The cosmetics beauty industry in India has experienced significant growth, becoming a favoured choice among the millennial generation for products and services. As this sector evolves, various beauty brands have emerged, each attracting users with their unique appeal. These brands are increasingly recognized by consumers as essential tools for enhancing personal appearance, allowing individuals to look more stylish and contemporary.

A key factor contributing to the success of beauty brands is their image, which often hinges on the endorsement and influence of public figures. Celebrities and influencers play a pivotal role in shaping consumer perceptions; the millennial generation, in particular, tends to emulate the lifestyles and fashion choices of these icons. This tendency illustrates the powerful impact that public figures have on consumer behaviour, as they not only drive trends but also enhance the desirability of products.

In essence, the health of a brand's image in the beauty industry is closely linked to the ability to connect with consumers through relatable and aspirational figures. As millennials seek to express their identity and enhance their appearance, the collaboration between beauty brands and public figures becomes increasingly crucial for sustaining brand loyalty and fostering consumer engagement.

Today’s consumers are extremely discerning when selecting cosmetic products prior to making a purchase. They take various factors into account before arriving at a decision. In addition to evaluating product quality, consumers also consider the brand image of the beauty products they choose. Brands that enjoy a strong reputation or are widely recognized often become the preferred options for consumer. Cosmetics play very important role in enhancing both beauty and health of facial skin, particularly among Generation Z. This demographic, born between 1997 and 2012, represents a transitional generation from Millennials, experiencing rapid technological advancements. As modernization influences the cosmetics industry, Gen Z's economic behavior is evolving, differentiating them from previous generations.

Their growing awareness of the importance of skincare for the face and body has led to an increased interest in cosmetic products, making them a necessity for this generation. The size of the skincare industry in India was valued at USD 2,933.7 million in 2023 and is expected to grow at a compound annual growth rate (CAGR) of 14.6% during the forecast period. By 2034, the market is projected to expand from USD 3,310.5 million in 2024 to USD 12,934.2 million. This growth is fueled by shifting consumer preferences, rising disposable income, and an increasing emphasis on personal grooming and wellness. Factors such as heightened awareness of skincare routines, a growing demand for natural and organic products, and an expanding middle-class population seeking high-quality skincare solutions are expected to further drive the industry's expansion. Indian Skincare Market size

The Indian skincare market reached a value of USD 2,933.7 million in 2023 and is projected to grow at a CAGR of 14.6% from 2024 to 2034. This robust expansion is driven by several factors: a) Increasing disposable incomes, b) Growing consumer awareness, c) Expanding middle-class population. The demand for skincare products has experienced a significant uptick, propelled by: a) Social media influence promoting beauty and skincare trends, b) Expansion of e-commerce platforms enhancing product accessibility, c) Shift towards organic and natural products. This last trend caters to a growing segment of health-conscious consumers, significantly impacting market dynamics. The industry is expected to grow from USD 3,310.5 million in 2024 to USD 12,934.2 million by 2034, reflecting the strong potential and evolving consumer preferences in the Indian skincare market.

The skincare market in India is predominantly driven by major metropolitan areas like Mumbai, Delhi, and Bangalore. These cities' high population density, urban lifestyles, and increased consumer spending on beauty products contribute significantly to market growth. Leading skincare brands have established a strong presence in these urban centers through extensive retail networks and targeted marketing campaigns. The diverse demographics in these cities also fuel demand for specialized skincare solutions, further stimulating market expansion.

India's regulatory landscape for cosmetic products is comprehensive, with the Bureau of Indian Standards (BIS) playing a crucial role in ensuring product safety and quality. As of 2022, the BIS had implemented over 70 standards specific to cosmetics, enforcing compliance with safety and efficacy requirements. These regulations serve to protect consumers from potentially harmful products while enhancing industry credibility. Adherence to these standards is essential for brands to gain market access and maintain consumer trust, making regulatory compliance a key consideration in product development and marketing strategies

Increasing Beauty Consciousness among Consumers

India's skincare industry is witnessing remarkable growth, driven by increasing beauty consciousness among consumers. As individuals become more health-aware and socially conscious, there is a noticeable shift toward self-care and personal grooming, fueling the demand for skincare products.

Social media platforms, beauty influencers, and celebrity endorsements play a significant role in amplifying this trend, encouraging consumers to explore innovative skincare solutions to achieve youthful and radiant skin. For example, a 2023 survey revealed that 65% of Indian consumers are willing to pay a premium for skincare products made with natural ingredients, highlighting the growing preference for organic and toxin-free formulations

Growing Popularity of Korean Skincare Products

The increasing popularity of K-Beauty, or Korean skincare products, in India has sparked significant consumer interest. K-Beauty emphasizes addressing skincare concerns while promoting the use of nourishing products to maintain a youthful complexion. Korean skincare offers a diverse range of treatments, such as sheet masks, essences, sleeping masks, and pressed serums. To meet the growing demand for Korean beauty solutions, several Indian skincare brands are introducing Korean-made or Korean-inspired products.

Category Insights- Sun care Segment: Leading the market in terms of product type, this segment is projected to grow at a CAGR of 16.8% between 2024 and 2034. And Hydration Segment: Based on functionality, hydration-focused products are expected to dominate the market through 2034, with an estimated CAGR of 17.2% during the forecast period.

rand Image (BI)

Bailey and Milligan (2022) suggest that brand image plays a crucial role in creating a self-identity and fostering the notion that our purchases reflect who we are. By associating certain colors, interests, and preferences with products, brands can facilitate decision-making for consumers, as their presence is ubiquitous. The brand image significantly influences consumers’ purchasing decisions, particularly when using online applications (Octhaviani & Sibarani, 2021). Kotler and Keller (2016) identify three key indicators of brand image: (1) the strength of brand associations; (2) the benefits derived from brand associations; and (3) the uniqueness of those associations.  A compelling brand image is characterized by three essential elements: (1) the development of a distinct product character that offers a value proposition; (2) the creation of a unique product identity that sets it apart from competitors; and (3) the ability to evoke emotional connections rather than relying solely on rational appeals. In essence, a brand serves as a unique identifier— such as a name, symbol, or packaging—that distinguishes a product or service from others offered by individual sellers or groups, thereby differentiating it from competitors’ offerings. Brands help foster consumer trust by assuring that products will meet their needs and provide satisfaction beyond expectations. The emergence of strong brands often stems from increased competition, necessitating distinct identities to differentiate products in the marketplace. Brands are instrumental for companies aiming to gain a competitive edge. Brand image encompasses consumer perceptions of various attributes, benefits, uses, contexts, users, and characteristics associated with a product's marketer or manufacturer. Ultimately, it reflects the overall perception of the brand, shaped by consumers’ information and experiences with it

Product Price (PI)

Mardia et al. (2021) define price as the monetary amount paid for a product or service, or the value exchanged by consumers to access the benefits or usage of that product or service. Arif Rahman (2010) elaborates that the objectives of pricing are as follows: i) Revenue—most businesses rely on income, with the exception of those in the public service sector; ii) Capacity—companies typically adjust supply and demand according to maximum production limits; iii) Customer Consideration—pricing is generally representative, meaning it adapts to various customer types, market segments, and different levels of purchasing power. These three factors may be addressed through strategies like price reductions, bonuses, and similar approaches.

Furthermore, Ardista and Wulandari (2020) state that several factors influence pricing, including: i) Demand Analysis—analyzing product demand involves two steps: evaluating expected prices and examining variations in sales; and ii) Competitor Reactions—competitors play a significant role in price determination, particularly regarding the perceived threat of competition. The indicators used to evaluate product pricing include: (1) price affordability;

(2) price alignment with product quality; (3) price alignment with benefits; and (4) price competitiveness relative to consumer ability. (Kotler & Armstrong, 2016, p. 78).

Brand Popularity (PP)

According to Hermawan (2014) as cited in Tumagor and Hidayat (2018), brand popularity refers to a potential buyer's ability to recognize or recall a brand within a specific product category. This recognition represents the initial step in establishing a product's brand identity. Shimp explains that brand awareness encompasses the brand's presence in consumers' minds when considering a particular product category, as well as how easily the brand name can be remembered. Moreover, brand awareness is seen as a fundamental aspect of brand equity.

Percy and Rossiter describe brand awareness as the buyer's capacity to recognize or recall a brand in sufficient detail to prompt a purchase decision. The process of building brand awareness requires ongoing efforts to reinforce consumer recognition, ensuring that they remember the brand as a leading choice among its competitors within the same product category. Therefore, it can be concluded that brand popularity or brand awareness is the ability of consumers to remember and identify a product linked to a specific brand. The indicators for assessing brand popularity include: (1) recognition of brand characteristics; (2) consideration of the brand; and (3) trust in the product (Nazib, 2016).

Purchasing-Decision (PD)

Kotler and Armstrong (2001) explain that understanding purchasing decisions marks the phase in the decision-making process where consumers actively make their choices. Furthermore, decision-making is an individual activity closely related to acquiring and utilizing the goods available. According to Kotler and Armstrong (2008), the purchase decision process encompasses determining what to buy and what not to buy.

Setiadi (2003) refers to consumer purchasing decisions as problem-solving. This concept signifies an ongoing interaction between various processes: environmental, cognitive, affective, and behavioral. The first stage involves recognizing the problem, followed by evaluating the best options. Subsequently, consumers select the goods and services. In the next phase, they utilize the chosen products or services. After experiencing the outcomes of their purchases, consumers often reassess their decisions. This process includes several steps taken to fulfill their needs and resolve any subsequent issues before reaching the post-purchase evaluation stage (Pranoto, 2008).

From these various definitions of purchasing decisions, it can be concluded that a purchasing decision represents a decision-making process regarding a purchase, determining whether a product or service will be acquired, starting with the awareness of a need or desire. The indicators that influence purchasing decisions include: (1) product choice; (2) brand selection; (3) supplier selection; (4) timing of purchase; (5) purchase quantity; and (6) payment method (Kotler and Armstrong, 2016, p. 78).

Conceptual Framework

Figure 1 Conceptual Framework

From the conceptual framework presented above, the following hypotheses can be formulated:

H1: Brand image positively and significantly influences the purchasing decisions of millennials and Gen Z regarding skincare products in Delhi NCR.

H2: Brand popularity positively and significantly affects the purchasing decisions of millennials and Gen Z concerning skincare products in Delhi NCR.

H3: Product price has a positive and significant impact on the purchasing decisions of millennials and Gen Z for skincare products in Delhi NCR.

H4: Brand image, brand popularity, and product price collectively have a positive and significant effect on the purchasing decisions of millennials and Gen Z regarding skincare products in Delhi NCR.

This research employs a quantitative method. The term "quantitative" refers to an approach grounded in positivism, used to examine populations or samples selected randomly, thereby utilizing research tools that analyze quantitative data with the aim of hypothesis testing (Sugiyono, 2017, p. 14). Quantitative methods are utilized to determine the effects of a treatment that are subsequently tested through hypotheses. In this study, a total of 180 respondents were sampled using the Slovin formula and the simple random sampling technique.

Data collection was conducted via a questionnaire employing a Likert scale with the following response options: Strongly Agree (5), Agree (4), Neutral (3), Disagree (2), and Strongly Disagree (1). The data analysis technique utilized in this research is partial least squares (PLS) analysis. According to Yamin (2021, p. 7), PLS analysis aims to predict, explore, and develop theoretical models, identify research variables and their measurements, create a structural model path diagram, and establish research hypotheses supported by relevant references and theories.

This study follows a three-stage analysis process: i) Outer Model Analysis which assesses the reliability and validity of the outer model, evaluated through Convergent Validity, Discriminant Validity, Average Variance Extracted (AVE), Composite Reliability, and Cronbach’s Alpha (Musyaffi et al., 2022, pp. 10-11); ii) Inner Model Analysis which explores the causal relationships between both exogenous and endogenous latent variables in the research (Musyaffi et al., 2022, p. 10)

Measurement Model

Reliability Test

The reliability test assesses whether repeated measurements of the same object yield consistent data. According to Sarwono and Jonathan (2014), reliability measures the internal consistency of the indicators of a construct, indicating the extent to which each indicator reflects a common latent construct. Kowanda and Dionysia (2016) further explain that reliability reflects the stability and consistency of the results (data) across different time points.

To evaluate the reliability of the constructs in this study, the composite reliability value was employed. Maspaitella et al. (2018) state that a variable is considered to have construct reliability if its composite reliability value exceeds 0.7 and the Cronbach's Alpha value is also greater than 0.7, indicating a good level of reliability for the variable. The composite reliability value for each indicator can be found in Table 1 below:

Table 1: Reliability test

In the table 1 above, it can be explained that the Brand Image (BI) variable with Cronbach’s alpha of 0.838 while the composite reliability is 0.853, it is declared reliable, the Product Price (PP) with Cronbach’s alpha of 0.785 while the composite reliability is 0.802, it is declared reliable, the Brand Popularity (BP) variable with Cronbach’s alpha of 0.903 while the

composite reliability is 0.913,it is declared reliable, the Purchasing Decision (PD) variable with Cronbach’s alpha of 0.903 while the composite reliability is 0.905, it is declared reliable.

Validity Test

Convergent Validity

As stated by Widyaningtyas, Syarah, et al. (2016), the validity test aims to assess the accuracy and precision of a measuring instrument in fulfilling its function or delivering appropriate measurement results, which is determined by calculating the correlation between each statement and the total score. In this study, the validity of measurements is evaluated through convergent validity and discriminant validity.

Convergent validity assesses the quality of a measurement instrument, typically represented by a set of question-statements (Kock, 2020a). A measurement instrument demonstrates good convergent validity if respondents interpret the question-statements (or other measures) related to each latent variable in the way intended by the designers of those statements (Kock, 2014). Essentially, convergent validity analysis examines the relationships between question statements and latent variables based on their loadings and cross-loadings. The coefficients of the question statements related to the primary latent variable are referred to as factor loadings, while those associated with other latent variables are known as cross-loadings.

Table:2 Loading factor Heating Map

Table 3: Factor Loading by Item

Source: Author Data

In Table 2 and Table 3, the loading factors are clarified, indicating that the variables of brand image, brand popularity, and product price all exhibit loading factor values greater than 0.7 or, at the very least, meet the threshold of 0.5. This suggests that all indicators fulfill the criteria for convergent validity, as none of the indicators for these variables have been removed from the model.

Discriminant Value

Discriminant validity refers to the degree to which a construct is genuinely distinct from other constructs based on empirical criteria. (a) Square Roots of Average Variance Extraction (AVEs) Discriminant validity is assessed by comparing the square roots of the Average Variance Extracted (AVE) for each construct with the correlations between that construct and others in the model. If the square root of the AVE for each construct exceeds the correlation values with other constructs, it indicates strong discriminant validity. (b) Average Variance Extracted (AVE) Discriminant validity also involves the Average Variance Extracted (AVE). If the AVE value for a construct is greater than 0.50, it suggests that the variable demonstrates good discriminant validity.

Source: Discriminant value of variables

The above output shows the results of the discriminant analysis. A simple linear discriminant function was used by weighting the independent variables (Brand Image, Brand Popularity, Product Price) based on their respective values. The overall discriminant value is 0.5756, and the table displays each variable's raw value, their normalized weights, and contribution to the overall value. Two visualizations are provided: a horizontal bar chart illustrating the percentage contribution of each variable, and a pie chart showing the proportion of contributions.

R-Square

The inner model, also known as the inner relation, structural model, or substantive theory, outlines the connections between latent variables grounded in substantive theory. The evaluation of the structural model is conducted using R-squared for the dependent construct. The R² value serves as a measure to determine the impact of specific endogenous and exogenous variables, indicating whether they exert a significant effect (Ghozali, 2014).

Table 4: Rsquare Adjustment

Based on Table 4 above, Rsquare value os 0.697 this means that 69.6% of variations or changes in purchasing decisions are influenced by BI, BP and PP, while the remaining 30.4%.

Structural Model-Test

According to the researcher Ghozali and Latan (2015:78), structural-model testing done by seeing the relationship between constructs.

Source: Author Data

To establish the structural relationship between latent variables, hypothesis testing should be conducted on the path coefficients by comparing the p-value with the significance level (alpha) of 0.1 or a t-statistic greater than 1.66. Both the p-value and t-statistic are derived from the output generated in Smart-PLS using the bootstrapping method.

Based on the structural model, we see the following influences:

Brand Image (BI) (H1): For Delhi, the t-statistic (1.397) is below the threshold (1.65) and the p-value (0.164) indicates that brand image does not significantly affect purchasing decisions for skincare products among millennials and gen-z.

Brand Popularity (BP) (H2): For Delhi, the t-statistic (4.238) with a p-value of 0.000 indicates that brand popularity has a strong, positive, and significant impact on purchasing decisions.

Product Price (PP) (H3): For Delhi, the t-statistic (2.247) with a p-value of 0.025 suggests that price positively and significantly influences purchasing decisions.

• The Effect of Brand Popularity (BP) on Purchasing Decisions- The brand name plays a crucial role in conveying product value to consumers, thereby influencing their purchasing decisions. Understanding the impact of brand names on product success is essential for companies to develop effective marketing strategies. This study reveals that brand popularity significantly affects purchasing decisions for skincare products among millennials and Gen-Z in Delhi NCR. The statistical analysis shows a t-statistic of 4.238, which is greater than 1.66, and a p-value of 0.000, indicating that brand popularity has a positive and statistically significant influence on these consumer groups.
• The Effect of Product Price (PP) on Purchasing Decisions – According to Kotler and Armstrong (2018), there is a direct relationship between price and purchasing decisions, where price significantly influences consumer behavior. Higher prices tend to reduce purchasing decisions, while lower prices increase them. This study demonstrates that product prices have a positive and significant impact on purchasing decisions for skincare products among millennials and Gen-Z in Delhi NCR. The statistical analysis reveals a t-statistic value of 2.247, exceeding the threshold of 1.66, and a p-value of 0.025, confirming the significant effect of product pricing on consumer choices.

• The Effect of Brand Image (BI) on Purchasing Decisions - Brand image is typically considered a key factor influencing purchasing decisions among potential consumers, often supported by high-quality products. Companies strive to offer the best options to attract consumers, as they compete to provide superior value. However, the findings of this study reveal that brand image does not significantly impact purchasing decisions for skincare products among millennials and Gen-Z in Delhi NCR. The statistical analysis shows a t-statistic value of 1.397, which is less than the threshold of 1.66, and a p-value of 0.163, indicating that brand image does not have a significant effect on consumer choices in this demographic.

• The Effect of Brand Popularity (BP), Product Price (PP), Brand Image (BI) on Purchasing Decisions - Purchasing decisions represent the final step in the consumer decision-making process, where a consumer decides to buy a product or service based on specific considerations. These decisions reflect the effectiveness of marketers in promoting their products to consumers. In this study, the influence of various factors on purchasing decisions was analyzed: Brand Image (BI) contributed 15% (0.150) to purchasing decisions where as the Brand Popularity (BP) had a significant impact, accounting for 48.5% (0.485) of purchasing decisions and Product Price (PP) influenced purchasing decisions by 22.6% (0.226). The overall R Square value was found to be 0.697, indicating that 69.7% of the variations in purchasing decisions are explained by these three variables—brand image, brand popularity, and product price—while the remaining 30.3% is attributed to other factors not included in the study. This R Square value suggests that the model has a moderate explanatory power for purchasing decisions.

Based on the research findings and discussions, the following conclusions can be drawn regarding the influence of brand image, brand popularity, and product price on purchasing decisions for skincare products among millennials and Gen-Z in Delhi NCR:

a.  Brand Image (BI)

Brand image does not have a significant positive effect on purchasing decisions for skincare products among millennials and Gen-Z in Delhi NCR. This suggests that while brand image is often considered important in marketing, it may not be a decisive factor for this demographic when choosing skincare products. This could be due to other factors such as product efficacy, price, or brand popularity playing a more significant role.

b.  Brand Popularity (BP)

Brand popularity has a positive and significant impact on purchasing decisions for skincare products among millennials and Gen-Z in Delhi NCR. This indicates that well-known and popular brands are more likely to influence consumer choices in this demographic. The influence of brand popularity could be attributed to social media, celebrity endorsements, or word-of-mouth recommendations that enhance the brand's appeal.

c.  Product Price (PP)

Product prices also have a positive and significant effect on purchasing decisions for skincare products among millennials and Gen-Z in Delhi NCR. This might seem counterintuitive since higher prices often deter purchases. However, in the context of this study, it could suggest that consumers perceive higher-priced skincare products as being of better quality or more effective, thus influencing their purchasing decisions positively.

Combined Effect of Brand Image (BI), Brand Popularity (BP), and Product Price (PP) Collectively, brand image, brand popularity, and product price have a positive and significant impact on purchasing decisions for skincare products among millennials and Gen-Z in Delhi NCR. Although brand image individually does not have a significant effect, when combined with brand popularity and product price, it contributes to a broader influence on consumer choices. This suggests that while individual factors may have varying impacts, their combined effect is substantial in shaping purchasing decisions.

Overall, these findings highlight the importance of brand popularity and product price in influencing skincare purchasing decisions among millennials and Gen-Z in Delhi NCR, while brand image plays a less significant role individually but contributes when considered alongside other factors.

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