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Visual AI for Catalog “Cold Start” and “Out of Stock” Problems

Applicable Segment(s):

Fashion & Apparel, Speciality

Impacted Function(s):

Commerce

Solution Area:

DeepRecs Visual AI

Visual AI for Catalog "Cold Start" and "Out of Stock" Problems

Company

An American multinational retail company operating a chain of hypermarkets, department stores, and grocery stores.

The Challenge

As a big department store, they refreshed their catalog, especially the apparel category, daily. They also run out of popular products quite often. So, they needed a strategy that solved the cold-start problem with new products and provided relevant alternatives when a product went out of stock.

The Approach

  • Using Algonomy's Image Similarity models powered by Visual AI, they were able to see immediate benefits.
  • Each seed considers the entire catalog. The current system can stratify the catalog if labels are provided (eg; product_id, category_id).
  • The model architecture is a variant of ResNet, which is a popular convolutional neural network architecture for transfer learning on images within the recommender systems domain.

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