"Last year, we only had two price reductions and there was no discernible difference in sell-through between the two. This year we have four main buckets, and have found that the two discount levels that drive the best sell-through are 20% and 40% …it could mean that potentially we do not need to markdown at 50% at all."
The company had been relying upon historical sales data and ad hoc estimates to drive pricing strategy and markdown decisions. As a result, pricing lacked localization, nor was easily adaptable to other market variables, creating gluts of excessively aged inventory. In addition, the company had questions about which “buckets” of percentage markdowns delivered the fastest sell-through while preserving margins.
After extended consultation, the antuit.ai team leveraged AI-driven insights to deliver integrated forecasting and elasticity models that optimized markdown pricing, incorporating multiple key variables. This led to a refined, data-driven markdown structure which would discourage stores from marking down clearance items too steeply—while accelerating overall sell-through by 10% within just one year.