“EyeFit” Personal Shopping System Final Presentation December 6, 2005 Lara Zielin, Nadia Bechler, and Kristen Flory

Brief History  Project Goal  Field Observations  Current Technology  Our Shopping Trip (testing the technology)  Transformed Concept

Prototype  Handheld, network- capable device  Affordances that must be preserved Seeing / Feeling Trying on items Freedom to browse other items  New affordances Previewing Recommending Retaining / Storing Recording  Building a user account

Let’s Go Shopping EyeFit System demo by three different types of shoppers  The Frequent Shopper  The “Hate-to-Shop” Shopper  The Gift Shopper

The Device Features Barcode Scanner Digital Voice Recorder Function Stylus Clip and cord Screen

The Frequent Shopper Custom-built 3-D model Goals for current trip Current wardrobe Shopping history—by trip/item Wish list “Helper” options Modeled clothing information Dressing room and check out feature

Recommendations Information about fit for specific body types Suggestions for outfits, how to wear it Options based on other users’ input

The “Hate-to-Shop” Shopper Chosen item information Goals for current trip Minimal shopping history “Helper” options Dressing room and check out feature Requires minimal entry of user account information!

The Gift Shopper Can be viewed online or in store Sorted lists Same recommender affordances

The Retailer Features & Benefits Sync shopper information: update shoppers wardrobe; view purchases; see what was tried on Gather marketing and polling data Tailor merchandise ordering to clientele Offer customer incentives

EyeFit Account Maintenance Features & Benefits Build & edit model Build & maintain wardrobe Add comments Create & edit “friend” access for wish list

The EyeFit System User Account Comments Server Device Store Kiosk Your Computer Store Accounts

Next Steps/ Future Features Features & Benefits Upload to other devices Expanded comparison shopping Possibilities for non-clothing items Add comments Customized catalog of merchandise per store to individual clientele preferences (this could be an e-catalog) A recommender system that continues “learning”! More information at your fingertips! An improved shopping experience!