AI Case Study

"Stitch Fix has combined the expertise of personal stylists with the insight and efficiency of artificial intelligence to analyse data on style trends, body measurements, customer feedback and preferences to arm the human stylists with a culled down version of possible recommendations. This helps the company provide its customers with personalized style recommendations that fit their lifestyle and budgets.

With this data, we try to understand clients' states and their needs when in those different states. We can then detect changes in state and consider possible triggers. This process by itself can lead to insights that help us keep our clients happier.

And once we define and understand states, and detect and understand clients' transitions between them, we can develop state transition matrices and Markov chain models that allow us to study system-level effects.

One of the many uses of these Markov chain models is to anticipate future demand, which is important because we often need to buy inventory months before it arrives at the warehouses. We must also ensure that we have the right number of resources and human stylists available at the right times.

Meeting future demand is just one of our inventory management challenges: we must also allocate inventory appropriately to different warehouses, and occasionally donate old inventory to make room for new styles. We can use algorithms to help us with these processes."