Leveraging the Power of Images in Managing Product Return Rates

Daria Dzyabura, Siham El Kihal (), John Hauser () and Marat Ibragimov ()
Additional contact information
Siham El Kihal: Frankfurt School of Finance & Management, Germany
John Hauser: MIT Sloan School of Management, USA
Marat Ibragimov: MIT Sloan School of Management, USA

No w0259, Working Papers from New Economic School (NES)

Abstract: In online channels, products are returned at high rates. Shipping, processing, and refurbishing are so costly that a retailer's profit is extremely sensitive to return rates. In many product categories, such as the $500 billion fashion industry, direct experiments are not feasible because the fashion season is over before sufficient data are observed. We show that predicting return rates prior to product launch enhances profit substantially. Using data from a large European retailer (over 1.5 million transactions for about 4,500 fashion items), we demonstrate that machine-learning methods applied to product images enhance predictive ability relative to the retailer’s benchmark (category, seasonality, price, and color labels). Custom image-processing features (RGB color histograms, Gabor filters) capture color and patterns to improve predictions, but deep-learning features improve predictions significantly more. Deep learning appears to capture color-pattern-shape and other intangibles associated with high return rates for apparel. We derive an optimal policy for launch decisions that takes prediction uncertainty into account. The optimal deep-learning-based policy improves profits, achieving 40% of the improvement that would be achievable with perfect information. We show that the retailer could further enhance predictive ability and profits if it could observe the discrepancy in online and offline sales.

Keywords: machine learning; image processing; product returns (search for similar items in EconPapers)
Pages: 34 pages
Date: 2019-09-03
New Economics Papers: this item is included in nep-big and nep-cmp
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Citations: View citations in EconPapers (1)

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https://www.nes.ru/files/Preprints-resh/WP259.pdf (application/pdf)

Related works:
Journal Article: Leveraging the Power of Images in Managing Product Return Rates (2023)
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Persistent link: https://EconPapers.repec.org/RePEc:abo:neswpt:w0259

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