LG Electronics Personalization & value
The right category is only half the answer.
Category-aware spend predictions that connect product relevance with a suitable price level, giving teams a more useful starting point for personalized merchandising.
Built the category-spend capability and connected its outputs to the customer intelligence workflow.
Production customer model
What price level fits this purchase?
Expected spend conditional on a category purchase, plus a price-preference tier where appropriate, to guide product selection and category audience planning.
Conceptual workflowThe business problem
A customer's overall value does not describe what they would spend in a particular category. Treating every category alike can distort audience priorities and lead to poorly matched product recommendations.
What I built
Developed a category-aware spend model that builds on customer purchase context and category pricing patterns.
Translated predictions into category-specific spending estimates and entry, mid-range, or premium preferences where the data supports that distinction.
Integrated category spend with customer value and next-purchase ranking to make audience planning sensitive to both relevance and value.
How I evaluated it
Compared predictions with subsequent category purchases. Checked aggregate spend, within-category ranking, and whether predicted price tiers corresponded to different observed spending patterns.
Built to operate
Recurring scoring integrated with upstream customer models, with checks before publishing new outputs and a prepared retraining and evaluation workflow.
What the work enables
Historical validation showed more informative category-level spending estimates than a single customer-wide spend value, and meaningful differences in observed spend between predicted price tiers.