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.
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.
To create a native mobile app that offers something different for existing customers.
Young professionals (mid-twenties) that are investing for the first time
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.
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.
Our interviews were strong validations of our initial assumptions about the problem space. These are the main insights we discovered from our interviewees:
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.
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.
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.
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.
If this product were to be released, a few key steps are needed to polish the conversational AI:
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