01 / U.S. News Money
U.S. News Money Mortgage Quick Fill
U.S. News used mortgage calculators to help users estimate monthly payments and connect high-intent homebuyers with lender options. When I joined the project, only 6.4% of users completed the flow and clicked into a lender path.
I led the redesign from a traditional calculator into a guided estimate experience, using AI-assisted exploration, research, and prototyping to help users get to a useful estimate faster while keeping financial inputs structured, visible, and editable.
01 / U.S. News Money
The 6.4% Problem
Reframing a mortgage calculator into a 30-second guided estimate experience.
Simon Dai - Portfolio Case Study
02 / Context
Why the calculator mattered
The calculator was a high-intent doorway to the mortgage journey. Improving it meant improving the point where uncertainty becomes action.
03 / The user
USER
Get a useful mortgage estimate in 30 seconds without requiring financial expertise.
04 / Original calculator
The Original Calculator Experience
The original calculator was functional, but it asked users to complete a dense form before they could see a useful estimate. Users had to invest effort before understanding the value.
Try the Prototype ↓
Loading interactive prototype
05 / Funnel readout
Where users dropped off
I paired product analytics with the original experience to understand where friction appeared in the journey.
06 / First iteration
The first fix wasn't enough
After early interviews and usability tests, we added more guidance around confusing mortgage inputs. The hypothesis was simple: if users understood the fields better, more of them would complete the calculator.
Why this decision
Users hesitated around unfamiliar terms and exact financial inputs, so the first fix focused on reducing confusion through tooltips and clearer visual explanations.
Result
The improvement was small. Tooltips helped users who were already committed, but they did not reduce the larger barrier of time, effort, and trust before users started.
Try the Prototype ↓
Loading interactive prototype
07 / Research insight
The Real Barrier Was Time + Trust
08 / Success criteria
From research signal to success criteria
Aligning Around Intake Friction
After research, I aligned Product, Design, Engineering, and leadership around one focused strategy: keep the calculator logic intact, redesign the intake layer, and measure success by result-screen reach and next-action conversion.
User success
Reach a useful estimate faster, with less uncertainty and fewer sensitive inputs upfront.
Product success
More users complete the calculator and reach the result screen with confidence to continue.
Business success
Increase high-intent actions: refining, saving, comparing, or viewing lender offers.
Delivery success
Improve the intake layer without rebuilding the core calculation engine.
09 / AI concept test
The chatbox was right - and wrong.
What if AI asked the questions?
We tested a conversational assistant as a way to make the process feel lighter and more personal. It helped users understand the journey, but trust still had to be designed deliberately.
Conversation prototype
What would you like to estimate?
A monthly payment for a home around $500k.
I can guide the estimate and show every assumption before we calculate.
Can I review or change the numbers first?
What users told us
Preferred guided help
Understood the assistant
Comfortable sharing exact income / debt
Wanted review / edit
Raised privacy concerns
Keep the guidance. Structure the input.
Guided help remained valuable, but the final interaction needed predictable steps, visible progress, and an explicit chance to review.
10 / Journey map
Map the journey first
Design implication
The visual shows the shift from an unstructured chatbot to a guided, progressive intake flow. Each step has a clear role - location, financial inputs, timing, and personal context - while users can review and edit assumptions before the flow hands them a useful estimate and a next action.
11 / Guided quick fill
Guided quick fill
We created a guided entry point that helped users estimate faster, understand assumptions, and stay in control before calculating.
12 / Design choices
Decisions that changed the product
The final solution came from four product decisions: where AI should appear, how much information users should provide upfront, how much control they needed, and what we could ship without rebuilding the core calculator.
Start with the outcome a user wants, then make each input feel necessary.
Use AI to explain the work, not to hide the mechanics of a financial decision.
Show what has been completed, what remains, and when editing is possible.
Offer a useful estimate before asking someone to commit to the next stage.
13 / Outcome
From 6.4% to 13.8%
The final design created a clearer path from financial uncertainty to a mortgage decision.
Try Final prototype ↓
Loading interactive prototype
14 / Closing principle
AI Is a Complexity Decision
The best answer was not more intelligence. It was the right amount of help at the right moment.
Connect the System
The strongest design decisions came from treating user confidence, product completion, and business conversion as one connected system.
Make AI Feel Invisible
The best AI pattern was not a visible assistant. It was guidance embedded into the workflow, reducing effort without creating new trust concerns.
Kill the Wrong Idea
The chatbox had signal, but the data showed it was the wrong interface. I kept the user need and changed the solution.