UX Case Study · Mobile Breakpoint

Redesigning
Bold.org/applicants

A diagnosis and lo-fi redesign of the Bold.org applicant landing page — focused on building trust before asking for action.

📱 Mobile-first
🎯 Conversion & Trust Optimization
⚡ Lo-fi Prototype
01 — Core Issues

What's Broken Above the Fold

The current page asks users to act before answering their most basic questions. Trust signals exist — they're just in the wrong place.

TRUST Credibility is Buried

Notable donors like Dwayne Wade, Imagine Dragons, and Terry Crews are powerful proof points — but they live far below the fold. First-time visitors never see them before being asked to sign up.

CTA Premature Call to Action

The page leads with "Apply" before answering the three questions every new visitor is silently asking:

  • Is this legit?
  • Is this worth my time?
  • What do I actually get?

CLARITY Process Is Invisible

Users don't understand what happens after signup, how long it takes, or what effort is required. This ambiguity increases perceived risk and reduces willingness to convert.

ANXIETY Silent Objections Go Unanswered

  • "Is this free?" — not stated clearly
  • "Will I get spammed?" — a small disclaimer isn't enough
  • "Is this a scam?" — vague language like "thousands of scholarships" feels marketing-heavy, not verifiable
"Thousands of scholarships" signals abundance but not credibility. Precise, verifiable numbers do both. — Core insight driving the redesign
02 — Lo-fi Redesign

Before → After

Every change is anchored to a specific behavioral goal. The redesign earns trust before asking for commitment.

Current Bold.org mobile page
Current Page
BEFORE
Proposed Bold.org redesign
Proposed Redesign
AFTER

View the Interactive Prototype

Open in Figma

What Changed & Why

HERO Outcome-Led Headline

"Actually win" implies Bold's matching reduces wasted effort — quietly countering the skepticism students carry from generic scholarship sites.

TRUST Numbers Move Up

$43M awarded, 300K members, 8,400+ scholarships — specific and verifiable. Moved above the fold to build credibility before the CTA.

TRUST Donors Above Fold

Dwyane Wade, Imagine Dragons, Terry Crews visible immediately. Recognizable names act as authority anchors before a single word is read.

CTA Lighter Ask

"Create your free profile" feels lower-commitment than "Apply." Microcopy — "Takes 2 minutes · No spam, ever" — preempts the top two objections inline.

FUNNEL 3-Step Model

A simple Create → Match → Win framework sets expectations around time, effort, and outcome — eliminating the biggest source of mid-funnel drop-off.

OBJECTIONS FAQ Layer

"Is this really free?" and "Will I get spammed?" answered explicitly with context — not just a badge. Supported by real user testimonials.

03 — Behavioral Impact

Why These Changes Improve Behavior

Each design decision maps to a specific psychological lever that reduces friction or builds confidence at the right moment.

⚡
Reduces Cognitive Friction
Users understand value and process within the first 5 seconds. No need to scroll to answer "what is this?" — the hero section handles it completely.
🏅
Builds Trust Before Asking for Action
Authority signals (notable donors) combined with specificity ($43M, 300K members) create the credibility equation: recognizable names × precise numbers = believable platform.
🎯
Aligns CTA With User Readiness
"Create profile" matches where the user is in their decision journey. "Apply" implies commitment the user hasn't earned yet. This single word change reduces perceived risk.
🛡️
Preempts Drop-Off Points
Answering objections (free? spam? scam?) at the moment of hesitation removes the friction that causes users to bounce. FAQ + inline microcopy covers both the scroll-ers and the skim-ers.
📈
Improves Perceived ROI
The message becomes clear: low effort (2 minutes) → high upside (real scholarship money). When the effort-to-reward ratio is obvious, conversion intent increases significantly.
04 — How to Evaluate Success

Success Metrics

Primary metrics track conversion directly. Secondary and behavioral signals tell us why the numbers moved — which is essential for iterating.

Primary Metrics

↑
Landing → Signup
Conversion Rate
Primary north star
↑
Above-the-fold
CTA Click-through Rate
Tests hero clarity
↑
Signup
Completion Rate
Tests expectation setting

Secondary Metrics

📜 Scroll Depth

Are users engaging with the trust and proof sections? Deeper scroll with high conversion = design working. Shallow scroll with low conversion = hero isn't landing.

⏱ Time to First Interaction

Faster interaction = clearer value prop. If users pause before clicking, the headline or CTA may still need refinement.

❓ FAQ Interaction Rate

High FAQ engagement indicates objection sensitivity in this audience — useful signal for prioritizing which objections to address inline on future iterations.

👤 Profile Completion Rate

If users sign up but don't finish their profile, the "How it Works" section may need to better set expectations around effort.

Behavioral Signals

↓ Drop-off Before Signup

Should decrease if trust and clarity improvements are working. Monitor against baseline from current page.

↑ Profile Completion Rate

Better expectation-setting on the landing page should reduce drop-off mid-profile. If this doesn't improve, investigate post-signup onboarding separately.

05 — Experimentation Plan

A/B Test Roadmap

Three prioritized experiments, ordered by expected impact and ease of implementation. Run sequentially to avoid contaminating signals.

Test Control Variant Primary Signal Priority
Hero A/B
Headline + proof + CTA		 "Find Thousands of Scholarships" + Apply CTA "Find Scholarships You'll Actually Win" + Create Profile CTA CTA click-through rate High
Donor Trust
Above-fold placement		 Donors buried below fold Donors visible in hero (Wade, Imagine Dragons, Crews) Time to first interaction High
CTA Language
Single variable		 "Apply Now" "Create Your Free Profile" Signup completion rate Medium

Ready to Explore the Prototype?

Open in Figma
Bold.org Mobile UX Redesign  ·  bold.org/applicants/  ·  Mobile Breakpoint Case Study