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"The Geek's Guide to Merchandising, Warehousing & Operating," Stitch Fix >> Mike Smith [COMMERCISM 2014]
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"The Geek's Guide to Merchandising, Warehousing & Operating," Stitch Fix >> Mike Smith [COMMERCISM 2014]

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DATA BLITZKRIEG: THE GEEK'S GUIDE TO MERCHANDISING, WAREHOUSING & OPERATING, Mike Smith, COO, Stitch Fix

DATA BLITZKRIEG: THE GEEK'S GUIDE TO MERCHANDISING, WAREHOUSING & OPERATING, Mike Smith, COO, Stitch Fix

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    "The Geek's Guide to Merchandising, Warehousing & Operating," Stitch Fix >> Mike Smith [COMMERCISM 2014] "The Geek's Guide to Merchandising, Warehousing & Operating," Stitch Fix >> Mike Smith [COMMERCISM 2014] Presentation Transcript

    • COMMERCISM   March  21,  2014        The  Geek’s  Guide  to  Merchandising,  Warehousing  and  OperaAng  
    • 1 “There is a tectonic shift going on in an industry (retail) that represents a large chunk of GDP and I’m not sure the industry knows how deep or fast it’s going to be” – a recent entrepreneur Most companies at this conference will FAIL to capitalize on the tectonic shifts because they won’t truly differentiate Introduc)on  
    • 2 Agenda Overview of Stitch Fix (very quick) Tactics for success Real life examples of using data with high impact What I wish I knew?
    • 3 S)tch  Fix  brings  scalable  personaliza)on  to  the  mass  market  
    • 4 Proprietary  tools  blend  the  science  of  data  with  the  art  of  styling  to   achieve  a  truly  personalized  customer  experience   •  Leverage  structured  data   •  Simultaneously  weight  many   features       •  Leverage  the  unstructured  data   (e.g.  pinterest,  images,  video,  etc.)   •  Foster  relaAonships  (notes,   explanaAon,  style  Aps,  etc.)   Styling  Algorithm   Stylists   12345 67891 32165 85236 42345 67891 32165 85236 12345 67891 32165 85236 12345 67891 32165 f (Ÿ)
    • 5 Agenda Overview of Stitch Fix (very quick) Tactics for success Real life examples of using data with high impact What I wish I knew?
    • 6 Four recommended tactics for success •  Invest in data science •  Recruit a data science leader that works well with functional leaders in business •  Ensure that metrics coming from data science are true and meaningful levers for driving business impact •  Develop an approach for HOW TO DO IT – the “It” being making data a differentiator 1 2 3 4
    • 7 Tactic 1: Invest in data science Investing in data science is not just investing in “analytical” people – it requires understanding the art & science mix Find the Eigen value Which image has a dog? Impact of tactic: Higher AOV
    • 8 Four critical rules to follow when hiring a great data science leader… •  Candidates can’t operate in a box •  Should not have a big ego •  Should be a great communicator •  Data science should report directly to founder / CEO Tactic 2: Recruit a great data science leader Impact of tactic: data science becomes an extension of business functions enabling greater accountability on P&L levers 1 2 3 4
    • 9 Too  many  data  points  DON’T  drive  impact  –  focus  on  those  that  do!   Tac)c  3:    Ensure  data  drives  real  business  impact   Impact of tactic: better contribution margin and LTV How much inventory has been stolen by employees? How do we get the bottom five customer service agents to go from 8 emails per hour to 10 emails per hour?           Data can help answer these questions, but they are low impact Data should be leveraged to answer questions with high business impact Are there high LTV “Romantic” customers that have a lower quality fix score? What is the true “quality” of the inventory relative to our current client mix? Do we have enough medium “Classic” dresses in inventory?          
    • 10 How do you do it if you don’t have the leader of algorithms for Google, Pandora, Amazon or Netflix? How do you know what questions to ask? Tactic 4: Develop an approach for HOW TO DO IT Impact of tactic: data that we collect and use drives improvement in our business Key challenges for startups… …are addressed with the following approach Start with end in mind •  What do you think the drivers of performance? •  What are the key metrics? Truly put yourself in the customer’s shoes •  How do you shop? •  What are the most important things to you?
    • 11 Agenda Overview of Stitch Fix (very quick) Tactics for success Real life examples of using data with high impact What I wish I knew?
    • 12 Real life example: Merchandising / inventory management ~30 questions that provide value to both the customer and to us really help us manage capital efficiently Sample range of annualized inventory turns
    • 13 Real  life  example:    Opera)ons   Strategic  handling  of  returns  or  restocked  items   The Old World: no organization or ability to prioritize returns The New World: bags prioritized by impact on inventory High priority returns – processed first Low priority returns – processed last
    • 14 Agenda Overview of Stitch Fix (very quick) Tactics for success Real life examples of using data with high impact What I wish I knew?
    • 15 What  I  wish  I  knew  …  three  key  things   •  For now, we don’t see value in measurements •  This business is very capital intensive •  Data can really risk reduce the “art” side of retail 1 2 3