Abstract
Pricing is a key lever used by e-commerce companies to achieve “growth with profitability”. Given the huge catalog size in e-commerce, most products have very close substitutes and complements. These complementary/substitute products result in influencing the demand for one another. Moreover, in the context of fashion, the utility of a product is mostly subjective. In categories like electronics, it’s relatively easy to define the utility of a product based on its attributes, but the same is not directly applicable to fashion. Products with similar attributes can have different utilities for the customer and therefore can be priced differently. Taking these things into consideration we base our pricing strategy on the following 3-stage decision-making process: 1) identifying the items which influence each other 2) building demand models that include effects of demand transference 3) joint optimization of the prices to achieve revenue or profit margin targets. We discuss our contributions to building a real-world system that implements these 3 stages in the specific context of fashion e-commerce. Fashion e-commerce has its nuances when it comes to pricing compared to general e-commerce and we explain how we dealt with these difficulties. Moreover, in addition to the formulations, we also describe challenges faced in building working systems that scale to millions of products and hundreds of categories. In addition, we describe a unique approach to quantifying the dollar benefit under scenarios where true A/B testing is not possible for legal reasons. Lastly, we explain how this work has resulted in significant incremental revenue for a large fashion e-commerce company.
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Sarkar, S. et al. (2023). Joint Price Optimization Across a Portfolio of Fashion E-Commerce Products. In: Emmerich, M., et al. Evolutionary Multi-Criterion Optimization. EMO 2023. Lecture Notes in Computer Science, vol 13970. Springer, Cham. https://doi.org/10.1007/978-3-031-27250-9_32
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DOI: https://doi.org/10.1007/978-3-031-27250-9_32
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