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Anthony Chen, Andrew Cooper, Ben Stueck
User Analysis
Our population consists of mobile phone users in need of finding a restaurant who are divided among two different groups.
1. Looking for a restaurant in a familiar setting
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User A is with small group of friends who have just finished watching a movie at the theaters. They decide it is time to get some dinner but the group cannot quickly come to a consensus for a place to go. They brainstorm for a couple minutes, but eventually they decide to use their mobile devices to begin searching for restaurants nearby. As they look into the options, they are only able to pull up two different menus before the group becomes antsy, and chooses the first idea to save some time. |
We discovered this user class when one interviewee discussed the difference between using a food finding application at home and on vacation. He mentioned that while on vacation he might be searching for any restaurant to go to. While at or near home, though, he may be jogging his memory of what options are available, since presumably he “knows” the restaurant landscape. This latter case is discussed here.
2. Looking for a restaurant in a unfamiliar setting
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User B is a visitor on Newbury Street who has decided its time to get some lunch. She has not made any plans for food, and needs help to make a choice. She wants something quick and nearby, but she also knows that she is a picky eater and needs to see her options before going in. As a result, she decides her best option is to visually locate the restaurants she can see around her, and make a choice when she sees the first menu that satisfies her preferences. |
2 of the 3 interviewees discussed that in an unfamiliar setting they will not use any application to locate a restaurant, as the applications they are familiar with are too cluttered and obnoxious to use. Instead, they will just do the best they can on their own. When probed about whether they would use a “good” application, both said they would be very open to using technology in an unfamiliar setting. This use case above is a person that might be in this situation.
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One interviewee asked about whether our potential application would refresh if he moved while using it. Although we haven’t decided that, it did bring up this interesting case, where a user is in a car and is traveling through a lot of space per unit time.
Task Analysis
These tasks were the three main tasks our interviewees discussed as being most important to them in a restaurant finding application. We feel that these three tasks would make for a complete application.
1. Find Restaurants
Goal: Easily find restaurants that are enticing to the user.
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- View an aggregate menu of all nearby restaurants.
- Navigate this menu and select dishes that interest you.
- View full menu, prices, and ratings of selected restaurant.
2. Compare Restaurant Menus
Goal: Simply and easily compare two restaurants side-by-side.
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- Simplify the information provided for the user
- Provide the user with adequate information to make a decision
3. Commute to Restaurant
Goal: Help the user find their way to the restaurant of their choice.
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