Loelle's LookBook

Google UX Exercise

Wait Staff Experience



Using the user flow as a framework, I creating the following wireframes to illustrate the user experience.



  • New users provide both an email and mobile number as modes of verification, to support self-service if login fails
  • To begin building the server's profile, we ask for their restaurant name and photo; these are important elements for their coaster
  • Existing users log in simply, using their mobile number as verification

Ordering coasters!

  • New users will need to order customized coasters, in order to jump start their journey towards feedback
  • A user's information will pre-populate as much as possible, with the option to add/edit
  • After previewing, a user will select the desired quantity and add to cart
  • A typical checkout experience would follow (not pictured) or a user could continue to browse the app and return to complete their purchase from the menu 

Reviewing feedback and sharing

  • Active users will be able to review their high level star rating, number of guests served, pinpointed strengths and recent comments on the home page
  • From the menu, users can access their profile, which serves as a "resume" that they can share with others
    • Ideally, a user could add and edit this information inline, including their personalized url
  • Users can access a dashboard, which allows them to track ratings over time
  • Finally, users can access coasters orders as well as settings via the menu (change password, contact information, etc.)


The patron experience is quite simple:

  • Using the physical coaster provided by the server, the patron visits the mobile site (or desktop site, in theory) to leave feedback
  • The patron provides their name and hopefully a receipt image
    • The hope is that attaching a receipt discourages fabricated ratings, though there's no guarantee and it's not required
  • Patrons go on to submit a star rating, trait-based rating and comments if they desire
    • The traits included were informed by user interviews