Persona-Based Segmentation: Customer Data Mapping as the Foundation of Corporate Marketing Strategy (Case Study on Scarlett Whitening)

Authors:
raw_author_name: Jerry Heikal
raw_affiliation_string: Magister Managemen, Universitas Bakrie, Jakarta, Indonesia

Abstract: This research aims to analyze customer segmentation in energy resource companies using the K-Means Clustering method. In the era of increasingly fierce business competition, a deep understanding of customer preferences and behavior is crucial for companies to design effective marketing strategies. Customer data, including purchase frequency, customer service field, company type and geographic location, were collected and analyzed using the K-Means Clustering algorithm. The analysis results showed the formation of homogeneous customer groups, allowing the company to identify the distinctive characteristics of each group. Five main groups were formed from the processed customer data using SPSS. The first group consists of scarlett's facial wash lovers who are dominated by women with an average age of 31 years, earning an average income of Rp15 million per month who live outside Jakarta and work as private employees. This group recognizes the majority of scarlett products from Tiktok. The second group consists of scarlett serum lovers who are dominated by women with an average age of 32 years, earning an average income of IDR 23 million per month who live in South Jakarta and work as private employees. This group also recognizes the majority of scarlett products from Tiktok. The third group consists of scarlett's shower scrub lovers who are dominated by single women with an average age of 31 years, earning an average income of IDR 10 million per month who live in South Jakarta and work other than private employees. This group recognizes scarlett products mostly from Instagram. The fourth group consists of scarlett's body lotion lovers who are dominated by women with an average age of 32 years, earning an average income of IDR 19 million per month who live outside Jakarta and work as private employees. This group recognizes the majority of scarlett products from Instagram. The fifth group consists of scarlett's body scrub lovers who are dominated by women with an average age of 28 years, with an average income of IDR 6.5 million per month who live in South Jakarta and work as entrepreneurs. This group recognizes the majority of scarlett products from Tiktok. The implementation of marketing strategies based on the results of this analysis shows that Scarlett needs to use cluster 2 as its target segment in order to continue to increase its revenue. Because by choosing this cluster, Scarlett will find it easier to design its marketing strategy, namely by increasing social media strategies by involving creative content and collaboration on the Tiktok platform, offering promotions and special offers for customers who buy Serum. Scarlett could present a special bundle offer for the product or provide points that can be redeemed for further discounts or free products after reaching a certain amount and since cluster 2 is predominantly in the South Jakarta area, focus the marketing campaign in that area. Scarlett's value proposition lies in the use of brand ambassadors, digital marketing, product quality and brand trust. Thus, this study concludes that customer segmentation analysis using K-Means Clustering brings strategic benefits to scarlett sellers. A deeper understanding of customers enables sellers to improve the relevance of marketing strategies, achieve better customer satisfaction, and remain responsive to changes in the business environment.