Data Science at StitchFix

March 17, 2017
By

(This article was first published on Revolutions, and kindly contributed to R-bloggers)

If you want to see a great example of how data science can inform every stage of a business process, from product concept to operations, look no further than Stitch Fix's Algorithms Tour. Scroll down through this explainer to see how this personal styling service uses data and statistical inference to suggest clothes their customers will love, ship them from a nearby warehouse (already stocked thanks to demand modeling), and incorporate customer feedback and designer trends into the next round of suggestions.

The design of the Tour is interactive and elegant, and clearly someone put a lot of work into it. It's a great example of simplifying the detail of data science into a format where the impacts are immediately apparent. Communicating the benefits of data science to non-experts is a key skill of any data scientist, and dialing down on the complexity, while not dumbing down the science, is key to that communication.

From the Tour, we can see that Stitch Fix's data science is far from simple. Their methods aren't just black-box machine learning techniques: rather, they are using statistical inference to figure out why customers like particular products (or why operational strategies are efficient or not) rather than simply predicting what will happen. This is all driven by a sophisticated data science platform, that enables the team to employ techniques like Generalized Additive Models implemented in R, or Natural Language Processing implemented in Python. Check out their MultiThreaded blog for more details on data science applications at Stitch Fix, and be sure to check out the Algorithms Tour linked below.

Stitch Fix MultiThreaded: Algorithms Tour

 

To leave a comment for the author, please follow the link and comment on their blog: Revolutions.

R-bloggers.com offers daily e-mail updates about R news and tutorials on topics such as: Data science, Big Data, R jobs, visualization (ggplot2, Boxplots, maps, animation), programming (RStudio, Sweave, LaTeX, SQL, Eclipse, git, hadoop, Web Scraping) statistics (regression, PCA, time series, trading) and more...



If you got this far, why not subscribe for updates from the site? Choose your flavor: e-mail, twitter, RSS, or facebook...

Comments are closed.

Sponsors

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)