Scenario Builder
PeerStreet • 2021 • Product Strategy, UX Design, UX Research, Usability Testing
In this project, I led the end-to-end design of the Scenario Builder, an interactive form experience where Loan Originators (our user base) can get pricing and high level feedback based on a very limited set of data about their submission.
Post-Covid, the company focus was on customer facing tools (vs internal tools), so the goal was to create a tool that would help our customers quickly get pricing estimates, which would help them save time and also win more business.
My role in this project was run some sessions with our users, distill and define that information, and then come out with a clear concept for how we would move forward with the tool.
The Problem
Loan Originators, a.k.a. Lenders, typically work with multiple loan buyers and don’t have an efficient way to compare different buyer programs and pricing. This implies that PeerStreet could be passed up for opportunities if originators fail to recognize the potential of PeerStreet’s offerings.
Many competitors have a fast and easy way to provide feedback on a loan to Lenders
To be competitive, Lenders need to provide borrowers with a reliable quote based on limited information (i.e. information shareable over a phone call). At the time, Lenders had to either reference PDFs of PeerStreet’s programs, or use the submission form (which requires over 30 input fields)
The Business Development team spent a lot of their time fielding questions for Originators, which is a very inefficient cycle for internal operations
Discovery
We asked the Relationship Managers (Sales) team to identify and connect us with active Lender partners who would be open to talking with the product team. We conducted 5 discovery calls with these Lenders to understand their current workflow around providing price estimates.
What inputs were required to provide an estimate?
What data are clients looking for in response to their inquiry? (Pricing, and anything else?)
What medium did they use to communicate with potential clients?
Did they provide real-time estimates? What challenges limit their ability to respond quickly?
Taking this information I mapped their flows to identify commonalities and expectations around a pricing tool.
Collaborating with the PM, Business stakeholders, and Tech Lead, we decided upon the following solution:
Build a new form where only key data needed to generate a meaningful response is required
Allow Lenders to experiment with deal structure and optimize economics
Display information critical for lender to close deal
Allow Lenders to promote a scenario into a submission
Competitive Landscape
Ideation & Iteration
Working with the Product Manager, we identified where this tool would live in the PeerStreet ecosystem, as well as any additional pages we would need to support. We wanted to enable users to not only create a scenario, but also save it for later and convert it into a real submission.
I had a few working sessions with the PM and engineers on our scrum to discuss the flow in detail, talking through each interaction on both sides of the platform (Lender view and internal view).
I explored a number of different layouts and informed by the discovery work, considering the hierarchy of information needed when pricing out these deals.
Once I built an interactive prototype to demo, we conducted a first round of feedback sessions with our users.
We gained some interesting insights from these sessions. Most notably, we were trying to strike the balance was between requiring too many fields to fill out vs. providing more accurate data. My assumption was that less fields would feel faster, lighter, and more calculator-like, which might encourage Lenders to interact with this tool more. However, feedback validated that an accurate quote was more important than simplicity.
“Some people might find filling out fields on the form laborious. I personally find more value to give accurate quotes to clients. It makes me look professional and organized.”
We took this feedback and leaned into the idea of making the Builder quite granular. Critical to a user’s experience would be the ability to quickly test different scenarios. To me, it made sense to include sliders to make this as easy as possible. However, with many dependencies between the fields/calculations it was important to test how these actually worked.
Logic
Working Prototype
I enlisted the help of a fellow designer to help me build these sliders. After vetting the functionality, we moved forward with development.
Development & Launch
De-scoped version
Observing user behavior on Hotjar
Version 1
Saved Scenarios table
Once Scenario Builder was available on our staging environment, I scripted and conducted a usability test with our group of Lenders.
I uncovered a few minor UI issues (loan address not obvious enough), but nothing too major. However, while they found the Builder useful, we received consistent feedback that it would be even more helpful to view multiple adjacent scenarios rather than arbitrarily plugging in one LTV value. A few Lenders mentioned an Excel spreadsheet calculator that PeerStreet historically provided, which was essentially a matrix of pricing.
Teaming with PM, I revised the design to accommodate a table and sent out mockups to our BETA Lenders to quickly gut check whether we were headed in the right direction.We released Scenario Builder as a BETA feature for a select group of Lenders. After giving them a chance to use the feature on their own, we solicited more feedback via email.
“Big improvement, in my opinion.”
- Lender 1
Looks great, extra options are key!”
- Lender 2
“Much better! Having a way to present options to a client in a fast and clear way, is such an overlooked thing. Going so far as to put notes and graphics to even highlight Best Rate and Max Leverage. A+!”
- Lender 3
Takeaways
This product is in the process of being rolled out incrementally, in order for the team to monitor for performance issues, establish reporting, and continue soliciting feedback from early users.
We are monitoring usage via a dashboard to track saved scenarios.
The project was a great exercise in using research, prototyping, and testing to help inform our product decisions. It exemplified how testing can invalidate assumptions, and ultimately lead us to a solution that better addresses the problem.