Suggestible - GR1

User Analysis

Age:
People old enough and not too old to use an android phone competently
most likely 20-60 year olds

Location:
Urban/metropolitan areas where there are more places to go

Characteristics:
Smartphone users, but not necessarily super tech-savvy
English-speaking
Have enough mobility and leisure time to go to the places that we recommend

Use Cases:
Bored or indecisive people looking for something to do:

• Don’t have specific requirements, just want to do something
• May flip through several options

Adventurous people looking for something new to do:

• Knows what type of activity they are looking for (food, places to go, or movies to watch etc...), would use filtering options
• Tired of doing the same thing all the time and wants to find out what else is out there
• Want suggestions of new things that are similar to old things they have done and liked

Groups of people looking that can’t agree on something:
(We are not optimizing our application for this use case but rather for the previous two.  Even though our application isn’t optimized for group decision making, it will still be a valid and probably useful tool for groups so we would still market our app as a decision maker that might be useful for groups.  All of the following bullet points show reasons why our application could be applied to group users)

• Looking for a specific category of activity, e.g. a restaurant
• Want a decision from a neutral party that will be satisfactory (the recommended restaurant should be close by and well-rated)
• Want to be able to quickly veto options and get new suggestions (since most groups can quickly identify options that they don’t like)

Lessons Learned from Interviews

User 1:
Some people are really open to suggestions and have few restrictions.
Had spent too much time on Reddit and just needed an idea for what to do.
Was willing to go somewhere or stay in his room.

User 2:
Often wants food and has no idea what to make herself or order.
Wants to leave her dorm and do something but can’t decide where to go.
Wants the motivation of a good suggestion to get her to do something.
Is indecisive, but still knows there are some things she will never want to do so she would want a permanent veto option.
Wants options tailored to the weather because she does know she wouldn’t want to go very far in the rain or cold.

User 3:
Is sometimes out wandering around with a group of people and wants to quickly find somewhere to eat or somewhere to go nearby.
Gets fed up of their indecisive friends who can never agree on anything and has run out of suggestions of things they might like to do.

User 4:
Tends to go out a lot and try new things.
Already knows of a variety of options to do at any given time but would like some new and interesting suggestions.
Looking for new types of food to eat (either specific recipes or different types of ethnic restaurants).
Would like to have some options of free (or cheap) things to do.

User 5:
Had a few types of things she liked to do.
Widely varied interests, but picky about her choices.
Would need a highly personalized, tailored suggestion system.
Was interested in a social component with friends helping decide what to do.

User 6:
Works part time so wants to find new things to do with her days off.
Wants to find new places to go out at night (usually dinner or movie or performance art) in the city with her husband.
Is relatively decisive and usually knows what category of suggestions she would want but would want the application for its ability to find new things for her to do within that category.
Would want to know about upcoming events like exhibits at museums or weekend markets and festivals that are not permanent fixtures of the city.
Would be willing to use a website as well as a mobile app since she is willing to plan in advance on a computer.

Users 1-5 demonstrate a wide range of young people (19-22 year olds) who have some overlapping interests but who also have different needs. User 6 is an example of an older user but from that interview we learned that even though User 6 was 58, married, and had lived in Boston for 30 years, her interests were along the same lines at the interests of User 4 who is 20 and had only been in Boston 2 years.  We group these two users into the “adventurous” user group which are people who want to find new things.  Users 1 and 2 can be grouped into the bored and indecisive user group.  User 3 would be in the difficult group decision user group that we aren’t optimising for but this user also expressed interest in a suggestion app even if it wasn’t tailored just to the group decision making experience.  User 5 expressed interest in having highly personalized suggestions but we feel that providing personalized suggestions would detract from the experience of users looking for completely random and spontaneous suggestions and from the users looking for new things to do.  As a result, we decided to tailor our application to people looking for randomized suggestions based only on the time of day and the time of week and the weather.  We feel that personalized suggestions can already be found from most websites (like Yelp and Amazon) and that our focus should be on a smaller user group.

Task Analysis

Tasks:
Browsing without filtering

• The user would open up the app and immediately start examining options.  When the app is first open, all categories of suggestions are selected so suggestions will include places to go, food, books, and movies interspersed.
• This user won’t set filtering options (wants suggestions from any category)
• This user will probably choose something quickly because not specifying a filter usually means they are open to more suggestions
• The application must show value quickly (good default suggestions) in order to satisfy this user going about their task

Searching with filtering

• The user will select areas of interest from filters and maybe just get suggestions for restaurants, food, and bars for example.
• The user is willing to take additional steps and spend more time narrowing down a category for better suggestions
• There are fewer time constraints because user is more committed to finding a suggestion in the category they selected

Finding out how to do a particular activity

• Once the person has found an activity of idea that they like, they will click to find out how to accomplish their goal
• The user will get linked to other websites with instructions (ie. recipes, directions, movie or book download).  There will be buttons usually for Google Maps, Yelp, and oftentimes Amazon or iTunes (for books and movies).
• There are now more time constraints. Now that the user has finally settled on an activity they want to get started immediately and don’t want to have to wade through complicated menus to figure out how to accomplish their goal.
• The user wants all of the information about their activity linked to from the application and doesn’t want to have to go fill in the information into Google Search or Yelp or other useful information websites on their own.