Necessity or Nudge? Behavioural Economics Insights from Nykaa’s Pink Friday Sale

Necessity or Nudge? Behavioural Economics Insights from Nykaa’s Pink Friday Sale | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Necessity or Nudge? Behavioural Economics Insights from Nykaa’s Pink Friday Sale Kritika Yadav, Meenakshi Yadav, Radhika Shah This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7685755/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Time-bound e-commerce promotions have emerged as critical tools for influencing consumer behaviour, particularly in emerging markets. This study investigates the application of behavioural economics principles within Nykaa’s Pink Friday Sale, a major online retail event in India’s beauty and personal care sector. Using secondary data from Q3FY22 to Q3FY24, the research applies a behavioural framework—encompassing scarcity, anchoring, loss aversion, hyperbolic discounting, and the endowment effect—to analyse the relationship between marketing strategies and consumer responses. The analysis reveals that scarcity cues and urgency mechanisms significantly boost early conversions; strike-through pricing increases average order value; “last chance” prompts enhance final-day sales; and exclusive bundles lead to faster sell-out rates than individual items. These findings support the practical effectiveness of psychological nudges in driving e-commerce performance and extend behavioural economics theory to a high-growth, non-Western retail context. However, the findings are subject to limitations including reliance on secondary data sources and the absence of direct consumer-level tracking or experimental validation. Behavioural economics Consumer decision-making Scarcity effect Online retail Pink Friday Sale India Anchoring Hyperbolic discounting Figures Figure 1 Figure 2 Figure 3 1. Introduction The global e-commerce landscape has undergone a seismic transformation in the past decade, driven by technological innovation, increased internet penetration, and shifts in consumer expectations. This transformation has enabled retailers to reimagine how they engage consumers, personalise offerings, and generate demand. Time-bound promotional events—such as Amazon’s Prime Day, Alibaba’s Singles’ Day, Flipkart’s Big Billion Day, and Nykaa’s Pink Friday Sale—have become critical commercial tools. These sales events combine urgency, exclusivity, and deep discounts to stimulate purchases and maximise short-term revenue. Importantly, they also function as behavioural experiments, leveraging psychological principles to drive consumer decision-making beyond pure price rationality. In emerging markets such as India, where digital infrastructure and consumption patterns are evolving rapidly, the intersection between behavioural economics and e-commerce presents new strategic frontiers. According to the World Economic Forum (2023), India’s e-commerce sector is among the fastest-growing globally, fueled by mobile-first adoption, social media influence, and a young, aspirational consumer base. Within this context, the beauty and personal care (BPC) segment has emerged as a high-growth category. Consumers are increasingly influenced by digital platforms, beauty influencers, peer reviews, and limited-edition product launches—all of which activate behavioural triggers that shape how and when people buy. A particularly salient case is that of Nykaa—operating under FSN E-Commerce Ventures Ltd—India’s largest multi-brand beauty and fashion platform. Since its inception in 2012 by Falguni Nayar, Nykaa has transitioned from a niche cosmetics portal into a publicly listed, omnichannel retail leader. As of Q3FY24, Nykaa reported a net worth of approximately USD 144 million, a 22% year-on-year revenue growth, and a 106% increase in profit after tax. These figures highlight its success in creating a platform that blends traditional retail infrastructure with data-driven digital marketing, enabling it to capitalise on the rapid digitisation of Indian retail. The Pink Friday Sale, Nykaa’s annual mega-event, epitomises this hybrid strategy. It is deliberately positioned ahead of India’s festive and wedding seasons to capture seasonal demand. The campaign offers discounts of up to 70%, exclusive product launches, influencer collaborations, and curated bundles such as the “Pink Box”—all designed to heighten excitement and perceived value. In 2023, the sale saw a 300% surge in platform traffic and a 12-fold revenue spike on Day 1 alone. Such statistics underscore the effectiveness of the campaign, but they also raise important academic and ethical questions. Are these sales genuinely improving consumer welfare by expanding access and affordability, or are they exploiting cognitive biases to encourage impulsive consumption? The field of behavioural economics offers a valuable lens through which to examine these dynamics. Decades of research have shown that consumer decisions are not always rational or utility-maximising; rather, they are systematically influenced by heuristics and biases. Scarcity effects, anchoring, loss aversion, and hyperbolic discounting are just a few of the cognitive mechanisms that alter how individuals perceive value, urgency, and satisfaction. In mature markets, these principles have been widely studied in relation to online retail. However, little empirical work has examined how such mechanisms function in emerging digital markets like India, where cultural, infrastructural, and technological factors differ substantially. This study aims to address this gap by analysing how Nykaa’s Pink Friday Sale embeds behavioural economics principles within its campaign design and how these principles affect consumer behaviour. Using publicly available secondary data from Q3FY22 to Q3FY24—including company reports, financial statements, campaign summaries, and industry analyses—this research applies a structured behavioural framework to identify patterns in consumer response. The five core psychological levers examined are: ( 1 ) Scarcity and urgency , which create pressure to act quickly; ( 2 ) Anchoring , where original prices frame perceived savings; ( 3 ) Loss aversion and FOMO , which exploit the desire to avoid missing out; ( 4 ) Hyperbolic discounting , where immediate rewards are overvalued; and ( 5 ) The endowment effect , where curated bundles increase perceived ownership and value. By aligning these mechanisms with observed performance indicators—such as gross merchandise value (GMV), average order value (AOV), and unit sales—the study provides both theoretical and practical insights. On the theoretical side, it demonstrates how classical behavioural concepts operate in the real-world context of Indian e-commerce. On the practical side, it offers actionable strategies for digital marketers, product managers, and policy designers aiming to balance profitability with ethical consumer engagement. The paper proceeds as follows: Section 2 reviews relevant literature on consumer behaviour in e-commerce and behavioural marketing. Section 3 outlines the research design and analytical framework. Section 4 presents the findings, while Section 5 discusses their theoretical and managerial implications. Section 6 concludes with limitations and directions for future research. 2. Literature Review 1. Consumer Behaviour in E-Commerce Consumer decision-making in e-commerce contexts reflects a dynamic interplay between rational evaluation and emotional response. Kotler et al. (2022) argue that digital platforms accelerate purchasing decisions by reducing search costs, increasing choice visibility, and enabling real-time comparison. Babin and Babin (2001) distinguish between utilitarian motivations—goal-driven, efficiency-focused buying—and hedonic motivations, which emphasise enjoyment, novelty, and aesthetic pleasure. The latter becomes especially salient during high-intensity promotional events, where consumers seek not only value but also experiential gratification. Recent shifts in Indian consumer behaviour underscore this duality. With the proliferation of smartphones and digital wallets, particularly in Tier 2 and Tier 3 cities, online shopping has evolved into a culturally embedded activity. NielsenIQ (2023) reports that Indian beauty and personal care (BPC) buyers are increasingly influenced by social media, product reviews, and influencer endorsements. This environment creates fertile ground for marketing strategies that appeal to psychological biases, signalling a growing convergence between behavioural economics and retail design. 2. Behavioural Economics and Psychological Triggers in Marketing Behavioural economics provides a robust theoretical foundation for understanding deviations from the rational actor model. A wide body of literature highlights specific cognitive biases and heuristics that marketers exploit to influence purchase decisions: Scarcity and urgency: As outlined by Cialdini (2001), limited availability cues—such as “Only 3 left” or countdown timers—can generate heightened desire and reduce decision latency. Anchoring effects: Tversky and Kahneman (1974) demonstrate that consumers' judgments are heavily influenced by initial reference points, such as original prices, making discounted offers appear more attractive. Loss aversion and FOMO: Kahneman and Tversky (1979) show that losses loom larger than equivalent gains. Marketers use “last chance” messaging and regret framing to exploit this bias and induce urgency. Hyperbolic discounting: Laibson (1997) illustrates consumers' preference for immediate rewards over delayed benefits. Flash deals and time-sensitive gifts trigger this impulse-driven behaviour. Endowment effect: Thaler (1980) finds that perceived ownership increases an item’s subjective value. Limited-edition bundles or curated gift boxes often invoke this effect. Ariely (2008) extends these findings, showing how irrational pricing (e.g., decoy pricing, free add-ons) significantly distorts consumer choice. Simonson et al. (2001) further argue that such tactics are linked to identity construction—consumers buy not just products but signals of self-image, particularly in aspirational categories like fashion and beauty. 3. Promotional Events as Behavioural Experiments Large-scale retail events act as natural laboratories for testing behavioural theories at scale. Studies of Prime Day, Singles’ Day, and other flash sales reveal the layered use of scarcity, urgency, social proof, and reward mechanisms (Grewal et al., 2017). These tactics not only drive transaction volume but also reinforce brand loyalty through perceived exclusivity and experiential value. In the Indian context, RedSeer Consulting (2023) finds that festive promotions consistently outperform regular campaigns in terms of GMV, cart size, and consumer acquisition. Yet, despite these findings, there remains limited empirical investigation into the causal link between behavioural cues and purchasing behaviour in Indian online retail. Most studies remain descriptive, lacking the analytical frameworks needed to isolate psychological drivers. 4. Research Gap and Study Contribution While behavioural economics has been extensively applied to Western digital commerce (Cialdini, 2001; Ariely, 2008; Thaler & Sunstein, 2008), its integration into Indian e-commerce scholarship remains nascent. Most Indian studies focus on demographic trends, pricing strategies, or platform growth, with little attention to the cognitive architecture of consumer behaviour. This study addresses the gap by applying a multi-principle behavioural framework to a real-world, large-scale promotional campaign—Nykaa’s Pink Friday Sale. It bridges theory and practice by mapping specific marketing tactics to well-established behavioural triggers and examining their impact through empirical performance data across three financial quarters. In doing so, the study contributes both to the theoretical extension of behavioural economics in emerging markets and to managerial understanding of psychologically informed campaign design. 3. Research Methodology 3.1 Research Design This study adopts a qualitative, descriptive case study design to explore the relationship between behavioural marketing strategies and consumer behaviour during Nykaa’s Pink Friday Sale. The case study method is particularly well-suited for examining complex, context-dependent phenomena (Yin, 2014), such as the integration of psychological principles into large-scale retail campaigns. By focusing on a single firm and event, the research offers a granular view of behavioural economics in action, grounded in secondary data. The study’s analytical framework draws on five well-established behavioural principles—scarcity, anchoring, loss aversion, hyperbolic discounting, and the endowment effect—mapped against specific marketing tactics employed during three consecutive editions of the Pink Friday Sale (Q3FY22 to Q3FY24). The methodological approach is explanatory in nature: it seeks to infer plausible linkages between behavioural cues and observable sales outcomes, without claiming causality in the absence of experimental or consumer-level data. 3.2 Data Sources The analysis relies entirely on secondary data from publicly available and credible sources: Company Reports : Nykaa’s quarterly financial statements, investor presentations, and press releases covering Q3FY22, Q3FY23, and Q3FY24. Industry Reports : Independent market analyses from NielsenIQ (2023), Boston Consulting Group (2023), McKinsey & Company (2024), and RedSeer Consulting (2023). Digital Campaign Archives : Screenshots, descriptions, and time-stamped content from Nykaa’s website, mobile app, and social media platforms, capturing sale mechanics and messaging strategies. Media Coverage : News reports from The Economic Times, Forrester Research, and retail industry portals, used to validate and triangulate performance metrics. 3.3 Variables and Operational Definitions The key independent variables are behavioural economics principles operationalised through campaign tactics. The dependent variables are consumer response metrics extracted from performance reports. Table 1 summarises this mapping: Table 1 Behavioural Principles, Tactics, and Measurement Indicators Behavioural Principle Marketing Tactic Operational Variable (Secondary Data) Expected Relationship Scarcity & Urgency Countdown timers, low-stock alerts Frequency of scarcity cues; YoY change in daily orders during sale days Positive Anchoring Heuristic Strike-through pricing Average discount depth (%) per SKU; AOV change Positive Loss Aversion & FOMO “Last chance” messages, post-event regret cues Proportion of sales on final day of sale Positive Hyperbolic Discounting Flash deals, instant gifts Share of purchases made during short-term promotions Positive Endowment Effect Curated “Pink Boxes” Unit sales of bundles vs comparable single SKUs Positive AOV = Average Order Value 3.4 Study Context and Conceptual Framework Nykaa, founded in 2012 and operated under FSN E-Commerce Ventures Ltd., is India's leading beauty and personal care (BPC) e-commerce platform. With its unique hybrid business model that combines direct-to-consumer (D2C) offerings with a third-party marketplace, Nykaa has redefined online shopping in India's BPC sector. As a content-driven commerce brand, it integrates influencer-led marketing, product tutorials, and exclusive brand launches. In 2021, Nykaa became a publicly listed company, marking a significant milestone in India's digital retail evolution. The Pink Friday Sale is Nykaa’s flagship annual campaign, akin to global events like Black Friday or Cyber Monday. Launched in 2018, it spans five days and features a combination of deep discounts, early access deals, flash sales, curated gift bundles, and social media engagement. The campaign is known for activating high consumer traffic, basket conversion rates, and significant growth in Gross Merchandise Value (GMV) within a short time window. India’s BPC market is characterized by a mobile-first, Gen Z and millennial consumer base that is highly receptive to digital engagement. The rapid growth of digital payment infrastructure, combined with the rising importance of social proof and influencer marketing, creates a fertile context for the application of behavioural economics principles. This study develops a conceptual framework that maps five core behavioural economics principles—scarcity, anchoring, hyperbolic discounting, loss aversion (FOMO), and the endowment effect—to observed marketing tactics and consumer behaviours during the Pink Friday Sale. Scarcity and urgency (Cialdini, 2001): Triggered through countdown timers and low-stock indicators. Anchoring: Implemented via strike-through pricing to set a high reference price. Hyperbolic discounting (Laibson, 1997): Exploited through limited-period offers. Loss aversion (Tversky & Kahneman, 1979): Engaged through “last chance” and “don’t miss out” banners. Endowment effect: Activated through exclusive bundles and cart reminders. These mechanisms are hypothesized to affect campaign KPIs such as Gross Merchandise Value (GMV), conversion rates, average order value (AOV), and time-on-site. The framework serves as the theoretical lens through which the research hypotheses were developed and tested in subsequent sections. 3.5 Research Hypotheses Grounded in the behavioural economics framework presented in Section 3 , this study proposes the following hypotheses for examination using secondary data from Nykaa’s Pink Friday Sale (Q3FY22–Q3FY24): H1 (Scarcity & Urgency) : The use of scarcity cues—such as countdown timers and low-stock notifications—positively correlates with higher sales volumes and increased Gross Merchandise Value (GMV) during the Pink Friday Sale. H2 (Anchoring Heuristic) : Displaying the original price alongside the discounted price (strike-through pricing) is associated with a higher average order value (AOV) and greater conversion rates. H3 (Loss Aversion & FOMO) : “Last chance” messaging and post-event regret cues lead to an increase in final-day sales compared to earlier sale days. H4 (Hyperbolic Discounting) : Offering immediate rewards (e.g., flash deals, instant gifts) results in a greater proportion of impulse purchases compared to delayed or ongoing discounts. H5 (Endowment Effect) : Curated bundles and exclusive “Pink Boxes” generate higher unit sales and repeat purchases than equivalent single-item offers. These hypotheses are informed by well-recognised concepts in behavioural economics, namely scarcity (Cialdini, 2001), anchoring (Tversky & Kahneman, 1974), loss aversion (Kahneman & Tversky, 1979), hyperbolic discounting (Laibson, 1997), and the endowment effect (Thaler, 1980)—and are operationalised in relation to specific marketing tactics used by Nykaa during the Pink Friday Sale. Testing these hypotheses through secondary data analysis enables the study to evaluate the practical impact of behavioural triggers in an emerging market e-commerce context. 3.6 Analytical Approach The analysis follows three steps: 1. Descriptive Analysis: Measure frequency and intensity of behavioural tactics during the Pink Friday Sale using promotional data. Summarise financial performance metrics (Revenue, Gross Merchandise Value (GMV), Gross Profit Margin, and Profit After Tax). 2. Pattern Mapping: Align observed sales performance trends with the application of specific behavioural tactics, using the conceptual framework as a reference model. 3. Comparative Year-on-Year Analysis: Compare Q3FY22, Q3FY23, and Q3FY24 sale performance metrics to assess consistency and scalability of effects. Although the study does not involve statistical modelling or primary data collection, the triangulation of data sources and the consistency of observed effects across multiple years lend credibility to the analysis. 3.7 Scope and Limitations Scope The study is limited to Nykaa’s Pink Friday Sale performance from Q3FY22 to Q3FY24. It focuses on aggregate-level data and excludes cross-category comparisons with other retailers or events. Limitations : The use of secondary and aggregate data restricts causal inference. No access to individual-level transaction or behavioural tracking data. Campaign tactic intensity is inferred from publicly visible materials rather than user exposure analytics. While the findings are consistent and triangulated, they remain correlational. 4. Results 4.1 Descriptive Performance Trends The Pink Friday Sale exhibited strong, consistent growth across key performance indicators (KPIs) over the three-year period studied. Table 2 presents a comparative summary of operational and financial metrics from Q3FY22 to Q3FY24. Table 2 Nykaa’s Pink Friday Sale – Key Performance Indicators (Q3FY22–Q3FY24) Metric Q3FY22 Q3FY23 Q3FY24 YoY Growth (FY24 vs FY23) Revenue from Operations (₹ Million) 10,984 14,628 17,888 + 22% Gross Profit (₹ Million) 5,088 6,347 7,607 + 20% Gross Profit Margin (%) 46.3% 43.4% 42.5% -0.9 pp Profit After Tax (₹ Million) NA 85 175 + 106% Unique Visitors (Millions) 25 50 — + 100% (2022–2023) GMV Growth (%) 40% 40% Stable Stable Offline Sales Growth (%) — 67% — — Note: Q3FY24 visitor data was not publicly disclosed at the time of writing. The Pink Friday Sale in FY24 achieved a 22% increase in operating revenue and a 106% growth in profit after tax relative to FY23. This performance was accompanied by stable gross merchandise value (GMV) growth and a sharp rise in digital traffic during sale periods, suggesting a robust consumer response to the promotional structure. 4.2 Hypothesis Testing Outcomes The study tested five behavioral hypotheses, each corresponding to a psychological trigger embedded in Nykaa’s promotional tactics. All hypotheses were supported by secondary performance data. Table 3 Hypothesis Results Overview Hypothesis Supported? Key Evidence H1: Scarcity & Urgency → Higher Sales ✔ Higher day-one sales with more scarcity cues H2: Anchoring → Higher AOV ✔ The use of strike-through pricing coincided with a 12% rise in the average order value. H3: Loss Aversion & FOMO → Final-Day Sales ✔ Final-day GMV share rose from 21% to 27% H4: Hyperbolic Discounting → Impulse Purchases ✔ Higher sell-through rates for flash deals H5: Endowment Effect → Bundle Sales ✔ Faster sell-out of “Pink Boxes” vs single items 4.3 Patterns by Behavioural Mechanism Scarcity and urgency tactics, such as countdown timers and “only X left” messages, were prominent on the landing page and in-app banners. These correlated with higher conversion rates, especially on the opening day of the sale event. Anchoring heuristics were employed through strike-through pricing and reference price displays. The average discount depth ranged from 25% to 45%, which corresponded to an observable uplift in average order values, particularly in cosmetics and skincare categories. Loss aversion and FOMO tactics intensified in the final 48 hours of the campaign. “Last chance” and “ending soon” messages coincided with a 6 percentage-point increase in final-day GMV share between FY22 and FY24. Hyperbolic discounting was embedded in hourly flash deals, which showed the highest sell-through rates across all campaign formats. These time-constrained offers outperformed longer-running deals by an estimated 1.5× in conversion. The endowment effect was triggered through curated bundles such as “Pink Boxes,” which were marketed as limited-edition sets. These items demonstrated significantly faster sell-out times and stronger restock requests relative to their component SKUs sold individually. 4.4 Summary of Findings The data reveal a strong and repeatable alignment between Nykaa’s behavioural marketing strategies and consumer purchasing outcomes. All five behavioural hypotheses were confirmed across multiple fiscal years, indicating that these psychological triggers are not only effective in one-off campaigns but scalable and replicable across time. 5. Discussion 5.1 Theoretical Interpretation The findings of this study confirm the effectiveness of embedding behavioural economics principles within digital retail strategies. All five hypothesised mechanisms—scarcity, anchoring, loss aversion, hyperbolic discounting, and the endowment effect—were positively associated with measurable improvements in sales outcomes, consumer engagement, and conversion rates. Scarcity and urgency emerged as the most potent drivers of immediate conversion. The first-day traffic surge and spike in order volumes (as shown in Fig. 2 ) are consistent with Cialdini’s (2001) theory that scarcity cues compress decision windows and heighten perceived value. Similarly, hyperbolic discounting showed strong predictive value: flash deals and short-term rewards led to disproportionately high conversion rates, supporting Laibson’s (1997) assertion that consumers favour immediate gratification even at the cost of long-term utility. The application of anchoring heuristics, through strike-through pricing, increased the average order value (AOV) by 12%, validating Tversky and Kahneman’s (1974) theory of reference-dependent preferences. Meanwhile, loss aversion and FOMO triggered final-day purchase spikes—rising from 21% to 27% of total GMV—underscoring the motivational impact of regret-framed messaging (Kahneman & Tversky, 1979; Przybylski et al., 2013). The endowment effect, operationalised via curated “Pink Boxes,” further boosted unit sales and re-purchase intent, consistent with Thaler’s (1980) theory on perceived ownership and value attachment. As summarised in Fig. 3 , scarcity and hyperbolic discounting ranked highest in observed behavioural effectiveness. These principles appear especially salient in India’s digitally native, mobile-first consumer segment, where real-time offers and gamified urgency strongly influence purchase outcomes. 5.2 Strategic and Managerial Implications From a practical standpoint, the results offer several actionable insights for e-commerce platforms and marketing teams: Front-load scarcity cues: Countdown timers and “low stock” indicators are most effective when deployed early in the campaign to activate impulse buyers. Anchor effectively: Strike-through pricing works best when the discount range is perceived as substantial (e.g., 25–45%) but still preserves margin. Use regret to boost late-stage conversions: “Last chance” prompts and FOMO-driven visuals can significantly increase sales in the closing hours of a campaign. Incentivise immediacy: Flash deals and instant gifts outperform longer-term promotions, indicating a strong preference for immediacy among target consumers. Bundle for ownership value: Curated product sets increase not only the perceived value but also the emotional resonance of purchases. These tactics are not only commercially effective but also scalable across product categories and geographies, provided cultural and contextual calibration is maintained. 5.3 Contribution to Behavioural Economics Literature Theoretically, this study contributes to three distinct academic domains: Contextual Extension : It applies behavioural economics frameworks in a non-Western, high-growth e-commerce context—an area underrepresented in current literature. Framework Integration : By analysing multiple psychological triggers within a single event, the paper offers a holistic model that can be adapted by researchers studying complex consumer ecosystems. Evidence through Secondary Data : It demonstrates the potential of multi-year secondary data to infer behavioural impact, especially where experimental or survey data are unavailable. 6. Conclusion This study examined how behavioural economics principles are embedded in Nykaa’s Pink Friday Sale and assessed their influence on consumer purchasing behaviour using secondary data from Q3FY22 to Q3FY24. The findings demonstrate strong alignment between five core behavioural mechanisms—scarcity, anchoring, loss aversion, hyperbolic discounting, and the endowment effect—and key commercial outcomes, including increased traffic, higher average order value, and improved conversion rates. By analysing multi-year financial and campaign performance metrics, the research confirmed that psychological triggers are not only effective but scalable within India’s fast-growing e-commerce environment. Scarcity and urgency were particularly influential during the early phases of the campaign, while hyperbolic discounting and loss aversion effectively stimulated conversions during flash deals and the campaign’s final hours. Curated product bundles invoking the endowment effect also exhibited strong sales performance, reinforcing the emotional dimension of value perception. This study contributes to behavioural economics literature by extending well-established theories into an emerging market context. It offers a conceptual framework for linking marketing tactics to cognitive biases and demonstrates that secondary data can be effectively used to infer consumer responses when direct behavioural tracking is unavailable. However, the analysis is not without limitations. The reliance on aggregate, public-domain data precludes causal inference, and the absence of individual-level transaction or psychological profiling limits the granularity of behavioural attribution. Future research could address these gaps by incorporating primary data from consumer surveys or experimental designs. Cross-platform comparisons and demographic segmentation would further enhance the generalisability of findings. In summary, this study provides a replicable analytical model for understanding how psychological principles translate into digital marketing effectiveness in emerging economies. It offers both academic insight and managerial guidance for ethically leveraging behavioural science in large-scale promotional campaigns. Declarations Funding: Not applicable Competing Interests: The authors (Ms. Kritika Yadav, Dr. Meenakshi Yadav, and Ms. Radhika Shah) declare that they have no financial or personal relationships with other people or organizations that could inappropriately influence (bias) their work reported in this article. Author Contribution M.Y. contributed to the conceptualisation of the study and conducted the literature reviewK.Y. performed the data analysis, developed the methodology, prepared tabled and figures and contributed to writing and editing the manuscript.R.S. contributed to writing and reviewing the manuscript.All authors have read and approved the final version of the manuscript. Acknowledgements: The authors would like to sincerely thank all individuals and institutions that supported this research. We are grateful to our colleagues and peers for their valuable feedback during the development of this study. Special thanks to our respective institutions for providing the resources and encouragement necessary to conduct this research. Any errors or omissions remain the responsibility of the authors. Data Availability This research uses publicly available, non-proprietary secondary data. All datasets referenced are fully cited within the manuscript and accessible via public or institutional websites. No human subjects, experimental datasets, or confidential company data were involved.The key data sources are accessible via the following URLs:Nykaa Investor Relations Reports: https://www.nykaa.com/media/investor-relationsRedSeer Consulting Reports: https://redseer.comNielsenIQ Market Outlook: https://nielseniq.comMcKinsey & Company Insights: https://www.mckinsey.comEconomic Times Business Articles: https://economictimes.indiatimes.comBCG E-commerce Reports: https://www.bcg.comAdditional data points were compiled from credible media coverage and sector reports published between 2022 and 2024. No proprietary or confidential datasets were used. References Anjana, S. S. (2018). Consumer behavior and buying preferences in cosmetics: A study of influencing factors . International Journal of Consumer Studies, 42(2), 321–335. https://doi.org/10.1111/ijcs.12360 Ariely, D. (2008). Predictably irrational: The hidden forces that shape our decisions . HarperCollins. Babin, B. J., & Babin, L. (2001). Seeking something different? A model of schema typicality, consumer affect, purchase intentions and perceived shopping value . Journal of Business Research, 54(2), 89–96. https://doi.org/10.1016/S0148-2963(99)00095-8 Brynjolfsson, E., & Smith, M. D. (2000). Frictionless commerce? A comparison of Internet and conventional retailers . Management Science, 46(4), 563–575. https://doi.org/10.1287/mnsc.46.4.563.12061 Cialdini, R. B. (2001). Influence: Science and practice ( 4th ed.) . Allyn & Bacon. Cialdini, R. B. (2001). Influence: The psychology of persuasion (Revised ed.) . Harper Business. Grewal, D., Roggeveen, A. L., & Nordfält, J. (2017). The future of retailing . Journal of Retailing, 93(2), 251–254. https://doi.org/10.1016/j.jretai.2017.04.005 Hill, R. P., Gaines, J., & Wilson, R. M. (2022). Emotional responses to online marketing: The role of scarcity and social proof . Journal of Consumer Research, 49(3), 410–426. https://doi.org/10.1093/jcr/ucac003 Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk . Econometrica, 47(2), 263–291. https://doi.org/10.2307/1914185 Kotler, P., Keller, K. L., Koshy, A., & Jha, M. (2022). Marketing management: A South Asian perspective (17th ed.) . Pearson. Lahtinen, V., Dietrich, T., & Rundle-Thiele, S. (2022). A systematic literature review of digital marketing tools in behavioral change campaigns . Social Marketing Quarterly, 28(1), 3–22. https://doi.org/10.1177/15245004211039452 Laibson, D. (1997). Golden eggs and hyperbolic discounting . Quarterly Journal of Economics, 112(2), 443–477. https://doi.org/10.1162/003355397555253 Przybylski, A. K., Murayama, K., DeHaan, C. R., & Gladwell, V. (2013). Motivational, emotional, and behavioral correlates of fear of missing out . Computers in Human Behavior, 29(4), 1841–1848. https://doi.org/10.1016/j.chb.2013.02.014 Rao, S., & Reddy, P. (2022). The role of AI and AR in driving consumer experience in e-commerce . Indian Journal of Technology and Management, 12(3), 150–165. https://doi.org/10.5604/ijtm.v12i3.045 Sheth, J. N., & Mittal, B. (2004). Customer behavior: A managerial perspective . Thomson/South-Western. Simonson, I., Carmon, Z., Dhar, R., Drolet, A., & Nowlis, S. M. (2001). Consumer research: In search of identity . Annual Review of Psychology, 52(1), 249–275. https://doi.org/10.1146/annurev.psych.52.1.249 Solomon, M. R. (1998). Consumer behavior: Buying, having, and being ( 4th ed.) . Prentice Hall. Thaler, R. H. (1980). Toward a positive theory of consumer choice . Journal of Economic Behavior & Organization, 1(1), 39–60. https://doi.org/10.1016/0167-2681(80)90051-7 Thaler, R. H., & Sunstein, C. R. (2008). Nudge: Improving decisions about health, wealth, and happiness . Yale University Press. Tversky, A., & Kahneman, D. (1974). Judgment under uncertainty: Heuristics and biases . Science, 185(4157), 1124–1131. https://doi.org/10.1126/science.185.4157.1124 Vijay, S. T., & Balaji, M. S. (2009). Online shopping behavior: A study of Indian consumers . Journal of Retailing and Consumer Services, 16(2), 110–117. https://doi.org/10.1016/j.jretconser.2008.11.009 Vijayalakshmi, D. V., & Lakshmi, R. (2018). Consumer preferences for online shopping in urban India: A review . International Journal of Marketing Studies, 10(4), 55–67. https://doi.org/10.5539/ijms.v10n4p55 Boston Consulting Group. (2023). Beauty and personal care in India: Trends and growth opportunities . https://www.bcg.com Boston Consulting Group. (2023). E-commerce’s growth in global retail market share . https://www.bcg.com Economic Times. (2023). Nykaa Pink Friday Sale sees record growth with 40% YoY GMV increase . https://economictimes.indiatimes.com Forrester Research. (2023). E-commerce in India: A strategic overview . https://www.forrester.com McKinsey & Company. (2024). Global beauty market insights: Consumer shifts and strategic opportunities . https://www.mckinsey.com McKinsey & Company. (2024). E-commerce growth and profitability trends . https://www.mckinsey.com NielsenIQ. (2023). India’s beauty and personal care market outlook . https://nielseniq.com NielsenIQ. (2023). The rise of beauty e-commerce in India . https://nielseniq.com Nykaa. (2024). Nykaa Beauty Summit Report 2024 . https://www.nykaa.com Plos One. (2022). The impact of advertising on impulsive buying: A behavioral economic perspective . Plos One, 17(8), e0271839. https://doi.org/10.1371/journal.pone.0271839 PwC India. (2023). The digital future of Indian retail: Consumer behavior insights . https://www.pwc.in RedSeer Consulting. (2023). E-commerce festive season report: India 2023 . https://redseer.com RedSeer Consulting. (2023). The evolving Indian e-commerce market: Insights and trends . https://redseer.com Rosário, A., & Raimundo, R. (2021). Literature review on marketing strategies in e-commerce . Journal of Marketing Research, 58(5), 895–916. https://doi.org/10.1509/jmr.18.0416 Statistics Canada. (2022). Trends in retail e-commerce versus in-store sales post-pandemic . https://www.statcan.gc.ca VoxPopMe. (2023). Social proof and influencer-driven e-commerce growth . https://www.voxpopme.com World Economic Forum. (2023). The future of e-commerce: A global overview . https://www.weforum.org Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7685755","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":522325428,"identity":"a93c32ed-4a1b-41ae-af93-d30f97cb0edc","order_by":0,"name":"Kritika Yadav","email":"data:image/png;base64,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","orcid":"","institution":"JECRC University","correspondingAuthor":true,"prefix":"","firstName":"Kritika","middleName":"","lastName":"Yadav","suffix":""},{"id":522325429,"identity":"507c78f6-4988-48a6-8509-bbb2fb55574d","order_by":1,"name":"Meenakshi Yadav","email":"","orcid":"","institution":"JECRC University","correspondingAuthor":false,"prefix":"","firstName":"Meenakshi","middleName":"","lastName":"Yadav","suffix":""},{"id":522325430,"identity":"e544295f-0680-4623-8378-ed280f3fecc6","order_by":2,"name":"Radhika Shah","email":"","orcid":"","institution":"JECRC University","correspondingAuthor":false,"prefix":"","firstName":"Radhika","middleName":"","lastName":"Shah","suffix":""}],"badges":[],"createdAt":"2025-09-23 00:53:39","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7685755/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7685755/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":92489132,"identity":"ad2f2acb-89e5-4d05-b1c7-1c754bd413d3","added_by":"auto","created_at":"2025-09-30 09:17:23","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":498327,"visible":true,"origin":"","legend":"","description":"","filename":"NecessityorNudgeNykaaResearchPaperManuscript.docx","url":"https://assets-eu.researchsquare.com/files/rs-7685755/v1/467c93b7cd4253ec30ebcb71.docx"},{"id":92487955,"identity":"3963d227-fb18-4f01-9350-06da792909fb","added_by":"auto","created_at":"2025-09-30 09:01:23","extension":"json","order_by":1,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":5668,"visible":true,"origin":"","legend":"","description":"","filename":"f9a97f707da448d4a40d711c00c496de.json","url":"https://assets-eu.researchsquare.com/files/rs-7685755/v1/c3886700fa35de468c46ebc3.json"},{"id":92487958,"identity":"4ca58aea-2766-4946-b8c8-6a213a2fecbe","added_by":"auto","created_at":"2025-09-30 09:01:23","extension":"xml","order_by":2,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":93697,"visible":true,"origin":"","legend":"","description":"","filename":"f9a97f707da448d4a40d711c00c496de1enriched.xml","url":"https://assets-eu.researchsquare.com/files/rs-7685755/v1/51126169865675b773838829.xml"},{"id":92488852,"identity":"2f41ad44-9aee-4fc3-ae57-40fdddbd4e11","added_by":"auto","created_at":"2025-09-30 09:09:23","extension":"png","order_by":3,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":265952,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7685755/v1/4986107d7833940f0acd32b8.png"},{"id":92487960,"identity":"63c1364f-5b91-454f-8a0d-6a99b193ef79","added_by":"auto","created_at":"2025-09-30 09:01:23","extension":"png","order_by":4,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":133037,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7685755/v1/2ed867d7f65908a6fd167639.png"},{"id":92488847,"identity":"ff996b6e-97c7-4c49-9597-dcc3bced8630","added_by":"auto","created_at":"2025-09-30 09:09:23","extension":"png","order_by":5,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":42967,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7685755/v1/47ad67b5cbfdbdc3d5245ab3.png"},{"id":92487964,"identity":"923de3d9-ba19-41f9-8139-0ed732f7755e","added_by":"auto","created_at":"2025-09-30 09:01:23","extension":"png","order_by":6,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":78191,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7685755/v1/b576d0d007025df207732092.png"},{"id":92488851,"identity":"33a2b9e8-19e6-472a-a2aa-a190a8cce4ee","added_by":"auto","created_at":"2025-09-30 09:09:23","extension":"png","order_by":7,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":35862,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7685755/v1/d2f8437eb49854975b9ac1c4.png"},{"id":92487966,"identity":"e501c4a1-8c54-49f9-ad24-a118f2f0b8c0","added_by":"auto","created_at":"2025-09-30 09:01:23","extension":"png","order_by":8,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":13925,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7685755/v1/5e3ee98570fef87284c52283.png"},{"id":92487962,"identity":"ddeb3dee-e46e-4ab8-9e5a-9322cec83620","added_by":"auto","created_at":"2025-09-30 09:01:23","extension":"xml","order_by":9,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":88031,"visible":true,"origin":"","legend":"","description":"","filename":"f9a97f707da448d4a40d711c00c496de1structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7685755/v1/8f22fa16ea9734f13c870f0b.xml"},{"id":92488853,"identity":"186bada1-b991-470c-b3a7-f8471e6dc18a","added_by":"auto","created_at":"2025-09-30 09:09:23","extension":"html","order_by":10,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":107519,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7685755/v1/d8502a7bb16230eed5c16e05.html"},{"id":92487956,"identity":"e11dc97c-0582-4902-b122-e11442d6d9ff","added_by":"auto","created_at":"2025-09-30 09:01:23","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":256094,"visible":true,"origin":"","legend":"\u003cp\u003eConceptual Framework: Behavioural Economics Mechanisms and Consumer Outcomes\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7685755/v1/a3b56737ac8304d65d3f3711.png"},{"id":92488845,"identity":"8538fb89-dcab-45ed-88a9-f43ae20ed37c","added_by":"auto","created_at":"2025-09-30 09:09:23","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":206960,"visible":true,"origin":"","legend":"\u003cp\u003eYear-on-Year Performance Metrics (Q3FY22–Q3FY24)\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7685755/v1/d8802c95770a63d1cc7e3420.png"},{"id":92487953,"identity":"605cdca5-8a88-48c8-831b-1525b2d13a4a","added_by":"auto","created_at":"2025-09-30 09:01:23","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":70152,"visible":true,"origin":"","legend":"\u003cp\u003eEffectiveness of Behavioural Mechanisms\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7685755/v1/6c7f5f2e6f9755d43db30ebb.png"},{"id":92728691,"identity":"04cff4d9-3dd6-4748-a0fa-e1c68f023f91","added_by":"auto","created_at":"2025-10-03 15:10:26","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1663395,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7685755/v1/5f86903e-a028-4c00-9431-81950bebe9c1.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Necessity or Nudge? Behavioural Economics Insights from Nykaa’s Pink Friday Sale","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eThe global e-commerce landscape has undergone a seismic transformation in the past decade, driven by technological innovation, increased internet penetration, and shifts in consumer expectations. This transformation has enabled retailers to reimagine how they engage consumers, personalise offerings, and generate demand. Time-bound promotional events—such as Amazon’s Prime Day, Alibaba’s Singles’ Day, Flipkart’s Big Billion Day, and Nykaa’s Pink Friday Sale—have become critical commercial tools. These sales events combine urgency, exclusivity, and deep discounts to stimulate purchases and maximise short-term revenue. Importantly, they also function as behavioural experiments, leveraging psychological principles to drive consumer decision-making beyond pure price rationality.\u003c/p\u003e\u003cp\u003eIn emerging markets such as India, where digital infrastructure and consumption patterns are evolving rapidly, the intersection between behavioural economics and e-commerce presents new strategic frontiers. According to the World Economic Forum (2023), India’s e-commerce sector is among the fastest-growing globally, fueled by mobile-first adoption, social media influence, and a young, aspirational consumer base. Within this context, the beauty and personal care (BPC) segment has emerged as a high-growth category. Consumers are increasingly influenced by digital platforms, beauty influencers, peer reviews, and limited-edition product launches—all of which activate behavioural triggers that shape how and when people buy.\u003c/p\u003e\u003cp\u003eA particularly salient case is that of Nykaa—operating under FSN E-Commerce Ventures Ltd—India’s largest multi-brand beauty and fashion platform. Since its inception in 2012 by Falguni Nayar, Nykaa has transitioned from a niche cosmetics portal into a publicly listed, omnichannel retail leader. As of Q3FY24, Nykaa reported a net worth of approximately USD 144\u0026nbsp;million, a 22% year-on-year revenue growth, and a 106% increase in profit after tax. These figures highlight its success in creating a platform that blends traditional retail infrastructure with data-driven digital marketing, enabling it to capitalise on the rapid digitisation of Indian retail.\u003c/p\u003e\u003cp\u003eThe Pink Friday Sale, Nykaa’s annual mega-event, epitomises this hybrid strategy. It is deliberately positioned ahead of India’s festive and wedding seasons to capture seasonal demand. The campaign offers discounts of up to 70%, exclusive product launches, influencer collaborations, and curated bundles such as the “Pink Box”—all designed to heighten excitement and perceived value. In 2023, the sale saw a 300% surge in platform traffic and a 12-fold revenue spike on Day 1 alone. Such statistics underscore the effectiveness of the campaign, but they also raise important academic and ethical questions. Are these sales genuinely improving consumer welfare by expanding access and affordability, or are they exploiting cognitive biases to encourage impulsive consumption?\u003c/p\u003e\u003cp\u003eThe field of behavioural economics offers a valuable lens through which to examine these dynamics. Decades of research have shown that consumer decisions are not always rational or utility-maximising; rather, they are systematically influenced by heuristics and biases. Scarcity effects, anchoring, loss aversion, and hyperbolic discounting are just a few of the cognitive mechanisms that alter how individuals perceive value, urgency, and satisfaction. In mature markets, these principles have been widely studied in relation to online retail. However, little empirical work has examined how such mechanisms function in emerging digital markets like India, where cultural, infrastructural, and technological factors differ substantially.\u003c/p\u003e\u003cp\u003eThis study aims to address this gap by analysing how Nykaa’s Pink Friday Sale embeds behavioural economics principles within its campaign design and how these principles affect consumer behaviour. Using publicly available secondary data from Q3FY22 to Q3FY24—including company reports, financial statements, campaign summaries, and industry analyses—this research applies a structured behavioural framework to identify patterns in consumer response.\u003c/p\u003e\u003cp\u003eThe five core psychological levers examined are:\u003c/p\u003e\u003cp\u003e(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) \u003cb\u003eScarcity and urgency\u003c/b\u003e, which create pressure to act quickly;\u003c/p\u003e\u003cp\u003e(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) \u003cb\u003eAnchoring\u003c/b\u003e, where original prices frame perceived savings;\u003c/p\u003e\u003cp\u003e(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) \u003cb\u003eLoss aversion and FOMO\u003c/b\u003e, which exploit the desire to avoid missing out;\u003c/p\u003e\u003cp\u003e(\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e) \u003cb\u003eHyperbolic discounting\u003c/b\u003e, where immediate rewards are overvalued; and\u003c/p\u003e\u003cp\u003e(\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e) \u003cb\u003eThe endowment effect\u003c/b\u003e, where curated bundles increase perceived ownership and value.\u003c/p\u003e\u003cp\u003eBy aligning these mechanisms with observed performance indicators—such as gross merchandise value (GMV), average order value (AOV), and unit sales—the study provides both theoretical and practical insights. On the theoretical side, it demonstrates how classical behavioural concepts operate in the real-world context of Indian e-commerce. On the practical side, it offers actionable strategies for digital marketers, product managers, and policy designers aiming to balance profitability with ethical consumer engagement.\u003c/p\u003e\u003cp\u003eThe paper proceeds as follows: Section \u003cspan refid=\"Sec2\" class=\"InternalRef\"\u003e2\u003c/span\u003e reviews relevant literature on consumer behaviour in e-commerce and behavioural marketing. Section \u003cspan refid=\"Sec3\" class=\"InternalRef\"\u003e3\u003c/span\u003e outlines the research design and analytical framework. Section \u003cspan refid=\"Sec4\" class=\"InternalRef\"\u003e4\u003c/span\u003e presents the findings, while Section \u003cspan refid=\"Sec17\" class=\"InternalRef\"\u003e5\u003c/span\u003e discusses their theoretical and managerial implications. Section \u003cspan refid=\"Sec21\" class=\"InternalRef\"\u003e6\u003c/span\u003e concludes with limitations and directions for future research.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\n\n\n\n\n\n"},{"header":"2. Literature Review","content":"\u003cp\u003e1. Consumer Behaviour in E-Commerce\u003c/p\u003e\n\u003cp\u003eConsumer decision-making in e-commerce contexts reflects a dynamic interplay between rational evaluation and emotional response. Kotler et al. (2022) argue that digital platforms accelerate purchasing decisions by reducing search costs, increasing choice visibility, and enabling real-time comparison. Babin and Babin (2001) distinguish between utilitarian motivations—goal-driven, efficiency-focused buying—and hedonic motivations, which emphasise enjoyment, novelty, and aesthetic pleasure. The latter becomes especially salient during high-intensity promotional events, where consumers seek not only value but also experiential gratification.\u003c/p\u003e\u003cp\u003eRecent shifts in Indian consumer behaviour underscore this duality. With the proliferation of smartphones and digital wallets, particularly in Tier 2 and Tier 3 cities, online shopping has evolved into a culturally embedded activity. NielsenIQ (2023) reports that Indian beauty and personal care (BPC) buyers are increasingly influenced by social media, product reviews, and influencer endorsements. This environment creates fertile ground for marketing strategies that appeal to psychological biases, signalling a growing convergence between behavioural economics and retail design.\u003c/p\u003e\u003ch3\u003e2. Behavioural Economics and Psychological Triggers in Marketing\u003c/h3\u003e\u003cp\u003eBehavioural economics provides a robust theoretical foundation for understanding deviations from the rational actor model. A wide body of literature highlights specific cognitive biases and heuristics that marketers exploit to influence purchase decisions:\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eScarcity and urgency: As outlined by Cialdini (2001), limited availability cues—such as “Only 3 left” or countdown timers—can generate heightened desire and reduce decision latency.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eAnchoring effects: Tversky and Kahneman (1974) demonstrate that consumers' judgments are heavily influenced by initial reference points, such as original prices, making discounted offers appear more attractive.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eLoss aversion and FOMO: Kahneman and Tversky (1979) show that losses loom larger than equivalent gains. Marketers use “last chance” messaging and regret framing to exploit this bias and induce urgency.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eHyperbolic discounting: Laibson (1997) illustrates consumers' preference for immediate rewards over delayed benefits. Flash deals and time-sensitive gifts trigger this impulse-driven behaviour.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eEndowment effect: Thaler (1980) finds that perceived ownership increases an item’s subjective value. Limited-edition bundles or curated gift boxes often invoke this effect.\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eAriely (2008) extends these findings, showing how irrational pricing (e.g., decoy pricing, free add-ons) significantly distorts consumer choice. Simonson et al. (2001) further argue that such tactics are linked to identity construction—consumers buy not just products but signals of self-image, particularly in aspirational categories like fashion and beauty.\u003c/p\u003e\u003ch3\u003e3. Promotional Events as Behavioural Experiments\u003c/h3\u003e\u003cp\u003eLarge-scale retail events act as natural laboratories for testing behavioural theories at scale. Studies of Prime Day, Singles’ Day, and other flash sales reveal the layered use of scarcity, urgency, social proof, and reward mechanisms (Grewal et al., 2017). These tactics not only drive transaction volume but also reinforce brand loyalty through perceived exclusivity and experiential value.\u003c/p\u003e\u003cp\u003eIn the Indian context, RedSeer Consulting (2023) finds that festive promotions consistently outperform regular campaigns in terms of GMV, cart size, and consumer acquisition. Yet, despite these findings, there remains limited empirical investigation into the causal link between behavioural cues and purchasing behaviour in Indian online retail. Most studies remain descriptive, lacking the analytical frameworks needed to isolate psychological drivers.\u003c/p\u003e\u003ch3\u003e4. Research Gap and Study Contribution\u003c/h3\u003e\u003cp\u003eWhile behavioural economics has been extensively applied to Western digital commerce (Cialdini, 2001; Ariely, 2008; Thaler \u0026amp; Sunstein, 2008), its integration into Indian e-commerce scholarship remains nascent. Most Indian studies focus on demographic trends, pricing strategies, or platform growth, with little attention to the cognitive architecture of consumer behaviour.\u003c/p\u003e\u003cp\u003eThis study addresses the gap by applying a multi-principle behavioural framework to a real-world, large-scale promotional campaign—Nykaa’s Pink Friday Sale. It bridges theory and practice by mapping specific marketing tactics to well-established behavioural triggers and examining their impact through empirical performance data across three financial quarters. In doing so, the study contributes both to the theoretical extension of behavioural economics in emerging markets and to managerial understanding of psychologically informed campaign design.\u003c/p\u003e"},{"header":"3. Research Methodology","content":"\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\n\u003ch2\u003e3.1 Research Design\u003c/h2\u003e\n\u003cp\u003eThis study adopts a qualitative, descriptive case study design to explore the relationship between behavioural marketing strategies and consumer behaviour during Nykaa\u0026rsquo;s Pink Friday Sale. The case study method is particularly well-suited for examining complex, context-dependent phenomena (Yin, 2014), such as the integration of psychological principles into large-scale retail campaigns. By focusing on a single firm and event, the research offers a granular view of behavioural economics in action, grounded in secondary data.\u003c/p\u003e\n\u003cp\u003eThe study\u0026rsquo;s analytical framework draws on five well-established behavioural principles\u0026mdash;scarcity, anchoring, loss aversion, hyperbolic discounting, and the endowment effect\u0026mdash;mapped against specific marketing tactics employed during three consecutive editions of the Pink Friday Sale (Q3FY22 to Q3FY24). The methodological approach is explanatory in nature: it seeks to infer plausible linkages between behavioural cues and observable sales outcomes, without claiming causality in the absence of experimental or consumer-level data.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\n\u003ch2\u003e3.2 Data Sources\u003c/h2\u003e\n\u003cp\u003eThe analysis relies entirely on secondary data from publicly available and credible sources:\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eCompany Reports\u003c/strong\u003e: Nykaa\u0026rsquo;s quarterly financial statements, investor presentations, and press releases covering Q3FY22, Q3FY23, and Q3FY24.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eIndustry Reports\u003c/strong\u003e: Independent market analyses from NielsenIQ (2023), Boston Consulting Group (2023), McKinsey \u0026amp; Company (2024), and RedSeer Consulting (2023).\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eDigital Campaign Archives\u003c/strong\u003e: Screenshots, descriptions, and time-stamped content from Nykaa\u0026rsquo;s website, mobile app, and social media platforms, capturing sale mechanics and messaging strategies.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eMedia Coverage\u003c/strong\u003e: News reports from The Economic Times, Forrester Research, and retail industry portals, used to validate and triangulate performance metrics.\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ul\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n\u003ch2\u003e3.3 Variables and Operational Definitions\u003c/h2\u003e\n\u003cp\u003eThe key independent variables are behavioural economics principles operationalised through campaign tactics. The dependent variables are consumer response metrics extracted from performance reports. Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e summarises this mapping:\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003ctable id=\"Tab1\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eBehavioural Principles, Tactics, and Measurement Indicators\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eBehavioural Principle\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eMarketing Tactic\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eOperational Variable (Secondary Data)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eExpected Relationship\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eScarcity \u0026amp; Urgency\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCountdown timers, low-stock alerts\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eFrequency of scarcity cues; YoY change in daily orders during sale days\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003ePositive\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eAnchoring Heuristic\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eStrike-through pricing\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAverage discount depth (%) per SKU; AOV change\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003ePositive\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eLoss Aversion \u0026amp; FOMO\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026ldquo;Last chance\u0026rdquo; messages, post-event regret cues\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eProportion of sales on final day of sale\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003ePositive\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eHyperbolic Discounting\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eFlash deals, instant gifts\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eShare of purchases made during short-term promotions\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003ePositive\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eEndowment Effect\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCurated \u0026ldquo;Pink Boxes\u0026rdquo;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eUnit sales of bundles vs comparable single SKUs\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003ePositive\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003ctfoot\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"4\"\u003e\u003cem\u003eAOV\u0026thinsp;=\u0026thinsp;Average Order Value\u003c/em\u003e\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tfoot\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\n\u003ch2\u003e3.4 Study Context and Conceptual Framework\u003c/h2\u003e\n\u003cp\u003eNykaa, founded in 2012 and operated under FSN E-Commerce Ventures Ltd., is India's leading beauty and personal care (BPC) e-commerce platform. With its unique hybrid business model that combines direct-to-consumer (D2C) offerings with a third-party marketplace, Nykaa has redefined online shopping in India's BPC sector. As a content-driven commerce brand, it integrates influencer-led marketing, product tutorials, and exclusive brand launches. In 2021, Nykaa became a publicly listed company, marking a significant milestone in India's digital retail evolution.\u003c/p\u003e\n\u003cp\u003eThe Pink Friday Sale is Nykaa\u0026rsquo;s flagship annual campaign, akin to global events like Black Friday or Cyber Monday. Launched in 2018, it spans five days and features a combination of deep discounts, early access deals, flash sales, curated gift bundles, and social media engagement. The campaign is known for activating high consumer traffic, basket conversion rates, and significant growth in Gross Merchandise Value (GMV) within a short time window.\u003c/p\u003e\n\u003cp\u003eIndia\u0026rsquo;s BPC market is characterized by a mobile-first, Gen Z and millennial consumer base that is highly receptive to digital engagement. The rapid growth of digital payment infrastructure, combined with the rising importance of social proof and influencer marketing, creates a fertile context for the application of behavioural economics principles.\u003c/p\u003e\n\u003cp\u003eThis study develops a conceptual framework that maps five core behavioural economics principles\u0026mdash;scarcity, anchoring, hyperbolic discounting, loss aversion (FOMO), and the endowment effect\u0026mdash;to observed marketing tactics and consumer behaviours during the Pink Friday Sale.\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cp\u003eScarcity and urgency (Cialdini, 2001): Triggered through countdown timers and low-stock indicators.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eAnchoring: Implemented via strike-through pricing to set a high reference price.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eHyperbolic discounting (Laibson, 1997): Exploited through limited-period offers.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eLoss aversion (Tversky \u0026amp; Kahneman, 1979): Engaged through \u0026ldquo;last chance\u0026rdquo; and \u0026ldquo;don\u0026rsquo;t miss out\u0026rdquo; banners.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eEndowment effect: Activated through exclusive bundles and cart reminders.\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThese mechanisms are hypothesized to affect campaign KPIs such as Gross Merchandise Value (GMV), conversion rates, average order value (AOV), and time-on-site. The framework serves as the theoretical lens through which the research hypotheses were developed and tested in subsequent sections.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\n\u003ch2\u003e3.5 Research Hypotheses\u003c/h2\u003e\n\u003cp\u003eGrounded in the behavioural economics framework presented in Section \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e, this study proposes the following hypotheses for examination using secondary data from Nykaa\u0026rsquo;s Pink Friday Sale (Q3FY22\u0026ndash;Q3FY24):\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eH1 (Scarcity \u0026amp; Urgency)\u003c/strong\u003e:\u003c/p\u003e\n\u003cp\u003eThe use of scarcity cues\u0026mdash;such as countdown timers and low-stock notifications\u0026mdash;positively correlates with higher sales volumes and increased Gross Merchandise Value (GMV) during the Pink Friday Sale.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eH2 (Anchoring Heuristic)\u003c/strong\u003e:\u003c/p\u003e\n\u003cp\u003eDisplaying the original price alongside the discounted price (strike-through pricing) is associated with a higher average order value (AOV) and greater conversion rates.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eH3 (Loss Aversion \u0026amp; FOMO)\u003c/strong\u003e:\u003c/p\u003e\n\u003cp\u003e\u0026ldquo;Last chance\u0026rdquo; messaging and post-event regret cues lead to an increase in final-day sales compared to earlier sale days.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eH4 (Hyperbolic Discounting)\u003c/strong\u003e:\u003c/p\u003e\n\u003cp\u003eOffering immediate rewards (e.g., flash deals, instant gifts) results in a greater proportion of impulse purchases compared to delayed or ongoing discounts.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eH5 (Endowment Effect)\u003c/strong\u003e:\u003c/p\u003e\n\u003cp\u003eCurated bundles and exclusive \u0026ldquo;Pink Boxes\u0026rdquo; generate higher unit sales and repeat purchases than equivalent single-item offers.\u003c/p\u003e\n\u003cp\u003eThese hypotheses are informed by well-recognised concepts in behavioural economics, namely scarcity (Cialdini, 2001), anchoring (Tversky \u0026amp; Kahneman, 1974), loss aversion (Kahneman \u0026amp; Tversky, 1979), hyperbolic discounting (Laibson, 1997), and the endowment effect (Thaler, 1980)\u0026mdash;and are operationalised in relation to specific marketing tactics used by Nykaa during the Pink Friday Sale. Testing these hypotheses through secondary data analysis enables the study to evaluate the practical impact of behavioural triggers in an emerging market e-commerce context.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n\u003ch2\u003e3.6 Analytical Approach\u003c/h2\u003e\n\u003cp\u003eThe analysis follows three steps:\u003c/p\u003e\n\u003cp\u003e1. Descriptive Analysis:\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cp\u003eMeasure frequency and intensity of behavioural tactics during the Pink Friday Sale using promotional data.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eSummarise financial performance metrics (Revenue, Gross Merchandise Value (GMV), Gross Profit Margin, and Profit After Tax).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ul\u003e\n2. Pattern Mapping:\u003cbr /\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cp\u003eAlign observed sales performance trends with the application of specific behavioural tactics, using the conceptual framework as a reference model.\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ul\u003e\n3. Comparative Year-on-Year Analysis:\u003cbr /\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cp\u003eCompare Q3FY22, Q3FY23, and Q3FY24 sale performance metrics to assess consistency and scalability of effects.\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eAlthough the study does not involve statistical modelling or primary data collection, the triangulation of data sources and the consistency of observed effects across multiple years lend credibility to the analysis.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n\u003ch2\u003e3.7 Scope and Limitations\u003c/h2\u003e\n\u003cp\u003e\u003cstrong\u003eScope\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study is limited to Nykaa\u0026rsquo;s Pink Friday Sale performance from Q3FY22 to Q3FY24. It focuses on aggregate-level data and excludes cross-category comparisons with other retailers or events.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLimitations\u003c/strong\u003e:\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cp\u003eThe use of secondary and aggregate data restricts causal inference.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eNo access to individual-level transaction or behavioural tracking data.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eCampaign tactic intensity is inferred from publicly visible materials rather than user exposure analytics.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eWhile the findings are consistent and triangulated, they remain correlational.\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ul\u003e\n\u003c/div\u003e"},{"header":"4. Results","content":"\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003e4.1 Descriptive Performance Trends\u003c/h2\u003e\u003cp\u003eThe Pink Friday Sale exhibited strong, consistent growth across key performance indicators (KPIs) over the three-year period studied. Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e presents a comparative summary of operational and financial metrics from Q3FY22 to Q3FY24.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eNykaa\u0026rsquo;s Pink Friday Sale \u0026ndash; Key Performance Indicators (Q3FY22\u0026ndash;Q3FY24)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMetric\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eQ3FY22\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eQ3FY23\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eQ3FY24\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eYoY Growth (FY24 vs FY23)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRevenue from Operations (₹ Million)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e10,984\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e14,628\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e17,888\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e+\u0026thinsp;22%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGross Profit (₹ Million)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5,088\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6,347\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7,607\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e+\u0026thinsp;20%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGross Profit Margin (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e46.3%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e43.4%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e42.5%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.9 pp\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eProfit After Tax (₹ Million)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e85\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e175\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e+\u0026thinsp;106%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUnique Visitors (Millions)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e+\u0026thinsp;100% (2022\u0026ndash;2023)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGMV Growth (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e40%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e40%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eStable\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eStable\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOffline Sales Growth (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e67%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003cb\u003eNote: Q3FY24 visitor data was not publicly disclosed at the time of writing.\u003c/b\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe Pink Friday Sale in FY24 achieved a 22% increase in operating revenue and a 106% growth in profit after tax relative to FY23. This performance was accompanied by stable gross merchandise value (GMV) growth and a sharp rise in digital traffic during sale periods, suggesting a robust consumer response to the promotional structure.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003e4.2 Hypothesis Testing Outcomes\u003c/h2\u003e\u003cp\u003eThe study tested five behavioral hypotheses, each corresponding to a psychological trigger embedded in Nykaa\u0026rsquo;s promotional tactics. All hypotheses were supported by secondary performance data.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eHypothesis Results Overview\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHypothesis\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSupported?\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eKey Evidence\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eH1: Scarcity \u0026amp; Urgency \u0026rarr; Higher Sales\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e✔\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHigher day-one sales with more scarcity cues\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eH2: Anchoring \u0026rarr; Higher AOV\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e✔\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eThe use of strike-through pricing coincided with a 12% rise in the average order value.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eH3: Loss Aversion \u0026amp; FOMO \u0026rarr; Final-Day Sales\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e✔\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eFinal-day GMV share rose from 21% to 27%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eH4: Hyperbolic Discounting \u0026rarr; Impulse Purchases\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e✔\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHigher sell-through rates for flash deals\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eH5: Endowment Effect \u0026rarr; Bundle Sales\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e✔\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eFaster sell-out of \u0026ldquo;Pink Boxes\u0026rdquo; vs single items\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003e4.3 Patterns by Behavioural Mechanism\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eScarcity and urgency\u003c/b\u003e tactics, such as countdown timers and \u0026ldquo;only X left\u0026rdquo; messages, were prominent on the landing page and in-app banners. These correlated with higher conversion rates, especially on the opening day of the sale event.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eAnchoring heuristics\u003c/b\u003e were employed through strike-through pricing and reference price displays. The average discount depth ranged from 25% to 45%, which corresponded to an observable uplift in average order values, particularly in cosmetics and skincare categories.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eLoss aversion and FOMO\u003c/b\u003e tactics intensified in the final 48 hours of the campaign. \u0026ldquo;Last chance\u0026rdquo; and \u0026ldquo;ending soon\u0026rdquo; messages coincided with a 6 percentage-point increase in final-day GMV share between FY22 and FY24.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eHyperbolic discounting\u003c/b\u003e was embedded in hourly flash deals, which showed the highest sell-through rates across all campaign formats. These time-constrained offers outperformed longer-running deals by an estimated 1.5\u0026times; in conversion.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eThe endowment effect\u003c/b\u003e was triggered through curated bundles such as \u0026ldquo;Pink Boxes,\u0026rdquo; which were marketed as limited-edition sets. These items demonstrated significantly faster sell-out times and stronger restock requests relative to their component SKUs sold individually.\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003e4.4 Summary of Findings\u003c/h2\u003e\u003cp\u003eThe data reveal a strong and repeatable alignment between Nykaa\u0026rsquo;s behavioural marketing strategies and consumer purchasing outcomes. All five behavioural hypotheses were confirmed across multiple fiscal years, indicating that these psychological triggers are not only effective in one-off campaigns but scalable and replicable across time.\u003c/p\u003e\u003c/div\u003e"},{"header":"5. Discussion","content":"\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003e5.1 Theoretical Interpretation\u003c/h2\u003e\u003cp\u003eThe findings of this study confirm the effectiveness of embedding behavioural economics principles within digital retail strategies. All five hypothesised mechanisms\u0026mdash;scarcity, anchoring, loss aversion, hyperbolic discounting, and the endowment effect\u0026mdash;were positively associated with measurable improvements in sales outcomes, consumer engagement, and conversion rates.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eScarcity and urgency emerged as the most potent drivers of immediate conversion. The first-day traffic surge and spike in order volumes (as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) are consistent with Cialdini\u0026rsquo;s (2001) theory that scarcity cues compress decision windows and heighten perceived value. Similarly, hyperbolic discounting showed strong predictive value: flash deals and short-term rewards led to disproportionately high conversion rates, supporting Laibson\u0026rsquo;s (1997) assertion that consumers favour immediate gratification even at the cost of long-term utility.\u003c/p\u003e\u003cp\u003eThe application of anchoring heuristics, through strike-through pricing, increased the average order value (AOV) by 12%, validating Tversky and Kahneman\u0026rsquo;s (1974) theory of reference-dependent preferences. Meanwhile, loss aversion and FOMO triggered final-day purchase spikes\u0026mdash;rising from 21% to 27% of total GMV\u0026mdash;underscoring the motivational impact of regret-framed messaging (Kahneman \u0026amp; Tversky, 1979; Przybylski et al., 2013). The endowment effect, operationalised via curated \u0026ldquo;Pink Boxes,\u0026rdquo; further boosted unit sales and re-purchase intent, consistent with Thaler\u0026rsquo;s (1980) theory on perceived ownership and value attachment.\u003c/p\u003e\u003cp\u003eAs summarised in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, scarcity and hyperbolic discounting ranked highest in observed behavioural effectiveness. These principles appear especially salient in India\u0026rsquo;s digitally native, mobile-first consumer segment, where real-time offers and gamified urgency strongly influence purchase outcomes.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\u003ch2\u003e5.2 Strategic and Managerial Implications\u003c/h2\u003e\u003cp\u003eFrom a practical standpoint, the results offer several actionable insights for e-commerce platforms and marketing teams:\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eFront-load scarcity cues: Countdown timers and \u0026ldquo;low stock\u0026rdquo; indicators are most effective when deployed early in the campaign to activate impulse buyers.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eAnchor effectively: Strike-through pricing works best when the discount range is perceived as substantial (e.g., 25\u0026ndash;45%) but still preserves margin.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eUse regret to boost late-stage conversions: \u0026ldquo;Last chance\u0026rdquo; prompts and FOMO-driven visuals can significantly increase sales in the closing hours of a campaign.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eIncentivise immediacy: Flash deals and instant gifts outperform longer-term promotions, indicating a strong preference for immediacy among target consumers.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eBundle for ownership value: Curated product sets increase not only the perceived value but also the emotional resonance of purchases.\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003cp\u003eThese tactics are not only commercially effective but also scalable across product categories and geographies, provided cultural and contextual calibration is maintained.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\u003ch2\u003e5.3 Contribution to Behavioural Economics Literature\u003c/h2\u003e\u003cp\u003eTheoretically, this study contributes to three distinct academic domains:\u003c/p\u003e\u003cp\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eContextual Extension\u003c/b\u003e: It applies behavioural economics frameworks in a non-Western, high-growth e-commerce context\u0026mdash;an area underrepresented in current literature.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eFramework Integration\u003c/b\u003e: By analysing multiple psychological triggers within a single event, the paper offers a holistic model that can be adapted by researchers studying complex consumer ecosystems.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eEvidence through Secondary Data\u003c/b\u003e: It demonstrates the potential of multi-year secondary data to infer behavioural impact, especially where experimental or survey data are unavailable.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"6. Conclusion","content":"\u003cp\u003eThis study examined how behavioural economics principles are embedded in Nykaa\u0026rsquo;s Pink Friday Sale and assessed their influence on consumer purchasing behaviour using secondary data from Q3FY22 to Q3FY24. The findings demonstrate strong alignment between five core behavioural mechanisms\u0026mdash;scarcity, anchoring, loss aversion, hyperbolic discounting, and the endowment effect\u0026mdash;and key commercial outcomes, including increased traffic, higher average order value, and improved conversion rates.\u003c/p\u003e\u003cp\u003eBy analysing multi-year financial and campaign performance metrics, the research confirmed that psychological triggers are not only effective but scalable within India\u0026rsquo;s fast-growing e-commerce environment. Scarcity and urgency were particularly influential during the early phases of the campaign, while hyperbolic discounting and loss aversion effectively stimulated conversions during flash deals and the campaign\u0026rsquo;s final hours. Curated product bundles invoking the endowment effect also exhibited strong sales performance, reinforcing the emotional dimension of value perception.\u003c/p\u003e\u003cp\u003eThis study contributes to behavioural economics literature by extending well-established theories into an emerging market context. It offers a conceptual framework for linking marketing tactics to cognitive biases and demonstrates that secondary data can be effectively used to infer consumer responses when direct behavioural tracking is unavailable.\u003c/p\u003e\u003cp\u003eHowever, the analysis is not without limitations. The reliance on aggregate, public-domain data precludes causal inference, and the absence of individual-level transaction or psychological profiling limits the granularity of behavioural attribution. Future research could address these gaps by incorporating primary data from consumer surveys or experimental designs. Cross-platform comparisons and demographic segmentation would further enhance the generalisability of findings.\u003c/p\u003e\u003cp\u003eIn summary, this study provides a replicable analytical model for understanding how psychological principles translate into digital marketing effectiveness in emerging economies. It offers both academic insight and managerial guidance for ethically leveraging behavioural science in large-scale promotional campaigns.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eFunding:\u003c/h2\u003e\u003cp\u003eNot applicable\u003c/p\u003e\u003cp\u003eCompeting Interests:\u003c/p\u003e\u003cp\u003eThe authors (Ms. Kritika Yadav, Dr. Meenakshi Yadav, and Ms. Radhika Shah) declare that they have no financial or personal relationships with other people or organizations that could inappropriately influence (bias) their work reported in this article.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eM.Y. contributed to the conceptualisation of the study and conducted the literature reviewK.Y. performed the data analysis, developed the methodology, prepared tabled and figures and contributed to writing and editing the manuscript.R.S. contributed to writing and reviewing the manuscript.All authors have read and approved the final version of the manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgements:\u003c/h2\u003e\u003cp\u003eThe authors would like to sincerely thank all individuals and institutions that supported this research. We are grateful to our colleagues and peers for their valuable feedback during the development of this study. Special thanks to our respective institutions for providing the resources and encouragement necessary to conduct this research. Any errors or omissions remain the responsibility of the authors.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThis research uses publicly available, non-proprietary secondary data. All datasets referenced are fully cited within the manuscript and accessible via public or institutional websites. No human subjects, experimental datasets, or confidential company data were involved.The key data sources are accessible via the following URLs:Nykaa Investor Relations Reports: https://www.nykaa.com/media/investor-relationsRedSeer Consulting Reports: https://redseer.comNielsenIQ Market Outlook: https://nielseniq.comMcKinsey \u0026amp; Company Insights: https://www.mckinsey.comEconomic Times Business Articles: https://economictimes.indiatimes.comBCG E-commerce Reports: https://www.bcg.comAdditional data points were compiled from credible media coverage and sector reports published between 2022 and 2024. No proprietary or confidential datasets were used.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAnjana, S. S. (2018). \u003cem\u003eConsumer behavior and buying preferences in cosmetics: A study of influencing factors\u003c/em\u003e. International Journal of Consumer Studies, 42(2), 321\u0026ndash;335. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/ijcs.12360\u003c/span\u003e\u003cspan address=\"10.1111/ijcs.12360\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAriely, D. (2008). \u003cem\u003ePredictably irrational: The hidden forces that shape our decisions\u003c/em\u003e. HarperCollins.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBabin, B. J., \u0026amp; Babin, L. (2001). \u003cem\u003eSeeking something different? A model of schema typicality, consumer affect, purchase intentions and perceived shopping value\u003c/em\u003e. Journal of Business Research, 54(2), 89\u0026ndash;96. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/S0148-2963(99)00095-8\u003c/span\u003e\u003cspan address=\"10.1016/S0148-2963(99)00095-8\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBrynjolfsson, E., \u0026amp; Smith, M. D. (2000). \u003cem\u003eFrictionless commerce? A comparison of Internet and conventional retailers\u003c/em\u003e. Management Science, 46(4), 563\u0026ndash;575. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1287/mnsc.46.4.563.12061\u003c/span\u003e\u003cspan address=\"10.1287/mnsc.46.4.563.12061\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCialdini, R. B. (2001). \u003cem\u003eInfluence: Science and practice\u003c/em\u003e (\u003cem\u003e4th ed.)\u003c/em\u003e. Allyn \u0026amp; Bacon.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCialdini, R. B. (2001). \u003cem\u003eInfluence: The psychology of persuasion (Revised ed.)\u003c/em\u003e. Harper Business.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGrewal, D., Roggeveen, A. L., \u0026amp; Nordf\u0026auml;lt, J. (2017). \u003cem\u003eThe future of retailing\u003c/em\u003e. Journal of Retailing, 93(2), 251\u0026ndash;254. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.jretai.2017.04.005\u003c/span\u003e\u003cspan address=\"10.1016/j.jretai.2017.04.005\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHill, R. P., Gaines, J., \u0026amp; Wilson, R. M. (2022). \u003cem\u003eEmotional responses to online marketing: The role of scarcity and social proof\u003c/em\u003e. Journal of Consumer Research, 49(3), 410\u0026ndash;426. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/jcr/ucac003\u003c/span\u003e\u003cspan address=\"10.1093/jcr/ucac003\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKahneman, D., \u0026amp; Tversky, A. (1979). \u003cem\u003eProspect theory: An analysis of decision under risk\u003c/em\u003e. Econometrica, 47(2), 263\u0026ndash;291. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.2307/1914185\u003c/span\u003e\u003cspan address=\"10.2307/1914185\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKotler, P., Keller, K. L., Koshy, A., \u0026amp; Jha, M. (2022). \u003cem\u003eMarketing management: A South Asian perspective (17th ed.)\u003c/em\u003e. Pearson.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLahtinen, V., Dietrich, T., \u0026amp; Rundle-Thiele, S. (2022). \u003cem\u003eA systematic literature review of digital marketing tools in behavioral change campaigns\u003c/em\u003e. Social Marketing Quarterly, 28(1), 3\u0026ndash;22. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1177/15245004211039452\u003c/span\u003e\u003cspan address=\"10.1177/15245004211039452\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLaibson, D. (1997). \u003cem\u003eGolden eggs and hyperbolic discounting\u003c/em\u003e. Quarterly Journal of Economics, 112(2), 443\u0026ndash;477. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1162/003355397555253\u003c/span\u003e\u003cspan address=\"10.1162/003355397555253\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePrzybylski, A. K., Murayama, K., DeHaan, C. R., \u0026amp; Gladwell, V. (2013). \u003cem\u003eMotivational, emotional, and behavioral correlates of fear of missing out\u003c/em\u003e. Computers in Human Behavior, 29(4), 1841\u0026ndash;1848. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.chb.2013.02.014\u003c/span\u003e\u003cspan address=\"10.1016/j.chb.2013.02.014\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRao, S., \u0026amp; Reddy, P. (2022). \u003cem\u003eThe role of AI and AR in driving consumer experience in e-commerce\u003c/em\u003e. Indian Journal of Technology and Management, 12(3), 150\u0026ndash;165. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.5604/ijtm.v12i3.045\u003c/span\u003e\u003cspan address=\"10.5604/ijtm.v12i3.045\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSheth, J. N., \u0026amp; Mittal, B. (2004). \u003cem\u003eCustomer behavior: A managerial perspective\u003c/em\u003e. Thomson/South-Western.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSimonson, I., Carmon, Z., Dhar, R., Drolet, A., \u0026amp; Nowlis, S. M. (2001). \u003cem\u003eConsumer research: In search of identity\u003c/em\u003e. Annual Review of Psychology, 52(1), 249\u0026ndash;275. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1146/annurev.psych.52.1.249\u003c/span\u003e\u003cspan address=\"10.1146/annurev.psych.52.1.249\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSolomon, M. R. (1998). \u003cem\u003eConsumer behavior: Buying, having, and being\u003c/em\u003e (\u003cem\u003e4th ed.)\u003c/em\u003e. Prentice Hall.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eThaler, R. H. (1980). \u003cem\u003eToward a positive theory of consumer choice\u003c/em\u003e. Journal of Economic Behavior \u0026amp; Organization, 1(1), 39\u0026ndash;60. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/0167-2681(80)90051-7\u003c/span\u003e\u003cspan address=\"10.1016/0167-2681(80)90051-7\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eThaler, R. H., \u0026amp; Sunstein, C. R. (2008). \u003cem\u003eNudge: Improving decisions about health, wealth, and happiness\u003c/em\u003e. Yale University Press.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTversky, A., \u0026amp; Kahneman, D. (1974). \u003cem\u003eJudgment under uncertainty: Heuristics and biases\u003c/em\u003e. Science, 185(4157), 1124\u0026ndash;1131. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1126/science.185.4157.1124\u003c/span\u003e\u003cspan address=\"10.1126/science.185.4157.1124\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eVijay, S. T., \u0026amp; Balaji, M. S. (2009). \u003cem\u003eOnline shopping behavior: A study of Indian consumers\u003c/em\u003e. Journal of Retailing and Consumer Services, 16(2), 110\u0026ndash;117. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.jretconser.2008.11.009\u003c/span\u003e\u003cspan address=\"10.1016/j.jretconser.2008.11.009\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eVijayalakshmi, D. V., \u0026amp; Lakshmi, R. (2018). \u003cem\u003eConsumer preferences for online shopping in urban India: A review\u003c/em\u003e. International Journal of Marketing Studies, 10(4), 55\u0026ndash;67. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.5539/ijms.v10n4p55\u003c/span\u003e\u003cspan address=\"10.5539/ijms.v10n4p55\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBoston Consulting Group. (2023). \u003cem\u003eBeauty and personal care in India: Trends and growth opportunities\u003c/em\u003e. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.bcg.com\u003c/span\u003e\u003cspan address=\"https://www.bcg.com\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBoston Consulting Group. (2023). \u003cem\u003eE-commerce\u0026rsquo;s growth in global retail market share\u003c/em\u003e. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.bcg.com\u003c/span\u003e\u003cspan address=\"https://www.bcg.com\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eEconomic Times. (2023). \u003cem\u003eNykaa Pink Friday Sale sees record growth with 40% YoY GMV increase\u003c/em\u003e. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://economictimes.indiatimes.com\u003c/span\u003e\u003cspan address=\"https://economictimes.indiatimes.com\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eForrester Research. (2023). \u003cem\u003eE-commerce in India: A strategic overview\u003c/em\u003e. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.forrester.com\u003c/span\u003e\u003cspan address=\"https://www.forrester.com\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMcKinsey \u0026amp; Company. (2024). \u003cem\u003eGlobal beauty market insights: Consumer shifts and strategic opportunities\u003c/em\u003e. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.mckinsey.com\u003c/span\u003e\u003cspan address=\"https://www.mckinsey.com\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMcKinsey \u0026amp; Company. (2024). \u003cem\u003eE-commerce growth and profitability trends\u003c/em\u003e. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.mckinsey.com\u003c/span\u003e\u003cspan address=\"https://www.mckinsey.com\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNielsenIQ. (2023). \u003cem\u003eIndia\u0026rsquo;s beauty and personal care market outlook\u003c/em\u003e. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://nielseniq.com\u003c/span\u003e\u003cspan address=\"https://nielseniq.com\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNielsenIQ. (2023). \u003cem\u003eThe rise of beauty e-commerce in India\u003c/em\u003e. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://nielseniq.com\u003c/span\u003e\u003cspan address=\"https://nielseniq.com\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNykaa. (2024). \u003cem\u003eNykaa Beauty Summit Report 2024\u003c/em\u003e. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.nykaa.com\u003c/span\u003e\u003cspan address=\"https://www.nykaa.com\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePlos One. (2022). \u003cem\u003eThe impact of advertising on impulsive buying: A behavioral economic perspective\u003c/em\u003e. Plos One, 17(8), e0271839. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1371/journal.pone.0271839\u003c/span\u003e\u003cspan address=\"10.1371/journal.pone.0271839\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePwC India. (2023). \u003cem\u003eThe digital future of Indian retail: Consumer behavior insights\u003c/em\u003e. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.pwc.in\u003c/span\u003e\u003cspan address=\"https://www.pwc.in\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRedSeer Consulting. (2023). \u003cem\u003eE-commerce festive season report: India 2023\u003c/em\u003e. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://redseer.com\u003c/span\u003e\u003cspan address=\"https://redseer.com\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRedSeer Consulting. (2023). \u003cem\u003eThe evolving Indian e-commerce market: Insights and trends\u003c/em\u003e. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://redseer.com\u003c/span\u003e\u003cspan address=\"https://redseer.com\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRos\u0026aacute;rio, A., \u0026amp; Raimundo, R. (2021). \u003cem\u003eLiterature review on marketing strategies in e-commerce\u003c/em\u003e. Journal of Marketing Research, 58(5), 895\u0026ndash;916. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1509/jmr.18.0416\u003c/span\u003e\u003cspan address=\"10.1509/jmr.18.0416\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eStatistics Canada. (2022). \u003cem\u003eTrends in retail e-commerce versus in-store sales post-pandemic\u003c/em\u003e. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.statcan.gc.ca\u003c/span\u003e\u003cspan address=\"https://www.statcan.gc.ca\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eVoxPopMe. (2023). \u003cem\u003eSocial proof and influencer-driven e-commerce growth\u003c/em\u003e. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.voxpopme.com\u003c/span\u003e\u003cspan address=\"https://www.voxpopme.com\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWorld Economic Forum. (2023). \u003cem\u003eThe future of e-commerce: A global overview\u003c/em\u003e. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.weforum.org\u003c/span\u003e\u003cspan address=\"https://www.weforum.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Behavioural economics, Consumer decision-making, Scarcity effect, Online retail, Pink Friday Sale, India, Anchoring, Hyperbolic discounting","lastPublishedDoi":"10.21203/rs.3.rs-7685755/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7685755/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eTime-bound e-commerce promotions have emerged as critical tools for influencing consumer behaviour, particularly in emerging markets. This study investigates the application of behavioural economics principles within Nykaa\u0026rsquo;s Pink Friday Sale, a major online retail event in India\u0026rsquo;s beauty and personal care sector. Using secondary data from Q3FY22 to Q3FY24, the research applies a behavioural framework\u0026mdash;encompassing scarcity, anchoring, loss aversion, hyperbolic discounting, and the endowment effect\u0026mdash;to analyse the relationship between marketing strategies and consumer responses. The analysis reveals that scarcity cues and urgency mechanisms significantly boost early conversions; strike-through pricing increases average order value; \u0026ldquo;last chance\u0026rdquo; prompts enhance final-day sales; and exclusive bundles lead to faster sell-out rates than individual items. These findings support the practical effectiveness of psychological nudges in driving e-commerce performance and extend behavioural economics theory to a high-growth, non-Western retail context.\u003c/p\u003e\u003cp\u003eHowever, the findings are subject to limitations including reliance on secondary data sources and the absence of direct consumer-level tracking or experimental validation.\u003c/p\u003e","manuscriptTitle":"Necessity or Nudge? Behavioural Economics Insights from Nykaa’s Pink Friday Sale","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-30 09:01:18","doi":"10.21203/rs.3.rs-7685755/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"33dd8c5c-0b2e-447a-9c1f-51d0deae940f","owner":[],"postedDate":"September 30th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-10-03T15:08:39+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-30 09:01:18","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7685755","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7685755","identity":"rs-7685755","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}