ZipPitch: the Speed-Dating app for Investing
The Democratization of the Crowd-sourced Investing Environment
ZipPitch is an app that matches investing interests with companies quickly and incorporates tools that apply “Shark Tank” questions and help educate investors with a focus on their risk tolerance.
Student Project at SMU UX certificate program
Team: Myself, Colin Robins & Cheslie Martin
I was responsible for the Presentation intro, Product design from research to conception, visualization and testing
Are you a confident, savvy investor like Chelsea, my wingman? Hey Chelsea, are you as impressed as me with that ROI over there! Or are you more like my friend Colin over here, an investing noob?
No matter what your comfort-level is with investing our idea will allow you to invest confidently.
We decided to blend an aspect that consumer investing hasn’t seen with AI (Artificial Intelligence); customize investing options according to the user and approach it with a thoughtful design? Zip Pitch: an app for the amateur angel investor.
This was my task; I focused on were Venn-Cat, Let’s Venture and Our Crowd. The first two were limited in helpfulness as the apps kept you from searching until you had signed up with your banking information which we didn’t want to commit to and decided not to adopt ourselves.
The Our Crowd app allowed for searching for investments immediately, which we liked and so became our primary competitor. While it gave good overall initial information, it was presented for Angel Investors who knew the lingo and that limited its target market dramatically.
Our initial contact was with a classmate who had a connection with a product in development. When the classmate dropped out the team decided to keep the category but expand upon the idea with our research.
Findings from Interviews
- I want to invest in what I know/understand – following leaders like Warren Buffet, who only invest in areas they understand well.
- FOMO – so many tech companies are turning traditional services upside-down and creating extreme valuations like Amazon, Uber, AirBnb, etc…
- Investing terminology is complicated – the Shark Tank show makes it understandable.
- I added the Monte Carlo method, a technique of statistical sampling employed to approximate solutions to quantitative problems. This process is used for the retirement advisement industry and it dovetail with a way to confidently display complex information visually and confidently.
We looked for a variety of users, from the experienced investor to the novice, to find differences and commonalities in our audience.
In order to visualize and make more tangible the individual steps that a user makes during the course and its possibilities, we created a corresponding model.
This model was revised when we found that our on-boarding and education experiences took so much time on the front end that our User’s lost interest. We moved the formalized on-boarding to later and the education element as an opt-in so that our User’s could really enjoy the search for investing opportunities quickly and then engage those elements when they had need to.
let my team members work on the basic page layouts for the introduction and log-in. I focused on the value-added elements of our idea. My sketches focused on taking the main evaluation sections of our app and visualizing the data for the ‘analysis / recommendation’ screens.
It was important to me to have many options to be reviewed for the investment evaluation and checkout pages which were essential parts of our app.
Moodboards and competitive analysis helped us start the process of visualizing our app and this was one of my areas as I enjoy trying to figure out the path our designs might take. By reviewing our competitors we understood where others had gone and the possibilities in serving areas where they hadn’t.
Our colors and type came from established resources and initial assumptions about our audience to help speed up our design process.
Knowing we could evolve these beginning assumptions through updated CSS / style sheets later enabled us to start the initial visualization process without too much hand-wringing over the ideal design solution.
After some paper prototyping adjustments, wireframes, mid- and high fidelity prototypes were created, which were supplemented with clickability using Adobe XD. Again, user tests revealed small vulnerabilities in the structure of the user interface, in some interactions.
Digital Design Sketches
After some paper prototyping adjustments, wireframes, mid- and high fidelity prototypes were created, which were supplemented with clickability using Adobe XD.
Again, my designs and focus were on data visualization, trying to help the user best see their new opportunities for investing.
The Illustrator renderings above were converted into Adobe XD below with additional data being added to again show options for our Users to evaluate.
Many ideas that seemed to resonate with our audience were discussed for future consideration.
AI could revolutionize and democratize the investment sector. Not for the sake of AI, but because, as the need for unbiased investment review. Just like MorningStar’s fund rating system visualized company data and helped investor’s picks with their side-by-side comparisons, our ability to visualize and filter risk could help this sector grow with investment from small investors rather than just large.
Due to the complexity of the project we were not able to implement any major adjustments to the concept in this short time. More testing with a larger audience would have helped us evaluate the strengths of the idea with more vigor.
We have an exciting way to combine existing elements like the Monte Carlo method and filtering to make investing in appropriate projects easy and accessible for the novice as well as the experienced investor. I approached the project with excitement for the research and ideation process. I wish I would have had more time to experience the user’s in our process. Overall I was happy with the way our small team split duties and accomplished so much in the prescribed time.
If there was more time available…
- Development of further user personas and Journey Maps / Task Models – in addition to the product-based Journey Map an experience-based Journey Map
- More research, as it‘s a complex and extensive topic with many factors where more practice would help us be better at facilitating an effective test as well as including stakeholders in them.
- Further iterations / test phases, actually test with real projects and their accompanying detail