Elbow Room: The App

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By Andrew Cohen

For General Assembly UX11

Presented Dec. 17, 2013

RESEARCH NOTES

Utilizing open-ended “Ohno Circle” methodology,

I sat in a restaurant near my home and just

observed the customers while taking notes.

FINDINGS

Many of the patrons who came in after 2pm came not for the food (which is excellent) but in search of a quiet place to

• Think • Talk • Listen

• Read • Work • Observe

PERSONAS

My research identified several user groups likely to seek out such mid-afternoon “third place” establishments. Among them: • High School and College Students • Stay-at-Home Mothers of Young Children • Freelancers • Professionals Seeking a Quiet Getaway

CHALLENGE

Find a way for people who like to hang out in quiet, uncrowded restaurants or cafes to immediately locate estblishments where they can sit with friends or a book for a long time without being rushed.

SOLUTION 1 An app/website that uses data analysis to determine at which times a given establishment is likely to be uncrowded based on of sales at different times of day. Example: It could tell you that the nearest Starbucks is a mob scene on Mondays at 8am but a hermit’s dream at 11am.

 

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SO LUTIO N 2 An app servic e that encourages restaurants and cafes to install webcams that allow prospec tive c ustomers to see how c rowded it is in real time before making the trip. This could be an add-on to servic es (Yelp, Zagat, Foursquare) that already help c ustomers find venues.

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THE IMPLEMEN TATIO N :

E lbow Room

An app that uses predic tive technology to

help you find a quiet place to go at any time

of the day.

 

          TASK FLOW

•Choose type of venue

•Choose time and location

•Choose from list of results

A lgorithms predic t present and future user density by fac toring in such fac tors as:

• C redit-c ard data • Fire c ode requirements • W eather reports • Real-time transac tions • Doorway sensors • C ell phone density • W ebcam analysis

 

User c riteria c reates a ranked list of nearest venues matching desired attributes, giving each a “c rowd index” number and a c orresponding color. • G reen = Under 50% full • Yellow = 50% to 100% full • Red = More than 100% full

(expec t a wait)

 

Venue-level page gives detailed information, inc luding a graph showing that day’s c rowd estimates, along with other data one would typically find on Yelp, Foursquare, or Zagat:

• Address, phone number • Hours, attributes, pric e • Travel information • Live webcam (if available)