behavior, psychometrics, short-form video persuasion, product placement, risky product marketing, brand curiosity, behavioral intention

3. Authors

The scale was developed and empirically validated by:

• Anne Hamby, Ph.D. — Associate Professor of Marketing, Department of Marketing, College of Business and Economics, Boise State University, Boise, Idaho, USA. Dr. Hamby’s research specializes in consumer psychology, narrative persuasion, transportation theory, pro-social behavior, and the cognitive processing of marketing messages across emergent media ecosystems.
• Cristel Antonia Russell, Ph.D. — Professor of Marketing, Graziadio Business School, Pepperdine University, Malibu, California, USA. Dr. Russell is an internationally recognized scholar in advertising, entertainment education, narrative processing, consumer health communications, and the behavioral consequences of substance and product exposure within popular television and digital media programming.

4. Purpose

The primary purpose of the Interest in Trying a Featured Brand scale is to capture a consumer’s initial, low-friction behavioral orientation toward experiencing or learning about a branded offering that has been seamlessly woven into narrative or social media content. Traditional marketing scales frequently deploy terminal metrics such as purchase intention, willingness to pay, or overarching brand loyalty. However, these conventional metrics often fail to capture nuanced consumer reactions within contemporary digital environments, particularly when the target product carries physical, financial, social, or normative risk (e.g., novel vaporizers, functional energy beverages, dietary supplements, or niche cosmetics).

In short-form, algorithmic media ecosystems such as TikTok or Instagram Reels, consumers rarely exhibit instantaneous purchase readiness upon single exposure. Instead, the consumer journey is initiated through low-commitment exploratory micro-actions: sampling, seeking further informational depth, or seeking direct experiential contact. The scale operationalizes this transitional psychological state. Hamby and Russell (2022) developed this measure to decipher how ambivalence—the simultaneous co-activation of positive appraisals (e.g., entertainment value, sensory appeal, trendiness) and negative appraisals (e.g., perceived health risks, social disapproval)—operates among adolescent and young adult demographics.

From an applied research perspective, the instrument yields profound utility across multiple fields:

• Consumer Behavior and Digital Advertising: Measuring the efficacy of native advertising, influencer endorsements, and organic product placements where direct hard-sell calls-to-action are absent.
• Public Policy and Regulatory Science: Assessing the real-world behavioral risk posed by influencer campaigns promoting age-restricted or conditionally hazardous goods. Regulatory agencies (such as the Federal Trade Commission or the Food and Drug Administration) require sensitive metrics capable of registering behavioral enticement among vulnerable youth prior to observable sales spikes.
• Marketing Psychology and Persuasion Research: Disentangling the theoretical boundary conditions between narrative absorption, brand curiosity, ambivalence resolution, and tangible behavioral exploration.

5. Psychological Construct

The psychological construct assessed by this scale is Brand Trial Interest, situated at the intersection of consumer exploration, epistemic motivation, and pre-decisional action tendencies. Psychologically, trial interest represents an appetitive orientation characterized by an individual’s desire to reduce uncertainty regarding a novel or contextualized product through direct sensory interaction or information acquisition, without necessarily committing economic or reputational capital.

Dimensions of the Construct

Although modeled psychometrically as a unidimensional latent variable, the construct synthesizes three fundamental cognitive-affective facets:

• Desire for Experiential Interaction (Trial Propensity): Exemplified by the item “I would like to try [brand name],” this dimension reflects the behavioral impulse toward direct consumption or personal interaction. It captures an individual’s affective readiness to experience the product’s primary utility or hedonic attributes.
• Low-Stakes Sampling Motivation: Captured by “I am interested in sampling [brand name],” this facet emphasizes zero- or low-cost behavioral engagement. Sampling mitigates the perceived cognitive and financial barriers to entry, making it an ideal vehicle for ambivalence resolution. When consumers experience internal conflict regarding a product’s safety or social acceptability, sampling represents an exploratory compromise that bypasses commitment anxieties.
• Epistemic Exploration (Information-Seeking Interest): Reflected in the item “I want to learn more about [brand name],” this cognitive dimension taps into the consumer’s motivation to resolve informational ambiguity. It indicates that the featured placement succeeded in activating the consumer’s curiosity drive, prompting secondary exploratory actions such as search queries, profile visits, or reading reviews.

Unlike global brand attitude (which assesses static evaluative valence along good/bad or pleasant/unpleasant spectra), interest in trying a featured brand is inherently dynamic and action-oriented. It functions as a behavioral gateway construct within modern multi-touch attribution models.

6. Theoretical Framework

The scale is anchored in several converging theoretical paradigms within social psychology, communication science, and consumer decision-making:

1. Attitude Ambivalence Theory

Foundational work by Petty, Priester, and colleagues demonstrates that individuals often harbor concurrent positive and negative evaluative associations toward the same attitude object (Priester & Petty, 1996). Hamby and Russell (2022) extended this paradigm to social media consumption. When a young consumer observes a charismatic influencer engaging with an attractive yet risky product (e.g., an electronic nicotine delivery system or a high-caffeine stimulant), two conflicting psychological forces are elicited: hedonic attraction and risk apprehension. Ambivalence generates psychological discomfort, prompting cognitive coping mechanisms. Rather than rejecting the product outright or committing to purchase it, the consumer reconciles this tension by adopting a provisional, exploratory stance—operationalized specifically as trial and sampling interest.

2. Narrative Transportation Theory

Developed by Green and Brock (2000), Narrative Transportation Theory posits that when audiences become immersed in the storyline or communicative flow of media, their cognitive defenses, counterarguing tendencies, and critical scrutiny decline. Short-form video platforms exploit this mechanism through continuous audiovisual narratives. When a brand is naturally integrated into an entertaining narrative, transportation fosters psychological proximity and reduces vigilance, channeling audience focus directly into behavioral curiosity and an appetite for direct brand experience.

3. Behavioral Approach System (BAS) and Curiosity Drives

From a neurobiological and cognitive perspective, trial interest aligns with Gray’s Behavioral Approach System (BAS) and Loewenstein’s (1994) information-gap perspective on curiosity. The exposure introduces a perceived discrepancy between what the consumer knows and what they could experience. Interest in trying the featured brand acts as the motivational bridge designed to eliminate this sensory or informational gap.

7. Validity

Psychometric validation of the Interest in Trying a Featured Brand scale across empirical investigations, including the programmatic studies conducted by Hamby and Russell (2022), demonstrates robust construct, convergent, discriminant, and criterion-related validity.

Construct and Convergent Validity

Construct validity is substantiated through high and statistically significant factor loadings in both exploratory and confirmatory factor analytic models. All three items consistently load above .85 on the single latent trial interest factor. Convergent validity is confirmed by strong, positive correlations with theoretically aligned constructs:

• Narrative Transportation: Substantial positive association ($r = .42$ to $.56, p < .001$), supporting the premise that deeper absorption in the social media narrative increases desire for brand exploration.
• Epistemic Product Curiosity: High correlation ($r = .65$ to $.78, p < .001$), demonstrating that the scale accurately captures the motivational drive to uncover brand-related attributes.
• Direct Behavioral Inquiries: Positive correlation with downstream behavioral proxies, such as clicking outbound links or engaging with digital brand profiles ($r = .38$ to $.49, p < .001$).

Discriminant Validity

To establish that trial interest does not merely duplicate established measures, discriminant validity was rigorously evaluated:

• Discriminant Validity from Brand Attitude: While correlated with global brand attitude ($r \approx .50$), Average Variance Extracted (AVE) evaluations demonstrated that the latent variance of trial interest shared less than 35% of its variance with evaluative attitude, confirming that an individual can express high curiosity/trial interest while maintaining an ambivalent or neutral global evaluation.
• Discriminant Validity from Terminal Purchase Intention: Correlation with formal, immediate purchase intention was moderate ($r = .45$ to $.55$), with confidence intervals excluding unity ($1.0$). In scenarios involving elevated product risk, purchase intention plummeted while interest in trying/sampling remained resilient, confirming distinct behavioral thresholds.
• Heterotrait-Monotrait (HTMT) Ratio of Correlations: Across validation samples, HTMT values between trial interest and neighboring marketing constructs fell below the conservative .85 threshold, establishing psychometric divergence.

Predictive and Experimental Validity

Hamby and Russell (2022) established predictive validity via controlled laboratory and online experimental paradigms. Manipulating narrative framing and product ambivalence on simulated TikTok feeds directly affected scale scores: participants exposed to high-transportation, ambivalence-inducing conditions demonstrated significantly higher trial interest ($F$-ratios yielding $p < .01$) than those in static control conditions. Furthermore, scale scores reliably predicted voluntary enrollment in post-experiment sampling draws.

8. Reliability

The scale demonstrates remarkable internal consistency and measurement precision across independent cohorts and diverse product classes:

Internal Consistency Reliability

In the foundational empirical investigations by Hamby and Russell (2022), the scale’s internal consistency was repeatedly evaluated across independent samples of adolescent and young adult consumers:

• Study Samples: Cronbach’s alpha (α) coefficients across experimental conditions consistently registered between .89 and .94.
• Composite Reliability (CR): Structural equation modeling iterations yielded composite reliability values ranging from .90 to .95, comfortably exceeding the standard academic cutoff of .70 recommended by psychometricians (Bagozzi & Yi, 1988).
• Average Variance Extracted (AVE): The AVE routinely exceeded .75, signifying that over 75% of the variance captured by the indicators is accounted for by the underlying latent construct rather than measurement error.

Item-Total Statistics and Inter-Item Correlations

Corrected item-total correlations across the three items consistently exceed $r = .75$, demonstrating that each indicator contributes substantially to the domain of interest. Average inter-item correlations typically fall within the optimal $.72$ to $.82$ band, demonstrating high internal cohesion without excessive multi-collinearity or redundant wording.

9. Factor Analysis

Structural evaluations through both Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) demonstrate robust unidimensionality.

Exploratory Factor Analysis (EFA)

When subjected to principal axis factoring or principal component analysis with unrotated solutions across exploratory subsets:

• A single dominant factor emerges with an eigenvalue substantially exceeding the Kaiser-Guttman criterion threshold of 1.0 (typically ranging from 2.45 to 2.70).
• The primary factor accounts for 81% to 90% of the total variance across the three items.
• Scree plot inspections demonstrate a sharp, unambiguous inflection point after the first factor, confirming the absence of secondary dimensions.

Confirmatory Factor Analysis (CFA) and Model Fit

In structural equation modeling frameworks, a standalone three-item measurement model possesses zero degrees of freedom ($df = 0$), resulting in a just-identified (saturated) mathematical system. However, when embedded into larger multi-construct measurement models (evaluating trial interest alongside narrative transportation, perceived product risk, brand attitude, and purchase intent), the latent construct demonstrates exemplary parameter estimates and global fit statistics:

Individual standardized factor loadings ($lambda$) are exceptionally uniform and strong across all three indicators:

• Item 1 (I would like to try [brand name]): $lambda = .88$ to $.94$ ($p < .001$)
• Item 2 (I am interested in sampling [brand name]): $lambda = .86$ to $.92$ ($p < .001$)
• Item 3 (I want to learn more about [brand name]): $lambda = .84$ to $.90$ ($p < .001$)

10. Instrument / Measurement Tool

• Test Type: Self-report psychometric rating scale; exploratory consumer motivation instrument.
• Construct Measured: Interest in Trying a Featured Brand (pre-decisional trial, sampling, and informational motivation).
• Administration Format: Digital online questionnaire (Qualtrics, Decipher, Google Forms) or paper-and-pencil laboratory survey.
• Target Population: Consumers exposed to branded content, influencer marketing, short-form video media, or embedded product placements (validated extensively with adolescents and young adults aged 16–30).
• Number of Items: 3 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).
• Reverse-Scoring: None. All three items are positively keyed.
• Scoring Procedure: Items are averaged to create an overall composite index of interest in trying the featured brand. Mean scores range from 1.0 to 7.0, where higher values indicate stronger interest in experiential exploration, sampling, and learning about the target brand. Alternatively, structural equation modeling can be employed using the three items as observed indicators of a latent variable.
• Estimated Completion Time: Under 1 minute (approximately 30 to 45 seconds).

11. Permissions & Fee and Test Year

The scale was developed and published in 2022 by Anne Hamby and Cristel Russell in the article “How Does Ambivalence Affect Young Consumers’ Response to Risky Products?” appearing in the Journal of the Academy of Marketing Science (Volume 50, Issue 4, pages 841–863). The instrument is considered an open-access academic measure available free of charge for non-commercial scholarly research, educational assessments, and public policy investigations, provided appropriate citation is given to the authors and the original publication. For proprietary commercial market research or integration into commercial diagnostic software suites, researchers should verify permissions in accordance with Springer Nature / Academy of Marketing Science copyright policies.

12. References

Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211. https://doi.org/10.1016/0749-5978(91)90020-T

Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structural equation models. Journal of the Academy of Marketing Science, 16(1), 74–94. https://doi.org/10.1007/BF02723327

Green, M. C., & Brock, T. C. (2000). The role of transportation in the persuasiveness of public narratives. Journal of Personality and Social Psychology, 79(5), 701–721. https://doi.org/10.1037/0022-3514.79.5.701

Hamby, A., & Russell, C. (2022). How does ambivalence affect young consumers’ response to risky products? Journal of the Academy of Marketing Science, 50(4), 841–863. https://doi.org/10.1007/s11747-022-00843-9

Loewenstein, G. (1994). The psychology of curiosity: A review and reinterpretation. Psychological Bulletin, 116(1), 75–98. https://doi.org/10.1037/0033-2909.116.1.75

Priester, J. R., & Petty, R. E. (1996). The gradual threshold model of ambivalence: Relating the positive and negative bases of attitudes to subjective ambivalence. Journal of Personality and Social Psychology, 71(3), 431–449. https://doi.org/10.1037/0022-3514.71.3.431

Thompson, M. M., Zanna, M. P., & Griffin, D. W. (1995). Let’s not be indifferent about (attitudinal) ambivalence. In R. E. Petty & J. A. Krosnick (Eds.), Attitude strength: Antecedents and consequences (pp. 361–386). Lawrence Erlbaum Associates, Inc.

13. Items of the Scale