1. FlipShop
Group 5
Andrea Zvinakis
Katherine Chen
Molly Mackinlay

2. 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

3. 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

4. Reframing the problem
How might 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) 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.

7. 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

8. 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

9. Use Scenario

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:
- 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

12. Evolution
Magic mirror in dressing 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. The End
Questions?