Microinteractions and Brand Positioning: the Role of Design Details in Brand Personality Perception

Augusto Bergamaschi Rückert; Juliana Moletta

DOI: 10.22167/2675-6528-202602699

Article derived from a Course Conclusion Work (TCC), with content based on the student’s original work and adapted to the editorial format of the E&S Magazine with the support of the ResumeAI tool, an artificial intelligence solution developed by Instituto Pecege for textual synthesis and organization.

Summary

In the attention economy, the differentiation of digital products has shifted from functionality to the quality of the user experience. This study investigated the extent to which the presence of animated microinteractions in a mobile application impacted the perception of brand personality. A quantitative and exploratory approach was adopted, in which 36 physical activity practitioners interacted with two high-fidelity prototypes of a fictitious sports application: one without animations (control) and another with animated microinteractions (variant). Brand personality perception was measured by Aaker’s Brand Personality Scale, and perceived usefulness by specific questions. The data were analyzed with statistical tests such as Welch, Mann-Whitney, and Spearman correlation. The results indicated that perceived usefulness metrics showed significant differences, with large effects in favor of the prototype with microinteractions. Although the brand personality dimensions did not reach statistical significance, there were observed trends of increase in Competence and decrease in Ruggedness. Correlational analysis revealed sincerity as the main predictor of recommendation intention. It was concluded that animated microinteractions primarily impacted the functional experience and, indirectly, the perception of brand personality. The study contributed by demonstrating that design details function as expressive vehicles for brand communication.

Keywords: Animations; Sports application; Aaker scale; User experience; Usability.

1. Introduction

In the contemporary attention economy, consumers are constantly exposed to a massive volume of information and stimuli, which intensifies competition among brands (van de Sand et al., 2020). This scenario, characterized by the attention economy, a term coined by psychologist and economist Herbert A. Simon, arises when the abundance of information makes user attention a scarce resource (Davenport and Beck, 2001). In this environment, the ability of a product or service to stand out and establish a lasting connection with the user has become crucial for marketing success. Functional quality and usability, previously perceived as competitive advantages, are currently considered basic requirements expected by consumers (van de Sand et al., 2020).

The true differentiation, therefore, lies in the quality of the experience provided to the user (van de Sand et al., 2020). User experience (UX) was initially presented by Norman et al. (1995) in the context of human-computer interaction research and applications and has since been associated with a variety of meanings (Forlizzi and Battarbee, 2005). The expression gained traction in the early 21st century as a way to articulate aspects of the use of interactive technologies that transcend the useful and the usable (Hassenzahl and Tractinsky, 2006). Hassenzahl (2008) describes user experience as an expanded perspective on the quality of interactive technology, focused on humans and the factors that drive a positive experience, such as the satisfaction of needs for autonomy, competence, stimulation, relatedness, or popularity. User experience design, in this sense, becomes the main vehicle for tangibilizing brand perception in the digital environment (van de Sand et al., 2020).

Within the vast universe of user experience, microinteractions emerge as elements that make digital products easier to engage with and more pleasurable to use. Saffer (2013) defines microinteractions as small animations or feedback mechanisms that serve a single use case and purpose. They represent functional and interactive design details of products, such as the animation of a “like” button, the sound feedback when sending a message, or the smooth transition between screens. Microinteractions have the power to transform routine interactions into moments of delight and engagement (Saffer, 2013), distinguishing a merely tolerated product from one genuinely appreciated.

The impact of these small details on the user experience is not insignificant. They play a fundamental role in communicating system status, preventing errors, and enhancing the sense of direct manipulation (Boyd and Bond, 2021). Recent studies indicate that microinteractions directly affect user perception and emotion, contributing significantly to the product’s hedonic quality (Ma and Chen, 2021). When well executed, microinteractions can also reduce the user’s perceived cognitive load (Yan et al., 2021).

Considering that brand positioning, according to Kotler and Keller (2019), involves designing the company’s offering and image so that it occupies a distinct place in the target audience’s mind, microinteractions can contribute to this construction by shaping the overall brand perception (Zha et al., 2024). User experience is a direct consequence of the system’s presentation, functionality, and interactive behavior, elements within which microinteractions are embedded (van de Sand et al., 2020). Each digital touchpoint, from the first access to an application to the completion of an action, contributes to the perception that the consumer builds about the company and its values.

Despite the growing recognition of the importance of user experience for brand positioning (van de Sand et al., 2020), the specific influence of microinteractions on the perception of a brand’s values remains an underexplored field. The recent formalization of what constitutes microinteractions by Saffer (2013) highlights the need to deepen the analysis of how these design details communicate abstract brand attributes, such as Innovation, trust, or exclusivity. The literature lacks an in-depth analysis of this connection, representing a theoretical and practical gap.

The justification for this study lies in the strategic need to align experience design decisions with branding objectives. In a saturated digital market, where products are increasingly similar in functionality, differentiation occurs in the details that compose and enrich the experience. Understanding the impact of microinteractions on brand perception offers managers and designers a tangible tool to incorporate brand values directly into the product experience, transforming each interaction into an act of brand communication. Given this context, the general objective of this work was to analyze the extent to which the presence of animated microinteractions in a mobile application impacts the perception of a brand’s personality.

2. Material and Methods

The present study adopted a quantitative and exploratory methodological approach, according to the guidelines of Hair Jr. et al. (2014). This research nature sought to deepen the understanding of brand perception in digital interfaces, identifying potential relationships with the presence of animated microinteractions. The central objective was to analyze the impact of animated microinteractions in a mobile application on the perception of a brand’s personality.

The research was structured in five sequential stages. Initially, the hypotheses to be tested were formulated. Next, the target audience was defined and a fictitious brand was conceived for the experiment. The third stage involved the development of data collection instruments, prototypes of an application, and a questionnaire. Subsequently, data collection was carried out, applying the experiment to the selected sample, randomly divided into two groups. The final stage consisted of the statistical analysis and interpretation of the data.

The population of interest was composed of regular practitioners of physical activities, of diverse ages and genders, residing in Rio Grande do Sul, Brazil. This niche was chosen for its relevance to values such as performance, innovation, and overcoming challenges. The fictitious brand developed for the experiment was named Lin, an application for recording and socializing physical activities.

The non-probabilistic sample was selected for convenience. Data collection occurred online over thirty days. Participants were invited by sharing links in WhatsApp groups related to physical activities. Initially, the invitation was directed to three groups, expanding to include groups from two local gyms to increase participation.

For experimental manipulation, two high-fidelity prototypes of a fictitious mobile application of the Lin brand were developed. Both were identical in layout, colors, typography, and functionalities. Prototype A (Control) contained no animations, with instant transitions and absence of dynamic visual feedback. Prototype B (Variant) incorporated animated microinteractions, such as button animations, smooth transitions, and visual feedback, designed to communicate performance, dynamism, and innovation. The creation of the layouts and generation of the code used the Figma Make tool.

Brand values perception was measured by an online questionnaire. The instrument included Aaker’s Brand Personality Scale (1997), with its five dimensions: Sincerity (eleven items), Excitement (eleven items), Competence (nine items), Sophistication (six items), and Ruggedness (five items).

Four perceived usefulness questions, seven for participant profile identification, and two open-ended questions were added to the questionnaire. The form was created in Google Forms, and the randomization of access links to the prototypes and the form was done via the Nimble platform.

The data analysis adopted a significance level of α = 0.05. Descriptive statistics (mean, median, standard deviation, minimum, and maximum) were calculated (Fávero and Belfiore, 2024). The Shapiro-Wilk Normality Test (α = 0.05) was applied (Fávero and Belfiore, 2024) to verify the data distribution.

To compare the Control and Variant groups, Welch’s t-test and Mann-Whitney U-test were used (Fávero & Belfiore, 2024). Both tests sought convergence, considering the sample size. Effect size was assessed by Cohen’s d (Cohen, 1988) and the Point-Biserial Correlation Coefficient (Grissom & Kim, 2012).

Correlations between the dimensions of the Aaker Scale and perceived utility metrics were calculated via Spearman correlation matrix with FDR correction (Fávero and Belfiore, 2024; Cui et al., 2021). The score of each dimension was the arithmetic mean of the items. The analysis was processed in Python 3, with SciPy, NumPy, Pandas and support from the LLM Anthropic Claude Opus 4.6.

Participants were informed about the study’s objectives, and participation was voluntary. Confidentiality and anonymity of respondents were guaranteed, with data used exclusively for academic purposes. A Free and Informed Consent Form (TCLE) was presented before the experiment, ensuring confidentiality and non-disclosure of company or individual names.

3. Results and Discussion

The research results are presented in a sequence that covers the description of the sample, the comparison between the control and variant groups regarding brand personality dimensions and perceived usefulness, a segmented analysis by gender, and finally, the identified correlations between brand personality and perceived usefulness. This organization aims to provide a comprehensive understanding of the findings, connecting them directly to the study’s objectives and existing literature. The detailed data analysis allows for exploring the nuances of the impact of animated microinteractions on brand perception, as proposed by the research problem.

The study sample consisted of 36 participants, of whom 12 were allocated to the control group (without animated microinteractions) and 24 to the variant group (with animated microinteractions). An imbalance in gender distribution between the groups was observed, with 33.3% of female respondents in the control group and 62.5% in the variant group. Furthermore, discrepancies were noted in the mean and median ages, as well as in self-declaration as an amateur athlete, suggesting a heterogeneity that was subsequently explored in the analysis. All participants, without exception, declared that they regularly engage in physical activities, which validates the choice of the target audience for a sports application.

Descriptive statistics revealed that, with the sole exception of the Robustness dimension, all of Aaker’s brand personality dimensions showed a positive delta in arithmetic means for the variant group, indicating greater agreement with the questionnaire statements. It is important to note that, on a Likert scale from 1 to 5, only the Sincerity dimension fell below the neutrality point (3 points) in both the control and variant groups. Regarding perceived usefulness, all evaluated dimensions (usefulness for routine, added value, ease, and recommendation) were below neutrality in the control group, evidencing an initial perception of low usefulness without microinteractions.

Brand personality perception: trends without statistical significance

In the evaluation of brand personality, none of the five dimensions of Aaker’s Scale (Sincerity, Excitement, Competence, Sophistication, and Ruggedness) achieved statistical significance (p < 0.05) when comparing the control and variant groups. However, the analysis of effect sizes revealed important trends that deserve discussion. Four of the five dimensions (Sincerity, Excitement, Competence, and Sophistication) showed higher means in the variant group, suggesting that animated microinteractions positively influenced the perception of these brand characteristics. The Competence dimension exhibited the largest effect size (d = +0.48), characterizing a small to medium effect, which indicates a tendency for the brand to be perceived as more competent with the presence of animations.

The Robustness dimension was the only exception, with the control group’s average exceeding that of the variant group (d = −0.42). This result suggests that animated microinteractions, by conferring a more polished and competent personality, may simultaneously reduce the perception of brand robustness and toughness. This finding is in line with the perspective of van de Sand et al. (2020), who argue that brand experience is a direct consequence of the system’s presentation, functionality, and interactive behavior. Microinteractions, in this context, act as indicators of technical acuity and refinement, attributes that align with competence but may distance themselves from a more rustic or “tough” image.

The implications of this pattern are relevant for brands seeking a specific positioning. If a brand wishes to be perceived as robust or rustic, the use of smooth animations can be counterproductive, communicating a visual refinement that does not align with the desired strength. The absence of statistical significance for brand personality dimensions should be interpreted with caution, mainly due to the limited sample power. The statistical power of the current sample was estimated between 25% and 30% for the observed effects, while academic convention suggests a minimum of 80% (Cohen, 1965, 1988). To reach this level, between 68 and 100 participants per group would be necessary (Di Stefano, 2003; Perugini et al., 2024). Thus, non-significance does not indicate an absence of effect, but rather an indefiniteness that demands a larger and more qualified sample for future investigations. The convergence of parametric (Welch) and non-parametric (Mann-Whitney) tests on the nine items analyzed, however, reinforces confidence in the exploratory results.

Perceived usefulness: strong and significant impact

In contrast to brand personality dimensions, the four questions related to the perceived utility of the application (utility for routine, added value, ease of use, and recommendation intention) showed highly significant differences (p < 0.05) between the control and variant groups. Effect sizes were large, ranging between d = 0.96 and d = 1.20, all in favor of the prototype with animated microinteractions. The confidence intervals for Cohen’s d, in all cases, excluded zero, which reinforces the robustness of these findings and confirms the hypothesis that animated microinteractions improve the perceived utility of the application.

This result directly corroborates previous studies, such as Boyd and Bond (2021), who, in an experiment with a similar design (A/B test between interfaces with and without microinteractions), observed that interfaces with microinteractions were perceived as more interesting, pleasant, and easier to learn. Although Boyd and Bond (2021) noted a subtle effect on overall usability, they identified statistically significant effects on specific items of interactivity and pleasure. This pattern is consistent with the findings of the present study, where the impact of microinteractions was more expressive in the dimensions of functional experience (utility, value, ease, recommendation) than in the more abstract dimensions of brand personality.

Participants who interacted with the animated prototype perceived the application as significantly more useful (an increase of +1.29 points in the average), easier to use (an increase of +1.04 points), and with greater added value (an increase of +1.29 points). This translation of hedonic quality, generated by animations, into perceived utility is consistent with Hassenzahl’s (2008) view, which argues that a positive experience is achieved when human needs for competence and stimulation are met by product interaction. Ma and Chen (2021) also demonstrated that microinteractions directly affect user emotion, contributing to hedonic quality, and the data from this study expand this perspective by showing that this hedonic quality translates into more positive functional evaluations.

The finding that microinteractions improve recommendation intention (d = 0.96) aligns with Zha et al.’s (2024) perspective on how sensory experience impacts brand loyalty. The higher recommendation intention generated by the experience with the animated app suggests an indirect path through which microinteractions, even if they do not directly alter perceived brand personality, can influence brand positioning. This occurs through word-of-mouth and the overall improvement of perceived usefulness, reinforcing the idea that design details are expressive vehicles of brand communication.

Gender as a differentiating factor

Given the discrepancy in gender composition between the control and variant groups, an in-depth analysis was conducted to investigate the impact of this variable on the study’s dimensions. Gender segmentation revealed that women (n=19) systematically rated higher than men (n=17) on all nine analyzed variables. Four of these variables reached statistical significance for women: usefulness (d = 0.89), competence (d = 0.76), recommendation (d = 0.75), and added value (d = 0.71), indicating a generally more positive perception from the female audience.

Cross-segmentation by group and gender revealed that the effect of animations varies substantially by gender, with three notable patterns. Firstly, animations impacted Robustness very differently: for women, the perception of Robustness dropped drastically with animations (Δ = −0.82, from 3.95 to 3.13), while for men, the drop was minimal (Δ = −0.15). This suggests that microinteractions can “soften” the brand more sharply for the female audience, making items in the Robustness dimension particularly sensitive to this attribute substitution.

Secondly, animations impacted usability in an opposite way between genders. For men, the effect of animations on usability was the largest individual effect in the entire analysis (Δ = +1.49, from 2.63 to 4.11, with point-biserial r = +0.68 and p = 0.003). Men in the control group rated the app as difficult to use (M = 2.63, below the neutral point of 3.0), and animations almost completely solved this problem. In contrast, women already perceived the app as reasonably easy to use even without animations (M = 3.25), and the effect of animations was modest (Δ = +0.48). This finding is consistent with Yan et al. (2021), who demonstrated that microinteractions can reduce perceived cognitive load, suggesting that for men in the control group, the interface without animations may have generated higher cognitive load, and the animations functioned as visual guidance that facilitated understanding of navigation.

Finally, the Competence dimension also showed a differentiated impact by gender. For men, the perception of competence jumped from 2.99 in the control group to 3.36 in the variant group, indicating that animations are more impactful on the male perception of brand competence. For women, competence was already high in the control group (M = 3.72) and remained practically identical in the variant group (M = 3.73), suggesting that microinteractions had a marginally smaller effect on female competence perception. These gender findings are relevant due to the imbalance in the composition of the experimental groups, and although the small segment sizes (n=4 in the control/female group) make these inferences exploratory, the observed patterns are expressive and justify the inclusion of gender as a covariate in future research.

Correlations between brand personality and perceived usefulness

The analysis of Spearman’s correlation matrix, with FDR correction, revealed that Sincerity was the brand personality dimension most consistently associated with perceived usefulness. This was the only dimension that showed a significant correlation (after FDR correction) with all four usability metrics: recommendation (p = +0.60), usefulness (p = +0.54), ease (p = +0.46), and added value (p = +0.42). This result aligns with the literature, which describes sincerity as the dimension most conducive to lasting relationships between consumer and brand (Aaker, Fournier, and Brasel, 2004), and with studies that point to its direct impact on consumer trust (Perepelkin and Di Zhang, 2014). In the context of a sports app, the perception of an honest, authentic, and friendly brand can function as a signal of reliability, reducing the perceived risk when recommending the app to others.

In contrast, the Robustness dimension showed negative correlations with all usability metrics (p between -0.16 and -0.17), although these correlations were not individually significant. This pattern suggests that, for the app and brand in question, robustness attributes such as rustic, tough, or masculine are not perceived as positive by users. The recommendation dimension, in turn, stood out for presenting a significant and positive correlation with all other dimensions, except Robustness. The strongest correlation was with added value (p = +0.81), followed by utility (p = +0.75). This reinforces that the intention to recommend is a synthesis of the overall user experience, integrating both the perception of functional utility and the perception of brand personality, as argued by van de Sand et al. (2020) regarding the inseparability of user and brand experience.

The correlation matrix data, while not allowing for direct causality inference, suggest an indirect mechanism by which microinteractions can influence brand positioning. Animations enhance perceived utility, a direct and significant effect, which in turn strongly correlates with brand personality dimensions that favor desired positioning, such as sincerity, competence, and excitement. This indirect path, from microinteractions to perceived utility and subsequently to brand personality, is consistent with Kotler and Keller’s (2019) proposition that brand positioning is built by the totality of impressions a consumer accumulates through all brand touchpoints. In summary, the results indicate that animated microinteractions primarily impact the user’s functional experience, and indirectly influence the perception of brand personality, especially in dimensions like competence and sincerity, while potentially softening the perception of robustness.

4. Conclusion

This study sought to analyze the influence of animated microinteractions in a mobile application on brand personality perception. It was found that the presence of these microinteractions significantly impacted the perceived utility of the application, encompassing its routine usefulness, added value, ease of use, and recommendation intention. Although the brand personality dimensions, according to Aaker’s Scale, did not reach statistical significance, a tendency towards an increase in Competence perception and a reduction in Ruggedness was observed. Correlational analysis indicated sincerity as the main predictor of recommendation intention. It was concluded that animated microinteractions primarily act on the user’s functional experience and indirectly influence brand personality perception, demonstrating that design details function as expressive vehicles for brand communication, capable of shaping the desired positioning.

However, the findings should be interpreted considering the study’s limitations, such as the small sample of 36 participants, which resulted in low statistical power for brand personality dimensions, and the gender distribution imbalance between groups. Remote and unmoderated data collection also prevented the control of variables such as the device used or participants’ attention level. Furthermore, the research was limited to a binary comparison of prototypes, without exploring variations in animation style or the impact of prolonged use. For future investigations, it is recommended to expand and balance the sample, including gender as a covariate, and apply the experiment to real products with extended exposure. It is also suggested to test multiple animation variants and analyze the impact on individual items of Aaker’s scale to obtain more granular guidance on the sensitivity of personality traits to different types of microinteraction.

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