1. ANDREW STEFFEY | LAURA SMITH | ALYSSA LLOYD
AEO PROPOSAL
ANDREW STEFFEY | LAURA SMITH | ALYSSA LLOYD

2. FOUNDATION GOAL Provide fit and feel in online shopping experience
Micro-moments
New/upcoming technology
So our foundational goal was a way for users to be confident that the fit and feel of the

3. AEO MOBILE APP RESEARCH
Demographics
15-25 years old
Students
Psychographics
Adventurous
Casual style
Tech-savvy
Alyssa

4. USER RESEARCH
Survey 1
77% of users not comfortable purchasing online due to lack of ability to get fit and feel virtually
Survey 2
Respondents explain major issues in online shopping:
Having to return clothes/return process
Not able to try on clothes
Questions they think about while shopping:
How will this product fit me?
What would this item look good with?
Can I show this and share this with my sister, mom, boyfriend?
Alyssa

5. KEY CONSIDERATIONS Provide fit and feel in online shopping experience
Micro-moments
Conjoin reviews and personal insight
Utilize natural interface
Laura

6. OUR IDEA Develop a natural interface
Users will be able to speak to their personal shopping/style assistant, Aidi
Aidi will collect metadata on the user via his/her purchase behavior, social media photos, likes, etc.
Aidi learns more about user + generates info about product reviews → style and sizing recommendations
Laura

7. WORKFLOW: HOW IT WORKS
Andrew

8. OUR IDEA: FEATURES Voice Search Inventory Customer Review Compilation
Rewards for reviews
Text/Chat Alternative
Style Recommendations
Example: Aidi, I have a birthday party tonight what should I wear?
Aidi: Dark jeans and your blue button up but take your grey sweater just in case, it will get cold later. Don’t forget a black belt and shoes.
Andrew

9. OUR IDEA: BENEFIT CYCLE
Aidi provides accurate recommendations
Consumer confidently purchases
Aidi asks for review (2 weeks) after purchase
Consumer rewarded for review
Laura

10. OUR IDEA: PROS/CONS Benefits Hands-free, reduces pain points
Adds personalized touch
Increase in product reviews
Increase consumer confidence
Reduce returns
Challenges
Users may not be in the right setting to speak out loud with their assistant
Solution: have a messaging feature so users can interact with their shopping assistant as they would via a texting conversation
Laura

11. SCENARIO 1: GEORGE’S SWEATER
George is looking to buy a sweater for a Christmas party he is attending in 2 weeks. He wants the sweater to be blue and under $50.
Presses the microphone button to activate Aidi
He asks Aidi, “Show me blue sweaters under $50”
Aidi processes the request and loads a page with results
George find one he likes but wants to know more about the product
He asks Aidi, “Is this sweater warm?”
Aidi shows number of reviews searched, the rating of product and offers advice.
Aidi responds, “People say it’s thinner than it looks, but it’s very soft and warm. Wear your grey button-up underneath for a smart trendy look.”
George likes what he hears and tells Aidi to add it to his cart.
Aidi adds sweater to cart and ask s if he would like to continue searching.
Alyssa

12. SCENARIO 1: VISUALS
Alyssa

13. SCENARIO 2: MEGAN’S CHRISTMAS WISHLIST
Megan is a sophomore at the University of Pittsburgh. She is in the process of Christmas shopping and finds a cardigan she thinks her mother might love. She wants to share this with her mom via text message and see if this would be right for her.
Clicks the microphone button
Asks Aidi, “Can I share this cardigan with my mom?”
Aidi responds, “Certainly. How would you like to share it?”
Options appear: Text Message, Facebook, Twitter icons
Megan says text, and Aidi opens her messaging app
A pre-made message appears with an image of the product, ratings, and a link to the page.
Andrew

14. SCENARIO 2: VISUALS
Andrew

15. VISUAL COMP: REWARDS PROGRAM
Laura

16. USABILITY FEEDBACK
50% would feel very comfortable w/ interface, 50% would feel somewhat comfortable
According to BrightLocal Local Consumer Review Survey % of users trust online reviews as much as a personal recommendations.
Andrew

17. FINAL RECOMMENDATIONS
Body composites
Meta-reviews
Andrew

18. THANK YOU
all