DATA SCIENCE | E-Commerce | U.S.

Inventory Model Reduced Stockout Risk

An e-commerce retailer was struggling to balance inventory availability with cash tied up in slow-moving products. We built a demand model that combined historical sales, seasonality, promotions, and product category trends to improve purchasing decisions.

Measured outcomes

21% Stockout risk reduction
16% Excess inventory reduction
2 yrs Sales history modeled

Implementation summary

Render Analytics connected the relevant systems, data signals, workflows and reporting logic so the team could make decisions from cleaner evidence and focus on measurable outcomes.