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Dockless bike sharing simplified! 


Alexis Lim
Austin Smart
Satvik Vats


Leading a team of three to craft & conduct IA + Research for building a new app.

Defining the Why?

It is inconvenient to find the best bike share service to use.

There are multiple bicycle sharing options for Seattle commuters: Ofo, Limebike, Jump and Spin. As these bicycles are dockless, it makes it hard for the user to find which one is the best option at that very moment and location of the user.  


Currently, the only way to see where each service has a bike near you is to go through each application separately, which means the user must remember where the previous service had a bike and price while looking at a different one.

UX Research 

Information Architecture 

Content Strategy

UI Design

Product Roadmapping


Semi-structured Interviews 

User Persona (Stakeholder Analysis)


Observational Studies 



Wireframes (Lo-Fi)



Ideating the How?

An app that has it all! Think of this scenario;

[Other scenario based solution were also explored during brainstorming. Solutions like restricting users to park bicycles at specific places or AI watch that leads you the best option. They were discarded due to how crazy/unfeasible their implementation is.]

Just after the class ends Austin wants to go to the Husky stadium to catch the football game, he looks around and tries to find a bicycle to rent but, couldn’t find one. Rather than opening multiple apps and figuring out which one is available and close to him he just opens our application and quickly finds the bicycle near the Sieg hall. This way not only did he save time but also the hassle of figuring which bicycle is close and compare maps on different apps, as all the maps are synchronized with our app.

Persona 1.jpeg

Wasup :)

Persona 2.jpg

Say hello 👋

Persona 3.jpg



An application exhibiting all the available bikes from all four bike sharing services in Seattle. The user will be directed to the chosen bike’s respective service application, not execute the renting of the bike within our application.

All available bikes from the three bike share companies will be represented on one comprehensive map as dots

  • Bikes can be sorted according their price and walking distance
    using specified colors


  • Variety of filters for different features available, such as price,
    bike type, and distance


Our big idea is to ease the use of the three bike sharing apps that are used here in Seattle. Since our goal for the application is to make life easier for the user, we are going to take a very user-centered design approach. We will do user testing to assure our app has good navigation. Success will be measured by how many users we have using the application.

Meta-data driven Information architecture 

Our architecture will hold the metadata about each bike, taken from the separate apps, but will redirect the user to the chosen bike’s company app.

The existing tools we would like to leverage are the current maps that each individual bike company has and the data that they all hold. To create our app, we would like to combine the existing maps into one. By using a similar design to the bike services’ application, we can utilize the familiarity of the design to make it easier for the users to navigate.

Pre-existing Technology integration = Consistent Design.

Bottom-up emphasis

Since there is already a solid top-down information architecture, we will be approaching this with a bottom-up emphasis.

We will need data for the bike services, such as location, price, and bike type. We will also need an interactive map.

We will use metadata fields for the individual bikes on the map, which will include price, location, and type.

Metadata field definition

Navigation system design

To leverage top-down strategy, the user will be presented with all the bikes available on the map. To leverage the bottom-up strategy, the user will have the option to filter for specific fields such as price or distance.

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