Part 2/11:

For over a decade, Nikita has been heavily engaged with customer segmentation, primarily employing traditional clustering methods such as RFM (Recency, Frequency, Monetary value) models. These models categorize customers based on their purchasing patterns and loyalty metrics, enabling retailers to identify top-tier frequent buyers and potential churners. While effective, these techniques often lack the depth needed to personalize marketing efforts accurately.

As her career progressed and AI technology matured, Nikita recognized the need to go beyond basic segmentation. The goal was to develop a more nuanced understanding of customers' life stages—such as whether they are parents of infants, teenagers, singles, couples, or seniors—to tailor promotional strategies more effectively.