Abstract
Effective performance tracking is pivotal for brands striving to excel in the dynamic world of dermocosmetics. This study introduces a system designed to monitor the sales performance of two new premium dermocosmetic brands entering the pharmacy channel of a global FMCG company. By emphasizing the need for understanding customer behavior and tailoring sales strategies, the research integrates RFMV (Recency, Frequency, Monetary, and “V” for in-pharmacy sales influencing factors) analysis as a powerful tool for customer segmentation. The study employs RFMV analysis and K-means clustering to classify pharmacies into three distinct segments: “Loyal Customers,” “Potential Loyal Customers,” and “Risk Customers.” Strategic insights are provided for each segment, offering practical recommendations to enhance sales performance and refine marketing tactics. This approach delivers actionable insights for optimizing product performance and strategic decision-making in a competitive market.
| Original language | English |
|---|---|
| Title of host publication | Sustainable Green Conversion - Selected Papers from ISPR 2024 |
| Editors | Numan M. Durakbasa, Kemal Güven Gülen |
| Publisher | Springer Science and Business Media Deutschland GmbH |
| Pages | 435-448 |
| Number of pages | 14 |
| ISBN (Print) | 9783031836107 |
| DOIs | |
| Publication status | Published - 2025 |
| Event | 24th International Symposium for Production Research, ISPR 2024 - Budva, Montenegro Duration: 10 Oct 2024 → 12 Oct 2024 |
Publication series
| Name | Lecture Notes in Mechanical Engineering |
|---|---|
| ISSN (Print) | 2195-4356 |
| ISSN (Electronic) | 2195-4364 |
Conference
| Conference | 24th International Symposium for Production Research, ISPR 2024 |
|---|---|
| Country/Territory | Montenegro |
| City | Budva |
| Period | 10/10/24 → 12/10/24 |
Bibliographical note
Publisher Copyright:© The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.
Keywords
- Customer segmentation
- Market optimization
- Marketing analytics
- Performance monitoring
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