Case · Retail
E-commerce — pre-simulating price & promotion ROI
// PERSONA
Yang, BI Lead — multi-category e-commerce
// INDUSTRY
Retail / E-commerce
// DATASET
case_06 · sku_price_elasticity.csv · 48,000 SKUs × 24 months
PROBLEM
The Problem
Pricing and promotion decisions across 48K SKUs run weekly, but "what if I cut price by 5% — what happens to revenue, turnover, and margin?" had no cross-variable answer. Regression alone could not reverse-solve *how much* to move each lever.
COMING SOON
APPROACH
XimTier Approach
Per-SKU price elasticity, inventory turnover, and seasonality are unified via Reverse What-If. Set a revenue target, and the system returns the optimal price / promotion / inventory mix — each recommendation ships with expected impact, confidence interval, and risk, so promo ROI is validated *before* launch.
COMING SOON
OUTCOMES
Outcomes
OUT / 01
Pre-simulate price changes (24h → 12min)
OUT / 02
Inventory turnover +18% YoY
OUT / 03
Promo ROI forecast accuracy 89%
OUT / 04
Stock-out rate −24% simultaneously
⚠ Example data — fine-tuned on customer data at deployment.