FlipShop
    Group 5
 Andrea Zvinakis
 Katherine Chen
 Molly Mackinlay
The shopping experience...
Gauging your fit is difficult:

Inconsistent sizing between brands necessitates the
need to try on clothes in-person, which is often tiresome,
time-consuming or impossible to do


                    When I’m shopping I won’t try stuff on
                    because I hate going in the
                    dressing room.




                        It might end up not
                                                     Returns are often expensive to
                        fitting, but I’m too         mail, a hassle to complete, or
Anh Cao, 21-year-       lazy to return it.           forgotten about
old student
The shopping experience...
Gauging your fit is difficult:
                                                          “I don’t shop
Photographs are deceptive:                                online often--I’m
photo retouching, altered                                 too short but I
                                                          have a long
clothes                                                   torso, so I often
                                                          don’t know what
                                                          size to get."

                                 Polle,
                                 58-year-old consultant




                                 Photographs are
                                 unhelpful: most people
                                 don't have model
                                 bodies
Reframing the problem


How might we make the experience
of trying on clothes more efficient,
productive, and enjoyable?
Our focus:
 - In home vs in store
    -Where does the shopping interaction take place?
 - Individual vs social
    -Are there other people involved or is it private?
 - Personalized vs generalized
    -Is the application store or person specific?
 - Retrieval vs discovery
    -Is the application more suited to help the user find
something specific they want, or to help the user browse?
Target users
(1) Young women who are                       (2) Working mothers
too busy or poorly                            who buy clothes for
located to go shopping                        their family members
regularly




Michelle - 25-year-old trendy,
tech-savvy working
professional
Michelle loves shopping but doesn’t have        Betty - 45-year-old working mother
time to go during working hours, so             who does the shopping for her family
browses her favorite stores online while
bored at work and collects her finds on         Better has two sons ages 10 and 15. She does the
Pinterest boards to get her friends' advice     majority of their shopping, but they dislike trying
on them.                                        clothes on in dressing rooms so she spends a lot of
                                                time buying and returning clothes for them.
Process

We went through multiple design iterations
and created many design scenarios and
storyboards to better envision the details of
our product and diagnose possible
breakdowns, like accidental category
selection
Our solution

FlipShop turns your TV into a virtual dressing
room mirror using Kinect's motion sensors to
build up a 3-D representation of your body
Use Scenario
Instruments

              Personas: let the user reuse a
              filter or set of categories

              Closets: different styles and
              contents of closets given
              polymorphic filtering

              Personal shopper: the
              filtering process is reified through
              the conversations between the user
              and the personal shopper
Design Justification
Alternatives:
- Virtual mall: too complex and hard to navigate in Kinect
Justification:
- Our design lets you see fit accurately, personal shopper feels personalized,
found new need to buy for others accurately
Insights:
 - Make it "in your own closet"
 - Category narrowing took too long so have a personal shopper filter for you
using voice
- Enable the use case of mothers buying clothes for sons
Evolution



Magic mirror in dressing room
                                  Magic mirror in home




                                Buying for others accurately
   Personalized filtering
Moving Forward
Multi-modal input
 - Online shop on other modalities (tablet, laptop, mobile) and send to kinect to
try on smaller selection more efficiently
Scaling - extreme browsing
- Instead of having to flip through large collection of garments, able to see
many items at a glance
Style recommendations
 - Enable personal shopper to make comments on ideal fit and style for body
type
Phone a friend
- Ability to call a friend and get feedback and advice on options
The End
 Questions?

377 presentation

  • 1.
    FlipShop Group 5 Andrea Zvinakis Katherine Chen Molly Mackinlay
  • 2.
    The shopping experience... Gaugingyour fit is difficult: Inconsistent sizing between brands necessitates the need to try on clothes in-person, which is often tiresome, time-consuming or impossible to do When I’m shopping I won’t try stuff on because I hate going in the dressing room. It might end up not Returns are often expensive to fitting, but I’m too mail, a hassle to complete, or Anh Cao, 21-year- lazy to return it. forgotten about old student
  • 3.
    The shopping experience... Gaugingyour fit is difficult: “I don’t shop Photographs are deceptive: online often--I’m photo retouching, altered too short but I have a long clothes torso, so I often don’t know what size to get." Polle, 58-year-old consultant Photographs are unhelpful: most people don't have model bodies
  • 4.
    Reframing the problem Howmight we make the experience of trying on clothes more efficient, productive, and enjoyable?
  • 5.
    Our focus: -In home vs in store -Where does the shopping interaction take place? - Individual vs social -Are there other people involved or is it private? - Personalized vs generalized -Is the application store or person specific? - Retrieval vs discovery -Is the application more suited to help the user find something specific they want, or to help the user browse?
  • 6.
    Target users (1) Youngwomen who are (2) Working mothers too busy or poorly who buy clothes for located to go shopping their family members regularly Michelle - 25-year-old trendy, tech-savvy working professional Michelle loves shopping but doesn’t have Betty - 45-year-old working mother time to go during working hours, so who does the shopping for her family browses her favorite stores online while bored at work and collects her finds on Better has two sons ages 10 and 15. She does the Pinterest boards to get her friends' advice majority of their shopping, but they dislike trying on them. clothes on in dressing rooms so she spends a lot of time buying and returning clothes for them.
  • 7.
    Process We went throughmultiple design iterations and created many design scenarios and storyboards to better envision the details of our product and diagnose possible breakdowns, like accidental category selection
  • 8.
    Our solution FlipShop turnsyour TV into a virtual dressing room mirror using Kinect's motion sensors to build up a 3-D representation of your body
  • 9.
  • 10.
    Instruments Personas: let the user reuse a filter or set of categories Closets: different styles and contents of closets given polymorphic filtering Personal shopper: the filtering process is reified through the conversations between the user and the personal shopper
  • 11.
    Design Justification Alternatives: - Virtualmall: too complex and hard to navigate in Kinect Justification: - Our design lets you see fit accurately, personal shopper feels personalized, found new need to buy for others accurately Insights: - Make it "in your own closet" - Category narrowing took too long so have a personal shopper filter for you using voice - Enable the use case of mothers buying clothes for sons
  • 12.
    Evolution Magic mirror indressing room Magic mirror in home Buying for others accurately Personalized filtering
  • 13.
    Moving Forward Multi-modal input - Online shop on other modalities (tablet, laptop, mobile) and send to kinect to try on smaller selection more efficiently Scaling - extreme browsing - Instead of having to flip through large collection of garments, able to see many items at a glance Style recommendations - Enable personal shopper to make comments on ideal fit and style for body type Phone a friend - Ability to call a friend and get feedback and advice on options
  • 14.