The Station Bank app helps young professionals invest with confidence through a conversational AI chatbot.

Team:
Jackie Lee (myself)
Jessica Walker
Keri Jordan
Margaret Kalejta

Platform:
iOS
Web

—
My Role

For this design sprint, the entire team was equally engaged in most of the process. My involvement includes: Research & Strategy, Journey Mapping, Storyboarding, Interviews, Ideation, User Testing, and Rapid Prototyping.

I led the User Interface Design alongside Keri.

—
The Process

Our team approached the project through the 5 day design sprint created by Google Ventures. This method helps narrow the problem space quickly and aligns the team with the objective.

—
The Client

About:
Station Bank (a fictional financial institution) aims to demystify the compexity of saving, spending and investing money. They currently operate with an existing responsive website and are looking to expand their services.

Request: 
To create a native mobile app that offers something different for existing customers.

Target Demographic: 
Young professionals (mid-twenties) that are investing for the first time

DAY 1: MAP

—
Research

75% of millenials say they would prefer financial services from online sources, such as: Google, Amazon and PayPal.

71% see that financial advisors do not have the best interests for clients.

62% value AI for recommending products and/or services.

Heaviest users of digital assistants are between the ages of 25-34.

—
Journey Mapping

Creating the Journey Map helped us dictate where, in time, the possible pain points are. Ultimately, we discovered that the frustration of seeing a financial advisor was significant and brought that insight to our interviews.

—
Interview Insights

Our interviews were strong validations of our initial assumptions about the problem space. These are the main insights we discovered from our interviewees:

• Do the majority of their banking online.
• Have some disposable income and clear financial goals.
• Are interested in investing but don't know where to start & think it's too risky.
• Would seek financial advice from a knowledgeable friend rather than a bank.

Other Interview Insights

—
Persona

Credit: Jessica Walker

DAY 2: SKETCH

—
Inspiration

At this point, we began to diverge again, and collected a wide range of ideas, from: chatbots, skills training, budgeting, micro-savings, gamification, and goalsetting. The screens presented directly impacted our final product.

—
Idea Sketching

Using our inspiration,we then did some idea sketching, crazy 8's, and then solution sketches. These were then used to create a solution for Henry.

DAY 3: DECIDE

—
Art Museum

An art museum is a pin up session where each member post their solution sketches onto a board. Each member is given a set number of dot stickers to anonymously vote on the most interesting ideas that are posted.

Using the art museum tactic allowed us generate a heatmap with dot stickers to see what the most popular app function is. We decided on conversational AI to help Henry invest for the first time.

—
Storyboarding

After defining the inherent problem with the fear of investment, we decided to create a storyboard to narrate a likely backstory. This helped us understand how Henry gains trust with Clara the chatbot. 

DAY 4: PROTOTYPE

—
Version 1

Initially, it was difficult to conceptualize to how test our product that is mainly focused on the conversation between Henry and the conversational AI. We decided to break up the conversation at crucial moments where the user should decide the next suggestive text that Henry would select.

DAY 5: TEST

—
User Testing

For our user tests, our team asked the participants to read the copy for the onboarding, and the flow for the rest of the interface. We learned through the user testing that the conversation needs to be more empathic for Henry, who knows nothing about investing.

—
Final Screens

—
Reflecting on the Sprint

Pros: 

• Allows multiple stakeholders to give undivided attention to the project.
• Rapid ideation saves time and money.
• Strong kickoff for a product.

Cons:

• If not prepared beforehand, it will be difficult to secure interviews and user testing sessions.
• Problem needs to be large enough for a sprint to be valuable.
• Due to the time constraint, the wrong problem can be solved and renders the sprint less valuable.

—
Next Steps

If this product were to be released, a few key steps are needed to polish the conversational AI:

1. Develop Clara
2. Have her perform real-time calculations
3. Make Clara more versatile for people with different levels of knowledge about investment

Let's Connect!

LinkedIn

Email

Dribbble

Instagram

© Jackie Ka Chun Lee. All Rights Reserved