| Take the 1st Steps toward Data-informed |
Case Types: Briefs on Analytics + Big DataOutline strategic actions & guide dialogue
What Happened there?
Now: Stitch Fix is an online personal styling service in the United States and United Kingdom. It uses recommendation algorithms and data science to personalize clothing items based on size, budget and style. The company was founded in 2011 and had an initial public offering in 2017 with a valuation of $1.6 billion
Case: Stitch Fix created the Netflix of Clothing Recommendation through a combination of effective surveying, data driven approach, and
Key Phrase: Great people and great algorithms together are better than the best people or the best machine learning alone.
| Context | They send clothes you like and you send them back. They data and algorithms to build client personas based on comprehensive intake survey + online activity data Cut out Brick and Mortar + works with clothes suppliers, providing valuable insight to suppliers based on customer data |
| Action | #1 Resilient woman – The Katrian Lake was often rejected based on: Woman CEO“No market” Investor + steward bias And yet she took “Survey Monkey” + excel + personal recommendation company #2 Be Netflix Not Blockbuster – After seeing Netflix’s rise, 10 years into existence, Lake partnered algorithms decision support tools w/ Human led client engagement |
| Results | The data Staff spoke with the CEO regularly, not a CTO or other unit. This sends a message about approach and values. Client profiles and past actions guide algorithm & stylist confirms/ inquires clientLower return rates + longer client lifecycle The algorithms and data are used internally to increase efficiency (trend prediction, tracking inventory or event performance, audience segmentation for marketing campaigns. Stylist feel empowered by insights of client habits and ML recommendation to propose items above clients “price range” due to persona Improved client engagement leads to trust |
| Lessons | Don’t forget the people – There will always be critical and niche parts of the business that your people will always be better at doing. Start from there and build out your data unit. |
