Customer Segmentation Research

A leading Crop Science company aimed to segment its market and identify which regions were most concentrated with specific farmer profiles. To achieve this, I gathered a wide range of data points including willingness to pay, behavioral patterns, trust levels, and other relevant variables. I applied K-Means clustering to this data, which resulted in four distinct segments: Early Adopters, Progressive Farmers, Traditional Farmers, and Hesitant Farmers. Three of the clusters were clearly differentiated, while one exhibited partial overlap, offering deeper insight into transitional behavior among farmer groups.
This segmentation enabled the company to:
1. Identify the dominant segment in each region
2. Tailor marketing campaigns based on unique segment characteristics
3. Understand behavioral differences across customer types
4. Prioritize which segment to target first

Moreover, it provided a strong foundation for financial forecasting, go-to-market strategy, and long-term planning.