Keywords

Platform-Based Social Media Marketing, SMMA, Instagram, Customer-Based Brand Equity, Structural Equation Modelling, Brand Equity Dimensions.

Introduction

In the rapidly evolving landscape of digital branding, Instagram has emerged as a key arena for consumer–brand interaction (Blanco-Moreno et al., 2024). With its visually immersive interface, algorithmic content distribution, and suite of storytelling tools (e.g., Reels, Stories, carousels), Instagram offers a dynamic environment where social media marketing activities (SMMAs) are not only consumed but co-created with users (Satar et al., 2024). With over two billion monthly active users globally and over 300 million in India alone, Instagram offers unparalleled reach and immersion (Selvakumar et al., 2025). It has become a fertile ground for consumer–brand interaction, enabling storytelling through images, videos, Reels, and ephemeral Stories. As brands adapt to changing consumer preferences for personalization, transparency, and message coherence, Social Media Marketing Activities (SMMAs) have evolved to include visually cohesive feeds, influencer partnerships, informative posting, and interactive features.

The platform’s relevance is reflected in brands’ increasing investment in tailored Instagram social media marketing activities (SMMAs), with 78% marketers integrating Instagram in their digital marketing (Ross, 2025). These activities shape how consumers process brand signals and engage cognitively, emotionally, and behaviorally with brand content (Ibrahim et al., 2024).

Despite the platform’s widespread commercial adoption, academic research on how such Instagram-specific SMMAs strategies influence distinct dimensions of consumer-based brand equity, i.e., awareness, image, perceived quality, and loyalty, remains limited (Huang, 2023).

Much of the existing literature treats SMMAs generically, without isolating platform-specific affordances or accounting for evolving content formats (Balabanis and Chatzopoulou, 2025). Furthermore, while brand awareness and image have received substantial attention, long-term consumer-based brand equity components like brand loyalty and perceived quality are less frequently examined in Instagram contexts (Ibrahim et al., 2024). This lack of granularity undermines our understanding of how brands can strategically deploy Instagram SMMAs to build enduring consumer-brand relationships.

To address these gaps, this study tries to develop a platform-specific framework examining the effects of four Instagram SMMAs strategy components, i.e., message consistency, post informativeness, engagement, and content personal relevance, on the dimensions of customer-based brand equity (CBBE). By empirically validating this model through structural equation modeling with active Indian Instagram users, the present study aims to offer new theoretical insight into the psychology of digital branding, while equipping marketers with actionable strategies to optimize Instagram’s potential for sustainable brand equity growth.

The study is divided into the following sections: firstly, the variables describing social media activities on Instagram are identified and described briefly, then a conceptual framework is proposed, which is tested in later sections via structural equation modelling, and findings are analysed and explained. The implications of the findings are discussed and future research directions are suggested. The findings of the study will help marketers to reflect on their social media strategies and how they can utilize and strengthen them for effective brand equity management.

Literature Review

Social Media Marketing Activities (SMMAs) on Instagram

The first step in the study is to identify the components of Instagram social media marketing activities (SMMAs). For this, a review of articles testing the impact of Instagram SMMAs on CBBE or its dimensions is carried out. Out of these, the most popular variables for analysing the impact of Instagram SMMAs on CBBE are entertainment, interaction, and sharing (Kim and Ko, 2012; Godey et al., 2016; de Vries et al., 2012; Abu Rumman, 2014). Another popular set of SMMAs used for studies is those derived from the honeycomb model, such as identity, conversation, presence, reputation, and relationship (Babac, 2011; Tresna and Wijaya, 2015; Kietzmann et al., 2012). Table 1 below gives a summary of all the variables studied as components of SMMAs on Instagram.

Table 1 Summary of Variables Studied as Components of Smmas on Instagram
SMMA variables	Research studies
Commonly used
Entertainment	Kim and Ko (2012); Godey et al. (2016); de Vries et al. (2012)
Trendiness	Kim and Ko (2012); Godey et al. (2016)
Interaction	Kim and Ko (2012); Godey et al. (2016); Abu Rumman (2014); de Vries et al. (2012)
Customization	Kim and Ko (2012); Godey et al. (2016)
Identity	Babac (2011); Tresna and Wijaya (2015); Kietzmann et al. (2012)
Conversation/Word-of-mouth	Babac (2011); Godey et al. (2016)
Sharing	Babac (2011); Tresna and Wijaya (2015); Abu Rumman (2014); Kietzmann et al. (2012)
Presence	Babac (2011); Tresna and Wijaya (2015); Kietzmann et al. (2012)
Reputation	Babac (2011); Tresna and Wijaya (2015); Kietzmann et al. (2012)
Relationship	Babac (2011); Tresna and Wijaya (2015); Kietzmann et al. (2012)
Less Common
Engagement	Perera and Perera (2018); Kavisekera and Abeysekera (2016)
Consistency	Perera and Perera (2018)
Informativeness	de Vries et al. (2012)
Personal relevance	Vries et al. (2012)

The analysis depicts that a void exists in the literature, and there is a need to conduct studies on less commonly investigated components of SMMAs influencing CBBE on Instagram. Further, some of the constructs studied were found to be overlapping with other variables. For example, interaction, sharing, and entertainment were found to be similar to sub-components of engagement. Therefore, the aim of the study is to identify those components of SMMAs that can be comprehensively described without any overlap with other variables to reduce redundancy.

Based on the above approach, engagement, informativeness, consistency, and personal relevance were identified as components of SMMAs' effectiveness on Instagram. Instagram is a consumer-powered channel, and consumer engagement is an important dimension of SMMAs (Rietveld et al., 2020). Informativeness has also been shown to be a key determinant of a favourable consumer response to SMMAs (Lee & Hong, 2016). Studies have also found that perceived consistency of communications is important for brand success, especially on social media channels such as Instagram (Šerić et al., 2020; Killian & McManus, 2015). Personal relevance was found to be a potential component of SMMAs in generating a positive consumer response (Geng et al., 2021). Hence, these variables were chosen for further investigation.

Engagement

Consumer engagement on Instagram with a brand can be defined as the involvement of consumers in brand-building activities that can have an influence on their decision-making. (Hollebeek, 2011) states customer engagement to be a state of mind defined by the degree of involvement and immersion with the brand-related activities. Consumer engagement is not constrained by the transactional nature and is much more than that (Doorn et al., 2010). It is defined as consumers’ behaviour that is brand-specific and is a result of some kind of motivation that the consumer has derived after interacting with a brand, and these interactions are a key aspect in the social media context (Hollebeek et al., 2014). Thus, consumer engagement is a crucial element in predicting and explaining consumer responses to social media marketing activities (SMMAs) on Instagram (Rietveld et al., 2020; Hollebeek et al., 2014). Therefore, we hypothesize that:

H₁: Engagement is an important aspect of SMMAs on Instagram.

Informativeness

The concept of informativeness is based on the rationality of consumers and enables consumers to arrive at an informed choice in their decision-making process regarding whether to accept a message or not, and is a distinct construct from emotional appeal (Lee & Hong, 2016). It is a perceptual construct that is measured via self-reported items (Lee & Hong, 2016). Studies in the field of SMMAs on Instagram have found that informational content of a post eases the decision-making process of consumers and helps them in making the right choices (Hazzam, 2022). Consumers value Instagram content that is informative in nature (Arli, 2017). Informativeness is an important aspect in influencing consumer attitudes towardsa social mediaadvertisement (Noguti & Waller, 2020). Informative ad messages on a social media platform such as Instagram can attract the attention of users and influence them to form a positive attitude towards the ad (Arli, 2017; Lee & Hong, 2016), which can further lead them to share the message with their network.

H₂: Informativeness is an important aspect of SMMAs' effectiveness on Instagram.

Consistency

There should be consistency in consumers' interactions with brands on Instagram and other communication channels for it to seem authentic (Killian & McManus, 2015). A misalignment can create confusion in the consumer’s mind as to which of the interactions truly represents the brand. Message consistency in Instagram interactions should be viewed from the aspect of content, timing, and tone (Qian et al., 2024). Communication on Instagram should complement the traditional brand communication channels (Šerić et al., 2020). The content creators of Instagram messages should align these messages with the brand personality (Watkins & Lee, 2016). The similarity of content and tone should be monitored in case of more than one content creator (Killian & McManus, 2015). Based on these arguments, we hypothesize:

H₃: Consistency is an important aspect of SMMAs' effectiveness on Instagram.

Personal Relevance

According to the Elaboration Likelihood Model (ELM), personal relevance has a positive impact on consumers’ motivation and their information-processing ability (Kitchen et al., 2014). Thus, in case of relevant information, the central route is adopted (Shahab et al., 2021). It can be assumed on the basis of ELM that when personal relevance is high, consumer involvement is higher, and there is an inclination towards adopting the central route for information processing. In such instances, the evaluation of advertising messages is done on the basis of past experiences, and accordingly, the response is decided (e.g., commenting, liking, sharing, or ignoring) (Shi et al., 2018). Therefore, it can be concluded that the personal relevance of messages and content on Instagram can attract the attention of consumers and make them more involved in the brand-building activities (Geng et al., 2021). Therefore, we hypothesize that:

H₄: Personal relevance is an important aspect of SMMAs' effectiveness on Instagram.

A favorable perception of social media marketing activities enhances corporate value and, in turn, strengthens CBBE. Empirical studies consistently support this relationship. Seo and Park (2018) demonstrated that airline social media marketing significantly improved brand awareness and brand image, both of which are central dimensions of CBBE. Similarly, Godey et al. (2016) provided evidence of a strong positive association between social networking site (SNS) marketing and CBBE, while Aji et al. (2020) confirmed that such activities by ready-to-drink tea brands substantially boosted brand equity.

In addition to brand awareness and brand image, social media marketing positively influences perceived quality and brand loyalty, which are critical determinants of CBBE (Nath Sanyal & Datta, 2011). Ibrahim (2022) found that engaging and well-structured social media campaigns significantly strengthened brand loyalty. Likewise, recent studies highlight that engaging social media content that is of personal relevance to consumers enhances their perceptions of quality, which further contributes to the development of strong CBBE (Shanahan et al., 2019). Collectively, this body of research underscores that social media marketing not only shapes awareness and image but also reinforces perceived quality and loyalty, thereby playing a comprehensive role in building and sustaining brand equity. Based on these, we hypothesize:

H₅: Effective SMMAs on Instagram have a positive effect on consumer-based brand equity.

Consumer-Based Brand Equity

Brand awareness

Brand awareness can be described in terms of how easily a consumer can recognize a brand in different circumstances (Keller, 1993). It has two components: recognition and recall (Aaker, 1991). It is a result of a consumer’s exposure to a brand. Therefore, the first building block of CBBE is creating brand awareness (Huang & Sarigöllü, 2012). Studies have found that participants chose high-quality brands more in the no brand awareness condition as compared to the brand awareness condition group (Macdonald and Sharp, 2000). Brand awareness was found to act as a cue in retrieving brand-related information, thus affecting choices (Patil, 2017). This brings us to the following hypothesis:

H₆: Brand awareness is an important dimension of consumer-based brand equity.

Brand Image

Brand image is a combination of various brand associations a consumer has with regard to a specific brand (e.g., Biel 1992). It is the consumer's perceptions of a brand’s tangible and intangible associations (Engel et al., 1993). Kapferer (1992) said that consumers form a mental image by combining all the brand cues. So, social media marketing efforts of the brand can result in the formation of the consumer’s brand image (Godey et al., 2016). Multiple studies in branding literature suggest that brand image is a crucial component of CBBE (e.g., Keller, 1993; Kim and Hyun, 2011). Positive brand images result in higher brand equity and enable brands to command a price premium (Anselmsson et al., 2014). Positive brand image also leads to brand preference (Alamro & Rowley, 2011). Strong, positive, and unique associations are required for creating a positive brand image to make the consumers more biased towards the brand and increase brand equity (Parris & Guzmán, 2023). A unique brand image in the minds of consumers can also become a source of differentiation, thus enhancing the brand equity (Sasmita & Mohd Suki, 2015). Hence, we hypothesize:

H₇: Brand image is an important dimension of consumer-based brand equity

Brand Loyalty

Brand loyalty can be defined as the commitment developed in consumers because of the perception that the brand is better compared to its alternatives, and this commitment is reflected in repeat purchases (Foroudi et al., 2018). Copeland (1923) introduced the concept of brand loyalty. Brand loyalty was also viewed as a comparison between brands with similar offerings (e.g., Aaker, 1996). Brand loyalty is one of the crucial elements of CBBE, and loyal consumers have a long-term effect in generating future revenues and therefore influencing the brand value (Parris and Guzmán, 2023). Therefore, brand loyalty can be summarised as commitment to repeat purchases in spite of situational influences capable of inducing switching behaviour (Akoglu and Özbek, 2022). Hence, the relationship between brand loyalty and brand equity is two-way, as both influence each other. Therefore, we hypothesize that:

H₈: Brand loyalty is an important dimension of consumer-based brand equity.

Perceived Quality

Perceived quality can be described as the consumer’s perception of a brand being superior to its competitors (Akoglu & Özbek, 2022). High perceived quality increases purchase intentions among consumers and acts as a point of differentiation from competitors (Wu et al., 2021). High perceived quality also enables the firm to ask for a premium price (Steenkamp et al., 2010) and paves the way for brand extensions (Völckner et al., 2010). Perceived quality has been incorporated in major CBBE frameworks as an important dimension (Aaker, 1996; Keller, 1993). The reason behind considering perceived quality as an important dimension is based on its strategic implications on brand equity, as it reduces the perceived risk (Rahman and Soesilo, 2018). This brings us to the following hypothesis:

H₉: Perceived quality is an important dimension of consumer-based brand equity.

Conceptual Framework

A conceptual framework is proposed on the basis of a review of existing literature pertaining to studying the impact of social media marketing on consumer-based brand equity and is presented in Figure 1. The study hypothesizes that engagement, informativeness, consistency, and personal relevance are the key components measuring social media marketing activities (SMMAs), and brand awareness, brand image, brand loyalty, and perceived quality are primary dimensions of brand equity. The study tries to establish the relationship between SMMAs and brand equity creation.

Methodology

Sampling and Data Collection

For data collection, a convenience sampling technique was applied to conduct a structured online survey. The survey questionnaire was circulated through Google Forms on Instagram. Though the survey was open to all demographics, screening questions like the usage of Instagram were put in place to collect responses only from active Instagram users. Since the survey was administered online, responses from all regions of the country were received. The participants were briefed about the purpose of the study in the introductory section and were asked to respond to the survey questionnaire in the context of brands that they follow on social media. The measures for survey items were adopted from previous studies. Out of the 318 responses received, 84 unengaged responses were eliminated from the study, and 234 responses were selected for further analysis. All respondents were active on Instagram with an average usage time of more than 1 hour a day. The sample had almost equal representation of both genders, with 113 males (48.3%) and 119 females (50.8%). The age group 25-35 years old represented the majority of the participants (54.2%). The reason could be that this age group is the one that does the most online shopping. Table 2 shows the demographic details of the respondents.

Table 2 Sample Characteristics
Classification	Frequency	Percentage frequency (%)
Gender
Male	113	48.3%
Female	119	50.8%
Prefer not to say	2	0.9%
Age
18-25 years old	69	29.7%
25–35 years old	127	54.2%
35–50 years old	28	11.9%
50 years old and above	10	4.2%
Education level
Undergraduate	30	12.7%
Graduate	45	19.5%
Postgraduate	131	55.9%
Doctoral	28	11.9%
Time spent on Instagram
1-2 hours	89	38.1%
2-3 hours	83	35.6%
3-4 hours	26	11%
4 hours or more	36	15.3%

Data Analysis and Results

Dimensionality and Reliability of Constructs

An exploratory factor analysis (EFA) was carried out to assess the uni-dimensionality of the constructs. The analysis employed principal component extraction with varimax rotation, setting the eigenvalue threshold above 1. IBM SPSS Statistics 22 was used for the analysis. The Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy yielded a value of 0.916, indicating that the data were appropriate for factor analysis. Additionally, Bartlett’s test of sphericity was significant (p = 0.000), suggesting strong intercorrelations among the variables.

From the original pool of 31 items, those showing cross-loadings above 0.30 were excluded, following Hair Jr et al. (2010). Therefore, the items REL 1, BI 1, and BL 4 were removed. The final analysis produced an eight-factor solution, accounting for 81.133% of the total variance. All retained items demonstrated factor loadings exceeding 0.60 and cross-loadings below 0.30, in line with recommendations by Nunally and Bernstein (1978) and Hair Jr et al. (2010).

Construct reliability was verified using Cronbach’s alpha, with values ranging from 0.820 to 0.944 across all factors, indicating high internal consistency. A summary of the EFA results is provided in Table 3.

Table 3 Descriptive Statistics of Exploratory Factor Analysis
Latent variables	Item code	Mean	SD	Factor loadings	Cronbach’s alpha
Engagement (Schivinski et al., 2016)					0.895
I read posts related to brand X on Instagram	ENG1	4.85	1.25	0.821
I express my reactions to brand X's Instagram post and comments by using buttons Like, Love etc	ENG2	4.84	1.19	0.806
I engage in conversations on brand X's Instagram page (e.g, commenting, asking, and answering questions)	ENG3	5.00	1.21	0.779
I share brand X’s Instagram posts on my own social media account	ENG4	4.62	1.33	0.757
I initiate new posts related to brand X on my social media account	ENG5	4.63	1.27	0.803
Informativeness (Yadav and Rahman, 2017)					0.914
X brand's Instagram page offers accurate information on products	INF1	4.82	1.42	0.802
X brand's Instagram page offers useful information	INF2	4.85	1.44	0.846
The information provided by X brand's Instagram page is comprehensive	INF3	4.83	1.46	0.821
Consistency (Šerić et al., 2020)					0.873
I find X brand's Instagram message to be consistent across all social media platforms	CONST1	5.02	1.50	0.873
I feel that the X brand has a consistent image	CONST2	5.10	1.59	0.901
Personal relevance (Jung, 2017)					0.896
When I saw this ad, I feel it is designed specially for me	REL1	*
When I saw this ad, I feel it has value for me	REL2	5.21	1.40	0.899
When I saw this ad, I think it is relevant to my needs	REL3	5.07	1.39	0.921
Brand Awareness (Yoo and Donthu, 2001)					0.847
I can quickly recall the symbol or logo of X brand.	BA1	5.11	1.26	0.729
I can easily recognize X brand among other brands	BA2	5.29	1.32	0.742
Some characteristics of X come to my mind quickly.	BA3	4.99	1.31	0.788
Brand Image (Kim and Hyun, 2011)					0.820
X brand has a favourable image	BI1	*
X brand has extensive experience	BI2	4.48	1.39	0.718
X brand is a representative of its industry	BI3	4.77	1.30	0.783
X brand is a customer-oriented company	BI4	4.86	1.33	0.730
Brand Loyalty (Yoo and Donthu, 2001;Chaudhuri and Holbrook, 2001)					0.849
I will continue to buy my favourite brand	BL1	4.66	1.44	0.881
If my favourite brand is not available, then I would buy it from another store instead of buying another brand	BL2	4.63	1.42	0.890
I am willing to wait if my favourite brand is not available in market	BL3	5.36	1.57	0.613
I prefer my favourite brand over the others	BL4	*
Perceived Quality (Aaker, 1996)					0.944
Compared to other brands of, I think this brand is of very high quality.	PQ1	4.83	1.40	0.876
This brand is the best brand in its product class.	PQ2	4.75	1.39	0.867
Brand consistently performs better than all other brands in its product class.	PQ3	4.77	1.40	0.867

KMO measure of sampling adequacy = 0.916; Total variance explained = 81.133%

Measurement Model Assessment of the Research Model

To assess the accuracy of the theoretical constructs and their associated indicators, a confirmatory factor analysis (CFA) was conducted using IBM SPSS AMOS 22 to assess the measurement model, which included eight constructs and 25 indicators, estimated via the maximum likelihood method. Model fit indices indicated a good fit: χ²/df = 2.26, GFI = 0.879, NFI = 0.903, TLI = 0.931, CFI = 0.943, and RMSEA = 0.063. Convergent validity was supported by significant factor loadings (p < 0.001), composite reliability (CR > 0.70), and average variance extracted (AVE > 0.50). Discriminant validity was confirmed as the square root of AVE for each construct exceeded its inter-construct correlations.

Refer to Table 4 for discriminant validity and Tables 4 & 5 for reliability and convergent validity metrics.

Table 4 Discriminant Validity of the Research Model
	ENG	INF	REL	CONST	BA	BI	BL	PQ
ENG	0.797
INF	0.505	0.884
REL	0.323	0.368	0.743
CONST	0.426	0.443	0.255	0.771
BA	0.489	0.449	0.408	0.249	0.808
BI	0.472	0.570	0.294	0.406	0.520	0.778
BL	0.100	0.139	0.086	0.149	0.276	0.245	0.840
PQ	0.485	0.577	0.366	0.395	0.455	0.620	0.233	0.921

Table 5 Confirmatory Factor Analysis of the Research Model
Latent Variables	Factor loadings	CR	AVE
Engagement		0.896	0.635
ENG1	0.887
ENG2	0.872
ENG3	0.757
ENG4	0.712
ENG5	0.742
Informativeness		0.915	0.782
INF1	0.854
INF2	0.913
INF3	0.886
Personal relevance		0.745	0.552
REL2	0.935
REL3	0.867
Consistency		0.806	0.594
CONST1	0.495
CONST2	0.833
CONST3	0.919
Brand Image		0.821	0.605
BI2	0.872
BI3	0.757
BI4	0.712
Brand Awareness		0.849	0.654
BA1	0.856
BA2	0.865
BA3	0.694
Brand Loyalty		0.873	0.706
BL1	0.930
BL2	0.957
BL3	0.580
Perceived Quality		0.944	0.849
PQ1	0.938
PQ2	0.925
PQ3	0.901

Structural Model Assessment and Hypothesis Testing of the Research Model

The structural model was evaluated to explore the relationships among latent constructs. Model fit was confirmed using multiple indices: CMIN/DF = 1.746, GFI = 0.898, NFI = 0.923, TLI = 0.961, CFI = 0.965, and RMSEA = 0.049, all within acceptable thresholds, indicating a well-fitting model.

Following model validation, hypothesis testing was conducted. Our findings highlight that engagement (β = 0.680, p < 0.001), informativeness (β = 0.768, p < 0.001), consistency (β = 0.503, p < 0.001), and personal relevance (β = 0.482, p < 0.001) were all significant aspects of Instagram’s SMMAs supporting H1 to H4. Further, Instagram social media activities that are engaging, informative, consistent, and personally relevant to consumers positively influence consumer-based brand equity (β = 0.931, p < 0.001), thus H5 is supported. Consumer-based brand equity can further lead to brand awareness (β = 0.653, p < 0.001), positive brand image (β = 0.785, p < 0.001), brand loyalty (β = 0.281, p < 0.001), and enhanced perceived quality (β = 0.774, p < 0.001), confirming H6 to H9. For detailed results, see Table 6.

Table 6 Hypothesis Testing
Hypotheses	β	p-values	Decision
H1: SMMA → ENG	0.680	0.000	Supported
H2: SMMA→ INF	0.768	0.000	Supported
H3: SMMA → CONST	0.503	0.000	Supported
H4: SMMA → REL	0.482	0.000	Supported
H5: SMMA → CBBE	0.931	0.000	Supported
H6: CBBE→ BA	0.653	0.000	Supported
H7: CBBE→ BI	0.785	0.000	Supported
H8: CBBE → BL	0.281	0.000	Supported
H9: CBBE → PQ	0.774	0.000	Supported

Discussion and Implications

Social media marketing activities on Instagram are attracting the interest of researchers, and studies are focusing on the theoretical and managerial implications of social media for brand management (Satar et al., 2024). Despite this, there is a lack of empirical evidence on how Instagram SMMAs impact the consumer-based brand equity creation process and what their influence is on other crucial elements of consumer-based brand equity, such as brand awareness, brand loyalty, brand image, and perceived quality (Huang, 2023). The present study tries to address these voids in the existing literature. Careful selection of variables that describe the impact of Instagram-based social media activities on consumer behaviour is done. The emphasis was to identify variables that can describe social media activities on Instagram in a comprehensive manner without overlapping with other variables. This research's theoretical contribution is providing a comprehensive framework that is capable of explaining how SMMAs impact consumer-based brand equity on Instagram. Although extant literature talks about the strategic importance of SMMAs on Instagram (Selvakumar et al., 2025), our study provides empirical evidence for the same. Also, this study lays emphasis on the fact that all four dimensions of consumer-based brand equity are important, and the impact of SMMAs on each of these should be studied. The major contribution of this study is that Instagram SMMAs that are engaging, informative, consistent and personally relevant to consumers can significantly enhance consumer-based brand equity.

Instagram SMMAs, therefore, can achieve branding goals in a similar way to traditional marketing activities. The managerial implications of the present study can be multifaceted. The present study identifies important components of Instagram SMMAs that can help marketing managers determine which areas to focus on while drafting a social media strategy. All the elements of SMMAs, i.e., engagement, informativeness, consistency, and personal relevance, should be given importance when creating social media content or advertisements. Also, current social media strategies should be modified and incorporate the above elements for improved brand-building activities that generate positive consumer responses. The content on Instagram should be made more engaging, informative, consistent, and relevant to users. Brands should look for ways to incorporate these aspects on their Instagram pages. Social media should not just be seen as a medium for increasing reach but as a brand-building tool competing with traditional marketing channels (TV and print media), enabling consumers to form an emotional connection with brands.

Limitations and Future Research

The present study also has certain limitations. Firstly, the validity of the proposed conceptual framework should be established in future studies, as the components used for describing SMMAs on Instagram had not been studied together earlier. Another limitation of the study is that it could not study all the variables measuring social media activities to avoid making the structural equation model too complex. Researchers can study other variables like vividness, accessibility, credibility, etc., which would further advance the knowledge in the area of platform-based social media marketing and branding. Demographic factors (age, gender, income, etc.) can also moderate the relationship between social media marketing activities and consumer-based brand equity creation; future studies can consider this aspect.

References

Aaker, D. A. (1996). Measuring brand equity across products and markets. California Management Review, 38, 102–120.

Indexed at, Google Scholar, Cross Ref

Aaker, D. A., & Equity, M. B. (1991). Capitalizing on the Value of a Brand Name. New York, 28(1), 35–37.

Abu Rumman, A. (2014). The Impact of Social Media Marketing on Brand Equity: An Empirical Study on Mobile Service Providers in Jordan.

Aji, P. M., Nadhila, V., & Sanny, L. (2020). Effect of social media marketing on Instagram towards purchase intention: Evidence from Indonesia’s ready-to-drink tea industry. International Journal of Data and Network Science, 4(2), 91–104.

Akoglu, H. E., & Özbek, O. (2022). The effect of brand experiences on brand loyalty through perceived quality and brand trust: a study on sports consumers. Asia Pacific Journal of Marketing and Logistics, 34(10), 2130–2148.

Indexed at, Google Scholar, Cross Ref

Alamro, A., & Rowley, J. (2011). Antecedents of brand preference for mobile telecommunications services. Journal of Product & Brand Management, 20(6), 475–486.

Anselmsson, J., Bondesson, N. V., & Johansson, U. (2014). Brand image and customers’ willingness to pay a price premium for food brands. Journal of Product and Brand Management, 23(2), 90–102.

Cross Ref

Arli, D. (2017). Does Social Media Matter? Investigating the Effect of Social Media Features on Consumer Attitudes. Journal of Promotion Management, 23(4), 521–539.

Cross Ref

Babac, R. (2011). Impact of social-media use on brand equity of magazine brands: A qualitative study of Vogue Turkey.

Indexed at, Google Scholar

Balabanis, J., & Chatzopoulou, E. (2025). The value of social media content to browsing and searching consumers of luxury products on Instagram. European Journal of Marketing, 59(5), 1227–1259.

Cross Ref

Blanco-Moreno, S., González-Fernández, A. M., Munoz-Gallego, P. A., & Casaló, L. V. (2024). Understanding engagement with Instagram posts about tourism destinations. Journal of Destination Marketing & Management, 34, 100948.

Chaudhuri, A., & Holbrook, M. B. (2001). The chain of effects from brand trust and brand affect to brand performance: the role of brand loyalty. Journal of Marketing, 65(2), 81–93.

Copeland, M. T. (1923). Relation of consumers’ buying habits to marketing methods. Harvard Business Review, 1(2), 282–289.

De Vries, L., Gensler, S., & Leeflang, P. S. H. (2012). Popularity of Brand Posts on Brand Fan Pages: An Investigation of the Effects of Social Media Marketing. Journal of Interactive Marketing, 26(2), 83–91.

Indexed at, Google Scholar, Cross Ref

Foroudi, P., Jin, Z., Gupta, S., Foroudi, M. M., & Kitchen, P. J. (2018). Perceptional components of brand equity: Configuring the Symmetrical and Asymmetrical Paths to brand loyalty and brand purchase intention. Journal of Business Research, 89, 462–474.

Geng, S., Yang, P., Gao, Y., Tan, Y., & Yang, C. (2021). The effects of ad social and personal relevance on consumer ad engagement on social media: The moderating role of platform trust. Computers in Human Behavior, 122, 106834.

Godey, B., Manthiou, A., Pederzoli, D., Rokka, J., Aiello, G., Donvito, R., & Singh, R. (2016). Social media marketing efforts of luxury brands: Influence on brand equity and consumer behavior. Journal of Business Research, 69(12), 5833–5841.

Cross Ref

Hair Jr, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate data analysis. In Multivariate data analysis (p. 785).

Indexed at, Google Scholar, Cross Ref

Hazzam, J. (2022). The moderating role of age on social media marketing activities and customer brand engagement on Instagram social network. Young Consumers, 23(2), 197–212.

Hollebeek, L. (2011). Exploring customer brand engagement: definition and themes. Journal of Strategic Marketing, 19(7), 555–573.

Hollebeek, L. D., Glynn, M. S., & Brodie, R. J. (2014). Consumer Brand Engagement in Social Media: Conceptualization, Scale Development and Validation. Journal of Interactive Marketing, 28(2), 149–165.

Indexed at, Google Scholar, Cross Ref

Huang, R., & Sarigöllü, E. (2012). How brand awareness relates to market outcome, brand equity, and the marketing mix. Journal of Business Research, 65(1), 92–99.

Cross Ref

Huang, Y.C. (2023). The roles of social media and mutual relationships between travel attitudes and brand equity. Asia Pacific Journal of Marketing and Logistics, 36(2), 390–407

Cross Ref

Ibrahim, B. (2022). Social media marketing activities and brand loyalty: A meta-analysis examination. Journal of Promotion Management, 28(1), 60–90.

Ibrahim, B., Hazzam, J., Ali Qalati, S., Aljarah, A., & Dobson, P. (2024). Building a tribe on Instagram: How User-generated and Firm-created Content can drive brand evangelism and fidelity. Journal of Marketing Communications, 1–20.

J. Kitchen, P., Kerr, G., E. Schultz, D., McColl, R., & Pals, H. (2014). The elaboration likelihood model: review, critique and research agenda. European Journal of Marketing, 48(11–12), 2033–2050.

Jung, A.-R. (2017). The influence of perceived ad relevance on social media advertising: An empirical examination of a mediating role of privacy concern. Computers in Human Behavior, 70, 303–309.

Kapferer, J. N. (1992). Strategic brand management: New approaches to creating and evaluating brand equity. Simon and Schuster.

Google Scholar

Keller, K. L. (1993). Conceptualizing, Measuring, and Managing Customer-Based Brand Equity. Journal of Marketing, 57(1), 1.

Cross Ref

Kietzmann, J. H., Silvestre, B. S., McCarthy, I. P., & Pitt, L. F. (2012). Unpacking the social media phenomenon: towards a research agenda. Journal of Public Affairs, 12(2), 109–119.

Killian, G., & McManus, K. (2015). A marketing communications approach for the digital era: Managerial guidelines for social media integration. Business Horizons, 58(5), 539–549.

Cross Ref

Kim, A. J., & Ko, E. (2012). Do social media marketing activities enhance customer equity? An empirical study of luxury fashion brand. Journal of Business Research, 65(10), 1480–1486.

Indexed at, Google Scholar, Cross Ref

Kim, J.-H., & Hyun, Y. J. (2011). A model to investigate the influence of marketing-mix efforts and corporate image on brand equity in the IT software sector. Industrial Marketing Management, 40(3), 424–438.

Lee, J., & Hong, I. B. (2016). Predicting positive user responses to social media advertising: The roles of emotional appeal, informativeness, and creativity. International Journal of Information Management, 36(3), 360–373.

Macdonald, E. K., & Sharp, B. M. (2000). Brand awareness effects on consumer decision making for a common, repeat purchase product: A replication. Journal of Business Research, 48(1), 5–15.

Nath Sanyal, S., & Datta, S. K. (2011). The effect of perceived quality on brand equity: an empirical study on generic drugs. Asia Pacific Journal of Marketing and Logistics, 23(5), 604–625.

Indexed at, Google Scholar, Cross Ref

Noguti, V., & Waller, D. S. (2020). Motivations to use social media: effects on the perceived informativeness, entertainment, and intrusiveness of paid mobile advertising. Journal of Marketing Management, 36(15–16), 1527–1555.

Cross Ref

Nunally, J. C., & Bernstein, I. H. (1978). Psychometric theory. New York: McGraw-Hill.

Parris, D. L., & Guzmán, F. (2023). Evolving brand boundaries and expectations: looking back on brand equity, brand loyalty, and brand image research to move forward. Journal of Product & Brand Management, 32(2), 191–234.

Patil, P. H. (2017). Brand awareness and brand preference. International Research Journal of Management and Commerce, 4(7), 15–24.

Perera, G. R., & Perera, I. (2018). Influence of social media marketing on the brand image of organizations in the hospitality industry of Sri Lanka. In Media influence: Breakthroughs in research and practice (pp. 371–383). IGI Global Scientific Publishing.

Indexed at, Google Scholar, Cross Ref

Qian, S., Lu, Y., Peng, Y., Shen, C. (Cindy), & Xu, H. (2024). Convergence or divergence? A cross-platform analysis of climate change visual content categories, features, and social media engagement on Twitter and Instagram. Public Relations Review, 50(2), 102454.

Indexed at, Google Scholar, Cross Ref

Rahman, F., & Soesilo, P. K. M. (2018). The effect of information exposure of contract manufacturing practice on consumers’ perceived risk, perceived quality, and intention to purchase private label brand. Journal of Retailing and Consumer Services, 42, 37–46.

Rietveld, Robert, Van Dolen,  Willemijn, Mazloom,  Masoud, & Worring,  Marcel. (2020). What you Feel, Is what you like Influence of Message Appeals on Customer Engagement on Instagram. Journal of Interactive Marketing, 49(1), 20–53.

Cross Ref

Ross, C. (2025). Instagram advertising and marketing - statistics & facts. Statista.

Sasmita, J., & Mohd Suki, N. (2015). Young consumers’ insights on brand equity: Effects of brand association, brand loyalty, brand awareness, and brand image. International Journal of Retail & Distribution Management, 43(3), 276–292.

Satar, M. S., Rather, R. A., Shahid, S., Islam, J. U., Parrey, S. H., & Khan, I. (2024). Dynamics of social media involvement in building customer engagement and co-creation behavior: the moderating role of brand interactivity. Asia Pacific Journal of Marketing and Logistics, 36(10), 2237–2258.

Indexed at, Google Scholar, Cross Ref

Schivinski, B., Christodoulides, G., & Dabrowski, D. (2016). Measuring consumers’ engagement with brand-related social-media content: Development and validation of a scale that identifies levels of social-media engagement with brands. Journal of Advertising Research, 56(1), 64–80.

Google Scholar

Selvakumar, V., Reddy, N. K., Tulasi, R. S. V., & Kumar, K. R. (2025). Data-Driven Insights into Social Media Behavior Using Predictive Modeling. Procedia Computer Science, 252, 480–489.

Cross Ref

Seo, E.-J., & Park, J.-W. (2018). A study on the effects of social media marketing activities on brand equity and customer response in the airline industry. Journal of Air Transport Management, 66, 36–41.

Šerić, M., Ozretić-Došen, Đ., & Škare, V. (2020). How can perceived consistency in marketing communications influence customer–brand relationship outcomes? European Management Journal, 38(2), 335–343.

Cross Ref

Shahab, M. H., Ghazali, E., & Mohtar, M. (2021). The role of elaboration likelihood model in consumer behaviour research and its extension to new technologies: A review and future research agenda. International Journal of Consumer Studies, 45(4), 664–689.

Indexed at, Google Scholar, Cross Ref

Shanahan, T., Tran, T. P., & Taylor, E. C. (2019). Getting to know you: Social media personalization as a means of enhancing brand loyalty and perceived quality. Journal of Retailing and Consumer Services, 47, 57–65.

Cross Ref

Shi, J., Hu, P., Lai, K. K., & Chen, G. (2018). Determinants of users’ information dissemination behavior on social networking sites: An elaboration likelihood model perspective. Internet Research, 28(2), 393–418.

Steenkamp, J.-B. E. M., Van Heerde, H. J., & Geyskens, I. (2010). What makes consumers willing to pay a price premium for national brands over private labels? Journal of Marketing Research, 47(6), 1011–1024.

Tresna, L., & Wijaya, J. C. (2015). The impact of social media towards brand equity: an empirical study of mall X. IBuss Management, 3(2).

Völckner, F., Sattler, H., Hennig-Thurau, T., & Ringle, C. M. (2010). The role of parent brand quality for service brand extension success. Journal of Service Research, 13(4), 379–396.

Indexed at, Google Scholar, Cross Ref

Watkins, B., & Lee, J. W. (2016). Communicating brand identity on social media: A case study of the use of Instagram and Twitter for collegiate athletic branding. International Journal of Sport Communication, 9(4), 476–498.

Wu, X., Xiong, J., Yan, J., & Wang, Y. (2021). Perceived quality of traceability information and its effect on purchase intention towards organic food. Journal of Marketing Management, 37(13–14), 1267–1286.

Yadav, M., & Rahman, Z. (2017). Measuring consumer perception of social media marketing activities in e-commerce industry: Scale development & validation. Telematics and Informatics, 34(7), 1294–1307.

Yoo, B., & Donthu, N. (2001). Developing and validating a multidimensional consumer-based brand equity scale. Journal of Business Research, 52(1), 1–14.

Indexed at, Google Scholar, Cross Ref

Received: 28-Aug-2025, Manuscript No. AMSJ-25-16163; Editor assigned: 29-Aug-2025, PreQC No. AMSJ-25-16163(PQ); Reviewed: 01-Sep-2025, QC No. AMSJ-25-16163; Revised: 06-Sep-2025, Manuscript No. AMSJ-25-16163(R); Published: 17-Sep-2025