Overview
Rocket Local Banker is a localized landing page experience designed to strengthen trust and improve lead conversion between Rocket Mortgage bankers, real estate agents (REAs), and homebuyers.
Although Rocket is the largest mortgage lender in the U.S., it is often perceived as distant compared to local lenders. This project reframed Rocket from a national, online-first brand into a locally present partner, enabling agents and clients to connect directly with a Rocket banker serving their area.
Role & Scope
Together with the three other designer I worked across concept definition, interaction design, and iteration and usability testing, delievering quality results under tight delivery constraints.
The concept originated during Rocket's company-wide Hackathon Week and was later advanced to a Proof of Concept (POC) following stakeholder review.
Problem Space
Losing trust to local lenders
Internal survey data showed that Rocket frequently lost real estate agent partnerships to local lenders for two main reasons:
- →Perceived responsiveness — local lenders are easier to reach and faster to respond
- →Trust through locality — agents and clients feel more confident working with someone embedded in their community
This surfaced a core challenge:
How might Rocket deliver the scale of a national lender while feeling as trustworthy and accessible as a local one?
Product Direction
page user flow
Introducing Rocket Local Banker
In response, we introduced Rocket Local Banker — individualized landing pages for Rocket bankers that could be shared with both clients and REAs.
Each landing page was designed to:
- →Serve as a single contact point for both user groups
- →Support lead-generation actions (applications and referrals)
- →Be accessible from multiple entry points across Rocket's ecosystem
Key Design Decisions
1. Supporting divergent user behaviors without confusion
The landing page needed to support two fundamentally different user paths:
- →Clients applying for a mortgage
- →Real estate agents submitting referrals
The core risk wasn't visual clutter — it was asking users to self-identify too early, which early exploration and testing showed increased hesitation and misrouting.
Defining the branching model
I explored multiple approaches to user branching:
- →Iteration 1: Branching before entering the page vs. branching within the page
Option 1: Branched Landing Pages
Pros
- • Tailored experience for different user types
Cons
- • Extra engineering effort with harder integration into different entry points
- • Potential user dropout due to the extra step
Option 2: One Landing Page for Both Parties
Pros
- • Standardized landing page, easier implementation
- • Link-share friendly, eliminating concerns about clients entering the referral version or REAs entering the application version
Cons
- • Requires careful design to prevent confusion between two distinct functionalities
- →Iteration 2: Branching inside vs. outside an auto-advanced form flow
Option 1: Auto-Form for Both Referral & Application
Pros
- • Consistent format ensures unified method for generating leads
Cons
- • Additional steps within auto-advanced form could lead to higher dropout rate
Option 2: Auto-Form for Application & Typeform Modal for Referral
Pros
- • Dedicated section for client application with simplified steps
- • REAs already familiar with Typeform survey modal used in referral process
Cons
- • Different patterns for the two CTAs require additional integration effort
- • May cause inconsistency in user experience
Through iteration and critique, I led the team toward a structure that:
- →Clearly separated client and REA actions
- →Minimized upfront decision-making
- →Used progressive disclosure to introduce complexity only when needed
This allowed users to recognize their path quickly while maintaining momentum and confidence.
2. Building trust through content and structure
Once the interaction model was set, the focus shifted to trust.
I conducted a competitor analysis across local lenders and banker profile pages to identify:
- →Content patterns that increased credibility
- →What information mattered early vs. later in the funnel
- →What could be deferred at the POC stage
These insights shaped the content hierarchy, balancing professional credibility, local presence, and conversion clarity without overloading the page.
final page design
Validation & Handoff
Usability testing
Before developer handoff, we tested the experience with:
- →5 real estate agents
- →5 clients
Testing focused on:
- →Confidence in the banker's local legitimacy
- →Clarity of next steps for applications and referrals
- →Expectations around post-submission follow-up
Results showed improved clarity around user paths and increased confidence in banker authenticity, informing final copy and interaction refinements.
"All the information I would need is provided and easy to find. Well written, well thought-out profile page for sure."
— Real Estate Agent 1
"The more I think about this page the more I like it. It's all pretty much there."
— Client 5
"As a real estate agent, this would be easy for my clients to use whether they're purchasing or refinancing a home."
— Real Estate Agent 2
"I like the 3 steps of application in 'Apply Online with Me' section. I think this is probably my favorite part."
— Client 4
Service blueprint
To ensure alignment beyond the UI, I partnered with product and engineering to create a service blueprint mapping:
- →User actions
- →Frontend touchpoints
- →Backend processes
This reduced implementation ambiguity and supported delivery of a technically feasible POC.
Outcome
- →Successfully presented to company stakeholders
- →Advanced from Hackathon concept to Proof of Concept
- →Delivered a live, testable landing page experience
- ↳Live example: rocketmortgage.com/local-loan-officers/profile...
- Note: Rocket has since updated their design system, so the live page may differ from the designs shown here.
- →Established a scalable pattern for future banker profile pages
Reflection
What This Project Taught Me
This was my first experience designing a true 0 → 1 product concept under real delivery constraints. It strengthened my ability to:
- →Move quickly from concept to execution
- →Make structural decisions with incomplete information
- →Balance ambition with feasibility — and know when to ship
If I Were Designing This Today
★AI as a Trust Explainer
AI could explain why a banker is a good fit by surfacing relevant experience and real usage patterns, such as specialization, past collaborations, or response behavior. By grounding recommendations in real signals rather than branding, trust feels earned instead of cosmetic.
★AI as an Expectation Setter
AI could clarify what happens after submission by predicting response times and outlining next steps in plain language for clients and agents. Setting expectations early reduces uncertainty and makes the experience feel more responsive and human.