The old saying, “look good, feel good,'' fits Stitch Fix perfectly. The direct-to-consumer, online personal styling service has boomed due to its ability to not only match consumers with trendy and comfortable clothes, but to make it a personalized experience for each buyer.

“At the end of the day, we want to be rooted in personalization. First and foremost, it's important for us that [consumers] not only come to Stitch Fix to complete a transaction, but that you really think about us as your partner style.”

From curating stylish experiences, to matching each individual with their own personal stylist, Stitch Fix and taken eCommerce and the subscription model to the next level. On this episode of IT Visionaries, Tatsiana Maskalevich, the Director of Data Science at Stitch Fix, takes listeners into the algorithms that help curate those experiences and the science behind it all.

Main Takeaways

• Know Your Data: With so many avenues to collect data on the internet, the collection process is not the difficult part. The hardest part is how you turn your data into actionable insights that can benefit your customers’ experience. In order to manage your data appropriately, you must be constantly creating feedback loops so you can best understand what is working and what is not working.
• It’s a Preference Thing: The customer experience is the number one pillar for any successful company. When you are creating curated experiences for your customers, you need to constantly be listening to what works for them and what does not work. Create a great experience by constantly giving your customers reasons to engage with your platform through quizzes and games or other interactive features.
• Rooted in Data:  One of the keys to building a successful data-centric platform is through the individuals constructing it. The algorithm you construct has to accomplish two things: It needs to continuously be learning about the person inputting that data, and it needs to continuously be relaying information back to the source. Focus on the foundation and infrastructure of your algorithm first, then experience second.

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