Beyond clicks and likes: a typology of affect in digital marketing

The growing use of digital marketing actions by marketers has fundamentally reshaped how brands connect with consumers. Affective components such as emotions, moods, feelings and humors have gained a central role in influencing consumer behavior for capturing and driving engagement in the fast-paced digital world. In this article, we will use the term “affect” as an umbrella concept to encompass all affective components discussed. This terminology aims to provide clarity and consistency in the examination of the emotional and affective dimensions relevant to our analysis.

Despite the growing interest in affect within digital marketing (e.g. Athwal et al., 2019; Ferrer-Rosell et al., 2020; Joo and Kim, 2021; Rodrigues et al., 2023; Wahid et al., 2023), the diversity of specific affective components and the variety of methods of research makes it difficult for scholars and practitioners to synthesize what is underlying from the research findings.

The scientific literature consistently acknowledges the significant influence of affect on online consumer behavior, shaping everything from everyday interactions on social media to more complex purchasing decisions (Gu et al., 2023; Jang et al., 2021; Lee et al., 2018; Wang et al., 2023).

A review of the extant literature on digital marketing reveals a significant gap in theoretical contribution, particularly regarding reviews that deeply explore affect in its nuances of emotions. The careful evaluation of the existing literature, as proposed by Xiao and Watson (2019) is intended to uncover areas still unsaturated by research, providing a clear vision for future studies to bridge these gaps. This effort aligns with the process described by Munn et al. (2018), emphasizing the pursuit of reliable and highly relevant results, thereby facilitating meaningful progress towards understanding affect in digital marketing.

For instance, where should the effort of scholars be placed to extend the body of knowledge in the topic? What are the main pillars managers should focus on when developing a digital marketing strategy? To address these questions, we conducted a review of the literature on affect in digital marketing.

We outlined a six-class typology to guide researchers and practitioners to better understand how affect and emotions operate across various digital domains of research. The classes outlined as (1) humanized brand building, (2) personalized consumer experience, (3) content marketing, (4) consumer behavior in digital environments, (5) affective responses in advertising and (6) influencer marketing offer a better understanding on how affect influence digital marketing, providing a basis for future research and the development of practical actions for researchers and managers.

This study contributes to theory by introducing a six-class typology that organizes and clarifies the role of affect in digital marketing, addressing gaps in the literature. Practically, it offers actionable insights for marketers, guiding strategies in areas like brand building, personalized experiences, and influencer marketing. By focusing on these elements, it sheds light on how affect is interrelated and influential across various contexts. This connection will be further explored in the results, where we discuss the interplay between some affective components.

Given the increasing complexity of digital marketing and the growing focus on affect, a structured approach was essential to synthesize fragmented insights across the literature. In this article, we followed the SPAR-4-SLR protocol (Scientific Procedures and Rationales for Systematic Literature Reviews) to conduct the research in three sequential stages: assembling, arranging, and assessment (Paul et al., 2021). This approach proved to be suitable to satisfy the requirements of rigor, transparency, and robustness for a literature review. The protocol has been used in marketing research areas such as “digital platforms and business-to-business” (Shree et al., 2021), “omnichannel consumer buying journey” (Furquim et al., 2023), and “purchasing behavior in the green agenda” (Sharma et al., 2023). Furthermore, content analysis was employed as a method to extract and examine the collected data in depth.

The application of this method has been used and recommended in studies addressing similar themes such as “emotions and consumer experience” (Page et al., 2010; Richins, 1997), “emotions and consumer behavior” (Laros and Steenkamp, 2005), and “emotions and social media strategies in B2B and B2C” (Zhang and Du, 2020). In this sense, we acknowledge the procedure is suitable for investigating how affect influence digital marketing. For this work, we adopted the steps of analysis outlined by Bardin (2011). The research was conducted without time limitations until October 20, 2024, all phases were adapted to the SPAR-4-SLR protocol and operationalized during the assembling, arranging, and assessment stages, as detailed in Table 1 and Subsections 2.1 to 2.3.

The initial stage of the research, referred to as assembling, encompassed the identification of prior empirical studies on emotions in digital marketing, a field of substantial academic and managerial interest. This article focuses on scientific works published in journals listed in the Scopus and Web of Science (WoS) databases, due to their complementarity, ensuring comprehensive coverage of the research domain (Booth et al., 2016).

In this context, Figure 1 illustrates the methodology used for the selection of the text corpus of this study, focusing on journal articles with an Impact Factor equal to or greater than 3.0. The selection of these documents was based on the credibility and relevance guaranteed by the impact indices listed for the respective journals.

Concurrently, the operationalization of “Phase 1” by Bardin (2011) was developed through an initial scanning of the documents selected at this stage of the SPAR-4 SLR. It involved defining the coding scheme, highlighting conceptual elements about affective components and digital marketing. Similarly, data were extracted highlighting the main problems, objectives, results, future research agendas, methodologies, keywords, and journals. The extraction of these data was intended to elucidate how affective components have been understood in empirical digital marketing research.

The second phase, denominated arranging, involves structuring and selecting articles through the definition of eligibility criteria. The inclusion criteria were limited solely to articles published in academic journals, thus excluding conference publications, consultancy reports, textbooks, master’s and doctoral theses, government documents, and non-peer-reviewed materials. Other inclusion criteria were the presence of a Digital Object Identifier (DOI) and publication in English in journals with an Impact Factor equal to or greater than 3.0.

Furthermore, the full text of each article was coded considering four additional inclusion criteria: (1) articles with empirical evaluation; (2) investigation of the main objectives of the article were associated with the context of affect in digital marketing; (3) correlation between the keywords used in the search; and (4) studies conducted from the perspectives of both the consumer and the brand. A list of the 68 articles is available as an  Appendix 1.

The third and final stage of the research, termed assessment, involved analyzing the articles selected in the previous phase. This study adopted a hybrid approach, combining a literature review with content analysis to address the proposed research agenda. For this purpose, the following software tools were used: Bibliometrix (version 4.1.4), Iramuteq (version 0.7 alpha 2), ATLAS.ti 24 and Microsoft Excel. The review was conducted considering all the articles in the text corpus (Figure 1).

The 68 articles were published in 50 journals with 217 authors and co-authors from the Web of Science (WoS) and Scopus databases. There is an average of 27.71 citations per published document, along with an annual growth rate of 13.39%. Additionally, there is 39.71% international co-authorship with an average of 3.25 authors per published document.

When observing the temporal evolution of the academic production, Figure 2 indicates a recent growth, particularly from 2020 onward. This increase can be attributed to the growing digitization of consumption and the ever-increasing significance of affect in online interactions, amplified by global events such as the COVID-19 pandemic, which demanded mass migration to digital environments (Wahid et al., 2023). This emerging scenario calls for a deeper understanding of how affect influences consumer behavior in the digital space, presenting a rich background for innovative research that explores the psychological mechanisms behind online purchasing decisions.

The independent presence of a pioneering study by Rodgers and Harris (2003) suggests an early insight into the role of gender in e-commerce interactions, highlighting affective differences and initial responses to digital marketing between men and women. This work anticipated the recognition that affect strongly influence digital marketing, a perception that would only gain substance and depth in subsequent research, as reflected in the exponential growth of publications in recent years (Figure 2).

The content analysis (Atlas.ti 24) reveals that affect, emotions and moods are interconnected in digital marketing research (Alnoor et al., 2024; Christodoulides et al., 2013; Hwang and Kim, 2007; Meyer et al., 2023). However, conceptual overlap between these dimensions, particularly between mood and emotions, emphasizes the need for clearer distinctions (Ekman, 1999; Plutchik, 1962). Bagozzi et al. (1999), pointed out that the inconsistent use of terms like affect, emotion, and mood in the literature creates conceptual ambiguity and weakens the theoretical consistency across studies.

In digital marketing research, affect is often studied as a holistic component, encompassing feelings, emotions, and moods that influence consumer behavior and decision-making (Christodoulides et al., 2013; Hwang and Kim, 2007; Rodrigues et al., 2023). Affect plays a key role in the consumer’s personal evaluation, which occurs before making a purchase decision, shaping both behavior and marketing strategies (Alnoor et al., 2024). It reflects internal motivations and attitudes, whether positive or negative, and influences how consumers perceive value in marketing communication efforts.

Affect builds emotional ties and a sense of proximity between consumers and brands, often reinforced through para-social interactions (PSI) and relationships (PSR) (Jamil et al., 2024; Meyer et al., 2023). First introduced by Horton and Richard Wohl (1956), the concept of PSI describes the illusion of a face-to-face relationship between an individual and a media figure, fostering a sense of connection and intimacy. In contemporary digital marketing, these affective bonds have become critical in domains such as influencer and content marketing, where consumer-generated content like eWOM significantly influences brand perception (Aghakhani et al., 2018; Ciocodeică et al., 2022).

Emotions have emerged as a primary focus in digital marketing studies, due to their immediate impact on consumer behavior and decision-making processes (Hwang and Kim, 2007; Yun et al., 2024). Operationalized as reactions or responses to external stimuli, emotions are often associated with key behavioral aspects such as attitude, intention, and connection with brands (Jang et al., 2021; Martinez and McAndrews, 2021; Pathak and Pathak-Shelat, 2017). Emotions such as love, anxiety, joy, and satisfaction can influence purchase decisions, fostering emotional engagement with brand messages and social media content (Cachón-Rodrigues et al., 2024; Castro-González et al., 2024; Teng et al., 2022; Zhang et al., 2023). They also play a significant role in post-purchase behavior, reinforcing consumer loyalty through emotional regulation and emotional contagion approaches (Wahid et al., 2023; Wang et al., 2023). However, conceptual overlaps between emotions and moods highlight the need for clearer theoretical distinctions in future research (Ekman, 1999; Plutchik, 1962).

Moods, unlike emotions, are defined by their longer duration and less specific triggers (Ekman, 1999), making them more complex to operationalize in digital marketing research. Moods are categorized into several types, such as aggressive, benign, and CEO-driven moods, each influencing brand perception, consumer behavior, and brand interactions in unique ways (Ning et al., 2022; Teng et al., 2022). Unlike emotions, which are typically immediate responses, moods are understood as evolving states that reflect variability and change over time, offering nuanced insights into consumer-brand relationships (Ciocodeică et al., 2022; Liu et al., 2024; Ning et al., 2022). These distinctions are essential to understand the interplay between personal, relational, and contextual attributes that impact consumer perception and brand engagement strategies (Garnier et al., 2024).

The interconnected relationship between affect, emotions, and moods plays a crucial role in shaping consumer behavior in the digital marketing context. Affect serves as the overarching category, grouping both short-lived emotional responses and longer-lasting moods (Bagozzi et al., 1999; Ekman, 1999; Plutchik, 1962). Among these concepts, emotions have received the most attention in the analyzed studies. This emphasis on emotions suggests a focus on consumer behavioral elements that offer more immediate results for digital marketing regular actions (Ciocodeică et al., 2022; Perez Benegas and Zanfardini, 2023).

These elements, though conceptually distinct, are often intertwined in consumer interactions, influencing decision-making processes and engagement with brands (Perez Benegas and Zanfardini, 2023). The necessity for a typology lies in the importance of distinguishing the specific contexts in which these concepts are explored in the literature. A typological framework allows researchers and practitioners to map how these affective components are applied across different areas thus offering clearer insights into their roles.

Typology analysis in a text enables an interpretation of the keywords more closely linked to the topic, serving as the backbone of content analysis. Regarding the classification results, we applied the Descending Hierarchical Classification (DHC) method to identify six distinct classes in the sample using Iramuteq version 0.7 alpha 2, and 80.98% of the segments were retained, which were statistically significant (Camargo and Justo, 2013).

The DHC method was chosen for its alignment with the research objectives, as it segments text into mutually exclusive classes based on co-occurrence patterns and lemmatization (Camargo and Justo, 2013). Unlike Latent Dirichlet Allocation (LDA), which distributes words probabilistically across multiple topics in unstructured corpus, DHC is better suited because we had a structured dataset. The preference for DHC also stems from the research team’s expertise and its strong support in the literature for typology analysis (Fabrizio et al., 2022; Furquim et al., 2023).

Only words that exhibited a chi-square value greater than 3.80 (χ² > 3.80) or a probability value less than 0.1% (p-value <0.001) were considered significant and included in the analysis (Reinert, 1990). Words not meeting these parameters were discarded. Words meeting these significance criteria make up the six classification classes in question, as detailed in Table 2.

The first class highlights the growing importance of emotional engagement in creating authentic connections with consumers. Incorporating emotional intelligence into communication strategies enhance brand image, builds customer loyalty, and promotes meaningful interactions (Hutchins and Rodriguez, 2018; Martinez and McAndrews, 2021; Rodrigues et al., 2023). This movement towards greater use of emotional content suggests the need for digital marketing to treat consumers as individuals with unique needs and emotions, driving both satisfaction and loyalty (Rambocas and Pacheco, 2018).

Luxury and retail brands exemplify this trend by using social media to address cognitive and affective needs, such as providing aesthetic enjoyment and entertainment alongside useful information (Athwal et al., 2019; Joo and Kim, 2021). Strategies like fostering “store love” in retail or using emotional engagement in hotel services significantly enhance loyalty (Ahmed, 2022; Ferrer-Rosell et al., 2020). Humanized communication, which focuses on shared values and emotional resonance, is vital for sustainable brand growth beyond transactional exchanges.

Apple’s “Shot on iPhone” campaign illustrates humanized brand building through emotional engagement. By showcasing user-generated content that highlights personal moments, Apple celebrated creativity and reinforced its commitment to individuality and diversity. This emotionally resonant approach strengthened loyalty by aligning the brand’s values with its audience’s desire for self-expression, fostering a lasting bond beyond transactional marketing.

The second class emphasizes the transformative impact of personalization on customer experiences in the online commerce environment, where brands increasingly leverage stimuli like livestreaming and interactive AI tools to enhance affective engagement and drive consumer satisfaction (Gu et al., 2023; Zhu et al., 2023). Livestreaming commerce blends entertainment and social interaction, fostering emotional connections between consumers and products, this format allows broadcasters to shape consumers’ moods and influence purchase intentions through real-time interactions (Zhu et al., 2023).

Similarly, AI-driven chatbots with sentiment analysis provide personalized responses, enriching customer service by recognizing emotional cues in communication, thus increasing satisfaction and loyalty (Dongbo et al., 2023). Studies show that user’s regulatory focus, whether promotion-focused (e.g. joy or arousal) or prevention-focused (e.g. relief), significantly affects real-time decision-making, engagement and purchase outcomes (Robertson et al., 2021; Zhu et al., 2023).

Current research lacks clarity on how different regulatory focuses influence user responses to positive versus negative affect in digital environments. Additionally, the nuances of how these responses translate into engagement metrics, such as click-through rates, time spent on content, or purchases remain underexplored. Addressing these gaps is crucial to understanding how affect and regulatory focus shape user interactions, offering actionable insights for tailoring digital marketing strategies to diverse user profiles.

Amazon’s personalization tools, like its recommendation engine, demonstrate the transformative power of tailored customer experiences. Similarly, Shein uses UGC to enhance personalization and engagement. By encouraging customers to share reviews, photos, and styling tips, Shein creates an interactive shopping environment. These strategies provide relatable, real-time content that drives purchase decisions, underscoring personalization’s importance in digital marketing.

The third class focuses on the domain of content marketing, where platforms like TikTok, Instagram, Twitter, Youtube and Facebook play central roles in shaping brand visibility and audience engagement. Emotional engagement, driven by user-generated content (eWOM) and vlogs, is a key factor in building meaningful consumer connections (Ciocodeică et al., 2022; Meyer et al., 2023). The agility of TikTok, the real-time virality of Twitter, and the long-term relational power of Facebook and Instagram intertwine to form the foundation of modern digital marketing strategies (Aghakhani et al., 2018; Chin and Huang, 2023; Ferrer-Rosell et al., 2020; Jang et al., 2021).

This shift toward emotionally intelligent content highlights the need for brands to balance information with emotional appeal, ensuring engagement that captures attention while building loyalty and trust (Gu et al., 2023; Wahid et al., 2023). Successful campaigns rely on dynamic, authentic and relatable content that resonates across platforms.

Jaguar’s 2024 rebranding illustrates the power of disruptive content marketing. By unveiling a minimalist logo and promotional materials without traditional car imagery, Jaguar repositioned itself as part of the art world: an approach that is abstract, emotional, and human, targeting a younger, style-conscious demographic. This bold move sparked widespread discussion, garnering millions of views and conversations on social media. While some praised the innovation for aligning Jaguar with modern design trends, others criticized it for departing from its automotive heritage. This campaign demonstrates how emotionally driven content marketing can drive engagement and visibility, leveraging social media’s virality to shape brand perception and connect with diverse audiences.

The fourth class explores consumer behavior in digital environments, where analyzing sentiment through comments, chats, and reviews provides valuable insights for understanding brand perception. These interactions allow companies to identify emotional drivers, emerging trends, and unmet needs, enabling faster responses to shifting expectations (Hutchins and Rodriguez, 2018). This class highlights how digital environments create opportunities for communication that enhances customer experience, aligning brand actions with evolving consumer emotions and needs (Berger et al., 2023; Dongbo et al., 2023; Pathak and Pathak-Shelat, 2017; Wang et al., 2017).

By monitoring sentiment and public opinion in real time, brands can deepen engagement and strengthen trust, turning digital interactions into connection opportunities (Wang et al., 2017). This approach goes beyond transaction-based relationships, focusing on building lasting emotional bonds and authentic engagement (Pathak and Pathak-Shelat, 2017). In digital environments, understanding consumer sentiment becomes crucial for maintaining relevance and cultivating loyalty in dynamic markets.

Netflix exemplifies sentiment analysis as a central tool for understanding consumer behavior. By monitoring reviews, social media discussions, and viewing patterns, Netflix identifies audience preferences and emotional drivers, enabling personalized recommendations.

The fifth class focus on affective responses in advertising, where emotional intensity plays a crucial role. Ads with high emotional content, whether joy, anxiety, or hope, elicit greater consumer engagement (Lee and de Villiers, 2024). Elements like emojis also influence reactions; present-oriented consumers prefer low-intensity emojis, while future-oriented ones favor high-intensity stimuli (Huang et al., 2022; Lin et al., 2024). Humor in advertising, especially on social media, enhances engagement, with low-aggressive humor fostering stronger interactions than high-aggressive humor (Garnier et al., 2024). Memes contribute to brand image through humor and interaction, driving user engagement and enhancing brand recall (Teng et al., 2022).

Ad frequency, combined with emotional or rational appeals, also influences consumer attitudes, with repeated exposure amplifying emotional impact over time (Hussain et al., 2018). The concept of stickiness is tied to ad frequency, as repeated exposure to emotionally engaging advertisements enhances recall and strengthens brand attachment, encouraging repeated interactions (Martinez and McAndrews, 2021).

Dove’s “Reverse Selfie” campaign illustrates the power of emotionally intense advertising by addressing anxiety and self-esteem related to digital beauty standards. Through a narrative highlighting the effects of beauty filters on young girls, the campaign evoked empathy and concern, fostering meaningful connections. This example demonstrates how emotional resonance in advertising can drive engagement and shape brand reputation.

The sixth class addresses influencer marketing, where consumer loyalty is shaped by the power of influencers (Jun and Yi, 2020). Followers form attachments with influencers, making it easier to capture attention and enhance digital word-of-mouth. The creation of emotional bonds between consumers, brands, and influencers is facilitated through para-social interactions (PSI) (Breves et al., 2024; Ferreira et al., 2024). These interactions positively influence strategies like influencer marketing, content marketing, and brand communication on social media (Rodrigues et al., 2023). Maintaining an engaged follower base depends on constructing a coherent, authentic story that strengthens loyalty and amplifies the message’s impact. Thus, influencer performance redefines marketing as a tool for establishing trust and enduring bonds between brands and consumers (Jun and Yi, 2020).

Many brands now use virtual influencers to engage audiences, reflecting influencer marketing’s growing impact (Jun and Yi, 2020; Ki et al., 2020; Lim and Lee, 2023; Zhang et al., 2023). Virtual influencers effectively stablish authentic affective connections, signaling a new era in influencer marketing (Zhang et al., 2023). This trend highlights the importance of authenticity and affective closeness as valuable currencies in reshaping strategies to leverage storytelling and digital presence. There dynamics humanizes brands, enhancing their influence through the previously mentioned attributes (Lim and Lee, 2023; Zhang et al., 2023).

Dior’s “67 Shades of Dior” campaign illustrates the power of influencer marketing in promoting inclusivity and engagement. Collaborating with 67 influencers, each representing a unique shade of the Forever Foundation line, Dior released daily content for 67 days across social media platforms (Influencity, 2024). This campaign emphasized diversity and fostered authentic connections, driving significant engagement while reinforcing Dior’s commitment to inclusivity. The campaign’s structured storytelling and emotional resonance exemplify how influencer marketing enhances brand influence and recognition.

By synthesizing various theoretical and practical approaches, this study elucidates the relationship between affective components and consumer behavior, offering significant insights for future research. A key gap lies in the lack of consensus on defining, measuring, and theorizing affective constructs in digital marketing. Current research often acknowledges the importance of affect, although, treat emotions and moods interchangeably or relies on surface-level engagement metrics (e.g. likes or shares) without exploring the deeper psychological mechanisms shaping consumer behavior.

Future research should focus on standardizing definitions and frameworks for affect dimensions, enabling a more comprehensive understanding of their role in digital marketing. This includes developing methodologies that capture both surface-level engagement and underlying psychological responses. Researchers are encouraged to explore mixed methods approaches, combining quantitative techniques (e.g. robust statistical analyses) with qualitative methods like interviews, focus groups, and sentiment analysis, to address the complexity of affective phenomena (Chin and Huang, 2023; Ciocodeică et al., 2022; Rodrigues et al., 2023).

For practitioners, the findings highlight the centrality of affects in shaping successful digital marketing strategies. Future actions should encompass authentic, emotionally engaging communication, such as personalized storytelling campaigns or interactive content that reflect consumer values. It is highly recommended for brands managers, to prioritize creating content that not only captures attention but also sustains emotional connections over time.

Overall, affects, emotions, and moods remain underexplored within the theoretical framework of digital marketing research. Future studies should highlight the understanding of how affective experiences drive consumer behavior, engagement, and brand connection, particularly in contexts requiring immediate emotional responses for purchase intent.

The application of the stimulus-organism-response (SOR) framework, without integrating complementary theories, has proved to be insufficient to explain how affectively balanced stimuli are perceived and lead to conditioned responses (Estrader et al., 2023). Future research could incorporate theories such as cognitive appraisal theory, affect-as-information theory, emotional contagion theory and the theory of planned behavior, which offer valuable insights into the interplay between affective stimuli and consumer decision-making.

Affective experiences, online experience, social networks, parasocial relationships (PSR), and the sentiment analysis method are adopted in the theoretical perspectives of affect in the context of digital marketing (Ning et al., 2022; Meyer et al., 2023). Future research should investigate how these approaches can enhance brand consolidation, consumer engagement, and buying behavior, particularly in increasingly digitalized consumption contexts. This is critical for creating marketing strategies that resonate with target audiences and boost sales (Christodoulides et al., 2013; Mukherjee, 2020).

The results suggest convergence in the definitions of affect, emotions, and mood within digital marketing studies, whereas psychological literature considers these as distinct processes (Barsade and Gibson, 2007; Ekman, 1999). Upcoming research should aim to clarify these distinctions and establish a unified framework for conceptualizing affective constructs in digital marketing.

Humanized brand building requires deeper understanding of how brands acquire and sustain human attributes in digital environments (Rambocas and Pacheco, 2018). Brands should invest in authentic storytelling and personalized interactions using consumer behavior data (Hutchins and Rodriguez, 2018; Martinez and McAndrews, 2021; Rodrigues et al., 2023; Teng et al., 2022). Further studies should address the subjectivity in defining “humanized” to address cultural and contextual variations.

In personalized consumer experiences, researchers should explore how innovations, AI and big data ethically and efficiently enhance personalization, offering insights into the digital context (Robertson et al., 2021; Standing et al., 2016; Zhu et al., 2023). Accurately measuring personalization’s effects on attitudes remains a challenge, often relying on indirect or self-reported data. AI-driven sentiment analysis may possibly improve accuracy while addressing risks like confirmation bias.

Content marketing studies should focus on how content diversity impact consumer journeys, from awareness to purchase (Aghakhani et al., 2018; Chin and Huang, 2023; Ferrer-Rosell et al., 2020; Jang et al., 2021). Investigating content that fosters loyalty and community building could help brands cultivate long-term relationships. Advanced analytics can guide content creation aligned with consumer interests, while immersive formats like augmented reality could strengthen emotional connections as seen in IKEA’s AR-based shopping app.

Advancing the understanding of how digital engagement strategies build and sustain brands-consumer relationship is crucial (Berger et al., 2023; Dongbo et al., 2023; Pathak and Pathak-Shelat, 2017; Wang et al., 2017). Real-time data analytics tools can help brands adapt strategies effectively, though challenges such as data privacy or over-reliance on short-term metrics persist. Developing digital loyalty programs that reward consumer engagement with exclusive experiences, rather than economic benefits alone, could strengthen emotional connections.

Quantitative metrics, such as likes and shares often fail to capture the depth or quality of consumer engagement (Chin and Huang, 2023; Ciocodeică et al., 2022; Rodrigues et al., 2023). Future research may address the challenges in distinguishing authentic engagement from artificially generated interactions, such as bot-driven activity, to improve engagement analysis.

Influencer marketing demands further research on how influencers’ authenticity and transparency impact consumer trust and loyalty (Steinert and Dennis, 2022). Longitudinal studies could be valuable assessing changes in trust over time. However, measuring the strategic impact on consumers’ attitudes remains challenging due to the complexity of social influence dynamics (Jun and Yi, 2020; Ki et al., 2020; Lim and Lee, 2023; Zhang et al., 2023). Researchers can investigate the volatility of influencers’ reputations, when personal issues or controversies can negatively impact the associated brand’s perception and its impact in the short, medium, and long term. This could suggest crisis management strategies for brands associated with high-risk influencers.

These findings emphasize the importance of affective components in digital marketing and the need for more research to advance this critical field. Managerial implications include strategies like personalized messaging, community-building activities, and exclusive brand experiences to strengthen brand-consumer relationships. Future research should develop a unified framework defining affects, their dimensions (emotions, moods, and feelings), and intensities for application in digital contexts.

This work identifies significant areas for future investigation, with limitations in each class highlighting the ever-evolving nature of digital marketing. Constant adaptation of strategies and research methods are important to address the complexities of this dynamic field.

This study enriches the literature by emphasizing the critical role of affective components in shaping brand-consumer relationships in the digital environment. It also identifies new opportunities for research and practical actions.

While the methodology ensures rigor and structure, we acknowledge potential limitations and the actions to mitigate them. To reduce biases, we followed systematic review and content analysis protocols, ensuring consistency and transparency in data selection and interpretation. To mitigate the subjectivity inherent in content analysis, we utilized a combination of software tools that enhanced precision and minimized human error. We prioritized high-impact studies with strong theoretical foundations, aligning them with our research objectives but potentially excluding relevant but non-indexed studies or emerging research not yet available in the databases used. Moreover, we integrated specialized literature from psychology to validate our findings on affect. These methodological precautions reinforce the study’s reliability and provide a solid foundation for future research on affect in digital marketing.

To advance humanized brand building, future research should explore the efficacy of humanization strategies across diverse cultures and markets, acknowledging global diversity in consumer responses. Research on ethically leveraging artificial intelligence to simulate human attributes in critical for balancing technological efficiency and authenticity. Additionally, understanding how affect shapes perceptions of brand authenticity is fundamental, as it significantly influences consumer trust and loyalty.

In personalization, future studies should examine how to balance personalized experiences with consumer privacy, ensuring personal data protection while maintaining personalization’s effectiveness. For content marketing, further investigation is recommended into how content formats affect brand memorability, as presentation significantly impact consumers recall and perception. Exploring virtual and augmented reality’s potential in marketing content could unlock immersive experiences that captivate consumers and influence their affective thinking.

Equally important is the exploration of the consequences of a negative brand image and the strategies for recovery. Transparent and swift communication combined with accountability and alignment with consumer values is essential for crisis management. Rebuilding relationships through personalized interactions and emphasizing positive emotional engagement can help brands reconnect with their audience. Integrating these recovery strategies into content marketing efforts not only mitigates reputational damage but also enhances brand resilience against future challenges.

A holistic approach to measure consumer behavior in digital environments is essential, beyond likes, shares, and comments to methods that capture the depth of online interactions. Future research should explore how multi-channel interactions influence engagement, emphasizing the importance of consistency and complementarity across channels. Additionally, studying the impact of gamification on engagement strategies could provide insights into how playful elements encourage active consumer participation.

To better understand the relationship between affective responses and advertising effectiveness, research should assess how varying levels of emotional intensity shape brand perception across industries and product types. Investigating the use of negative emotions in advertising could reveal how consumers can increase interest without harming the brand image.

In influencer marketing, it is important to investigate how the perceived authenticity of influencers affects the impact of affective components in their messages. Future studies should examine the congruence between influencers and brands, analyzing how this alignment enhances credibility and message effectiveness. Comparing the effectiveness of virtual influencers and human influencers in driving emotional engagement and consumer identification is another valuable avenue for exploration. Research should also examine how influencer marketing impacts purchase decisions in high and low involvement situations, while understanding cognitive processing mechanisms to mitigate potential negative perceptions from campaigns.

Finally, digital marketing research must address the distinctions between the affective components to achieve greater theoretical clarity. Future studies should define these constructs more precisely to better understand their influence on consumer behavior and marketing outcomes, providing a stronger foundation for practical strategies. The ambiguity surrounding affective components is not exclusive to marketing but originates in psychology, where the distinctions between different affective elements remain inconsistently defined in the literature.

This study highlights the complexity of affective interactions in digital marketing, providing a review for future investigations. By addressing these gaps, the academic community can contribute to the development of more effective, humanized marketing strategies, reinforcing the importance of affects in a dynamic and constantly evolving digital environment.

This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior – Brasil (CAPES) – Finance Code 001. Special thanks go to our academic advisors and professors whose insights and guidance were invaluable throughout the study. We are also indebted to our peers and colleagues at Universidade Federal do Paraná for their constructive critiques and support. Lastly, we extend our deepest gratitude to all those who contributed to the success of this research.

The supplementary material for this article can be found online.