Ariva

Ariva takes multiple locations in NYC along with a small number of selected preferences to provide the user with a central meeting location, itinerary, and the ability to share with friends.

CONTEXT

The Question

How might we help transit agencies increase ridership and customer engagement while managing operational costs?

The Gap

The greatest stress point is finding a convenient spot that works for everyone in a group. Planning always requires using multiple platforms for different legs of the same event-planning function (i.e., Yelp for spot-searching, Google Map for directions, messaging apps for communication, etc.)

SOLUTION

Solution Statement

By allowing users to easily determine and navigate to a central location for a meeting, Ariva will connect people in New York City, build relationships and bring the city closer together. This can be achieved while leveraging existing platforms/APIs, and also incentivizing public transportation use.

Benefits

Provides a central place to meet “in the middle”

Reduces friction by simplifying the decision-making process

Aligns suggestions with preferences

Quality suggestions and new discoveries for users

Initial Configuration for Success

Desirable mid-point suggestions

Clean and attractive user interface

Strong decision-making guidance

Clear public transportation directions

VALIDATION

Experiment Sequence

Experiment: Act As the App

People who are planning a meeting send us what they want to do and two start locations from which people in the group will be traveling. We manually pick an activity for them at an optimized location and return the itinerary via text message. Following the experiment phase, we received post-experience user feedback.

Results showed that the majority of our experimental users (87.5%) had a positive experience with our solution.
When asked if they would download and use the app if it were available on the App Store, 25% stated maybe, 37.5% stated yes, and 25% stated yes with frequency.

Experiment: Paper Prototypes

We sketched out three different user flows on paper for users to follow. Each prototype included a different feature and/or flow from input to result output. Over a 3 hour time frame we also collected feedback via a form on which interface was preferred and why.