Abstract

The case discusses how Stitch Fix, an online personal styling service founded by Katrina Lake (Lake), employed algorithms to select apparel for its customers according to their style, fit, and price preferences. In the course of recommending apparel for its customers, the company employed algorithms related to, among others, collaborative filtering and mixed-effects modeling. The case also describes how human beings were used to augment algorithms in styling customers. It also points out how the algorithms learnt from the feedback given by the customers for a specific shipment to select styles for subsequent shipments. The case describes how algorithms were employed by the company to perform other key tasks such as allocating a shipment request to a warehouse and computing the amount of and the type of inventory that the company should purchase. The case goes on to describe how machine learning algorithms were employed by Stitch Fix in new product development – the company’s in-house brands eventually contributed over 20% to its turnover. Data mining was employed by Stitch Fix to enter new categories such as plus size for women and premium-brand offerings. The case also describes the challenges faced by the company such as limits to the amount of shopping that its customers could do, intense competition from e-commerce players such as Amazon, and increasing advertising expenses eating into the company’s profits.

Learning Objectives

The case is structured to achieve the following Learning Objectives:

• Understand how algorithms can be employed to aid various operations in a company, including for making personalized recommendations and aiding new product development.
• Identify the areas where human capabilities can augment algorithms.
• Understand how Stitch Fix employed data to expand its business.

Keywords

Algorithms; Fashion; Online personal styling service; Big data; e-commerce; Business Analytics; Marketing Analytics; Service marketing; Consumer behavior; Natural language processing; Customer’s level of satisfaction; Human-Machine Algorithms; Warehouse assignment ; Inventory management; Entrepreneurship; Blue Ocean Strategy