INSTAGRAM MARKETING STRATEGY OF THE NATURAL COSMETICS BRAND VIGOR COSMETIQUE NATURELLE: A DATA-DRIVEN ANALYSIS OF CONTENT AND AUDIENCE ENGAGEMENT METRICS

Authors

  • Tetiana KOZLOVSKA

DOI:

https://doi.org/10.31379/sed.1.4.2025.37

Keywords:

social media marketing, Instagram marketing, engagement rate, digital marketing, data-driven marketing, visual content analysis

Abstract

This article presents the findings of a comprehensive empirical study examining the Instagram marketing strategy of Vigor Cosmetique Naturelle, a Ukrainian natural cosmetics brand. The study is based on the analysis of 925 posts published between August 2023 and April 2024, employing descriptive statistics, correlation analysis, principal component analysis (PCA)-based clustering, and multimodal visual content analysis. The key performance indicators (KPIs) under examination include the Engagement Rate (ER%), average likes and comments, as well as post-level attributes such as content type (giveaway vs. regular post), colour palette, colour warmth, aesthetic quality, compositional complexity, and seasonal-temporal distribution. The findings indicate that the account's mean ER% of 0.05% falls considerably below industry benchmarks of 1–3% for the beauty segment in the Central and Eastern European region. A comparative analysis of giveaway and regular posts revealed a short-term 1.7-fold increase in engagement; however, this uplift does not translate into sustained audience growth. Temporal analysis identified moderately pronounced seasonality, with engagement peaks in August 2023 and March 2024, as well as a statistically significant predominance of ER% on Fridays (0.07% versus the overall mean of 0.05%). The radar profile of visual content attributes demonstrated a high degree of similarity between top-50% and bottom-50% posts, suggesting a limited role of individual visual characteristics in driving engagement and pointing to a deficit of content differentiation. Based on these findings, the study formulates practical recommendations for optimising the brand's content strategy, including strengthening the dialogic dimension of posts, expanding the colour palette, incorporating storytelling, and aligning the content plan with the identified temporal engagement patterns.

References

Alassafi, M. O., Alghamdi, W., Naveena, S. S., Alkhayyat, A., Tolib, A., & Ugli, I. S. M. (2023). Machine learning for predictive analytics in social media data. E3S Web of Conferences, 399, 04046. DOI:https://doi.org/10.1051/e3sconf/202339904046 [in English].

Basbeth, F., & Nardo, R. (2023). The role of user engagement and Instagram influencer in a corporate SNS account. In Studies in big data (pp. 55–63). DOI:https://doi.org/10.1007/978-3-031-42463-2_7 [in English].

Carmine, S., & De Marchi, V. (2022). Reviewing Paradox Theory in Corporate Sustainability Toward a Systems Perspective. Journal of Business Ethics, 184(1), 139–158. DOI:https://doi.org/10.1007/s10551-022-05112-2[in English].

Fu, C., Silalahi, A. D. K., Yang, L., & Eunike, I. J. (2024). Advancing SME performance: A novel application of the technological-organizational-environment framework in social media marketing adoption. Cogent Business & Management, 11(1). DOI:https://doi.org/10.1080/23311975.2024.2360509[in English].

Hootsuite. (2024). Social media trends 2024: Annual research report. Hootsuite Media Inc. [in English].

HypeAuditor. (2024). State of influencer marketing 2024: Annual report. HypeAuditor Research. URL: https://hypeauditor.com/resources [in English].

Ilyashenko, S. M., & Shypulina, Yu. S. (2022). Tsyfrovyi marketynh: pidruchnyk [Digital marketing: Textbook]. Universytetska knyha. [in Ukrainian].

Jia, Z. (2024). Psychological analysis of social media visual content based on image recognition algorithm. International Journal of Electrical and Electronics Engineering, 11(9), 196–204. DOI:https://doi.org/10.14445/23488379/ijeee-v11i9p117 [in English].

Kaur, J., Saini, S., Behl, A., & Poonia, A. (2024). Impact of digital storytelling on improving brand image among consumers. Journal of Promotion Management, 30(8), 1348–1376. DOI:https://doi.org/10.1080/10496491.2024.2403760 [in English].

Kotler, P., Kartajaya, H., & Setiawan, I. (2021). Marketing 5.0: Technology for humanity. Wiley. [in English].

Meta. (2024). Engagement and reach metrics on Meta platforms: Technical documentation. Meta Business Help Center. [in English].

Natorina, A. O. (2020). Instagram biznes-akaunt ryteilera: haidy ta KPI [Instagram business account of a retailer: Guides and KPIs]. Zenodo. DOI:https://doi.org/10.5281/zenodo.3678892 [in English].

Paper, D. J. (2020). Hands-on Scikit-Learn for machine learning applications: Data science fundamentals with Python. Apress. DOI:https://doi.org/10.1007/978-1-4842-5373-1 [in English].

Prymak, T. O. (2023). Marketynhovi komunikatsii u sotsialnykh merezhakh: teoriia ta praktyka [Marketing communications in social media: Theory and practice]. KNEU. [in English].

Reshetnikova, O. V. (2022). Kontent-marketynh u tsyfrovomu seredovyshchi: pidkhody do otsiniuvannia efektyvnosti [Content marketing in the digital environment: Approaches to efficiency assessment]. Marketynh v Ukraini, (4), 45–58. DOI:https://doi.org/10.31891/dsim-2026-13(17) [in English].

Ranjan, M., Barot, K., Khairnar, V., Rawal, V., Pimpalgaonkar, A., Saxena, S., & Sattar, A. (2023). Python: Empowering data science applications and research. Journal of Operating Systems Development & Trends, 10, 27–33. DOI:https://doi.org/10.37591/joosdt.v10i1.576 [in English].

Rival IQ. (2024). 2024 social media industry benchmark report. URL:https://www.rivaliq.com/blog/social-media-industry-benchmark-report [in English].

Socialinsider. (2024). Instagram benchmarks 2024: A comprehensive industry analysis. Socialinsider Reports. URL:https://www.socialinsider.io [in English].

Tian, J. (2023). Research on the marketing strategy of beauty brands in the background of social media. In Advances in economics, business and management research (pp. 1267–1277). DOI:https://doi.org/10.2991/978-94-6463-098-5_144 [in English].

Zozuliov, O. V., & Tsarova, T. O. (2021). Systema marketynhovykh modelei tovaru [System of marketing models of a product]. Marketing and Digital Technologies, 5(3), 6–17. [in English].

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Published

2025-04-28

How to Cite

KOZLOVSKA, T. (2025). INSTAGRAM MARKETING STRATEGY OF THE NATURAL COSMETICS BRAND VIGOR COSMETIQUE NATURELLE: A DATA-DRIVEN ANALYSIS OF CONTENT AND AUDIENCE ENGAGEMENT METRICS. Society. Economy. Digitalization, 1(4), 46–60. https://doi.org/10.31379/sed.1.4.2025.37

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Section

Information systems and technologies as determinants of the digital economy