Promotheus: An End-to-End Machine Learning Framework for Optimizing Markdown in Online Fashion E-commerce

TL;DR

This paper introduces two end-to-end machine learning systems, Ithax and Promotheus, for optimizing markdown strategies in online fashion e-commerce, significantly improving profitability over manual methods.

Contribution

The paper presents novel systems for markdown optimization that operate without demand estimation and with full elasticity modeling, demonstrating real-world effectiveness.

Findings

Promotheus achieves 86% profit improvement over manual strategies.

Ithax achieves 79% profit improvement, enabling cold start deployment.

Both systems are successfully deployed at ASOS.com.

Abstract

Managing discount promotional events ("markdown") is a significant part of running an e-commerce business, and inefficiencies here can significantly hamper a retailer's profitability. Traditional approaches for tackling this problem rely heavily on price elasticity modelling. However, the partial information nature of price elasticity modelling, together with the non-negotiable responsibility for protecting profitability, mean that machine learning practitioners must often go through great lengths to define strategies for measuring offline model quality. In the face of this, many retailers fall back on rule-based methods, thus forgoing significant gains in profitability that can be captured by machine learning. In this paper, we introduce two novel end-to-end markdown management systems for optimising markdown at different stages of a retailer's journey. The first system, "Ithax", enacts a rational supply-side pricing strategy without demand estimation, and can be usefully deployed as a "cold start" solution to collect markdown data while maintaining revenue control. The second system, "Promotheus", presents a full framework for markdown optimization with price elasticity. We describe in detail the specific modelling and validation procedures that, within our experience, have been crucial to building a system that performs robustly in the real world. Both markdown systems achieve superior profitability compared to decisions made by our experienced operations teams in a controlled online test, with improvements of 86% (Promotheus) and 79% (Ithax) relative to manual strategies. These systems have been deployed to manage markdown at ASOS.com, and both systems can be fruitfully deployed for price optimization across a wide variety of retail e-commerce settings.