Improving User Qualification Experience
Onboarding flow for creators on CreatorSamples · Behavioral-Driven UX to increase clarity and reduce drop-off
CreatorSamples supports two tiers of TikTok creators: Standard and Creator+. Previously, upgrading to Creator+ required manual review, often causing delays and unclear feedback. This redesign introduced automation to improve clarity and reduce admin effort.
Project Overview
⚙️ Problem Statement
Manual approval led to reduced user engagement, delays, and high admin workload.
🎯 Goal
Automate the qualification process to improve UX and reduce admin work.
🤝 Target User
TikTok content creators (requesting product samples) and platform admins (reviewing eligibility).
✔️ Design Requirements
Auto-qualify users (GMV > $2000)
Showcase-first (done externally via TikTok)
Real-time feedback & fallback
Boost Creator+ participation
💡 Solution
Flip flow → Showcase first, then
check Real-time feedback → Remove manual review
Fall back ("Apply Anyway") → Prevent drop-off
🔎 Project Details
Duration
3-day design sprint
Approach
Behavioral UX decisions made under tight timeline
Tools
Figma, DaisyUI (Tailwind-based UI Component Library)
Role
Led UX → UI → handoff
Built a lean design system
Platform
Responsive Web (Mobile-first)
Focus
End-to-end qualification UX: from flow to UI
Problem Analysis
The previous process relied entirely on manual admin reviews, causing inefficiencies and delays that frustrated users and admins as the platform scaled.
👩🎨 Creators Challenges
🧑💻 Admins Frictions
Previous User Flow
Previous UI
Deriving the Solution
The solution development phase involved two potential approaches, each addressing specific user and business challenges:
Behavioral Principles That Drove the UX
With limited time for in-depth research, I applied behavioral psychology to guide fast, user-centered decisions.
Final Solution
We chose Option B "Add to Showcase First" because it:
Encouraged early action through user commitment (Commitment Bias)
Made user effort feel valuable by front-loading showcase interaction (Effort Justification)
Reduced the perceived risk of failure by adding an “Apply Anyways” fallback for unqualified users (Loss Aversion)
💡Final Solution Snapshot
Required users to add to showcase before checking eligibility
Used real-time logic for automatic Creator+ qualification
Offered fallback path for those who didn’t meet the criteria
Case 1
Qualified – Request Sample
All 3 criteria passed
(GMV, followers, post rate)
Case 2
Not Qualified – Apply Manually
One or more criteria not met
(1+ unmet)
Results & Impact
Even under tight constraints, a psychology-first approach led to real impact by boosting engagement and reducing internal effort.
Impact on Creators
Impact on admins
If I had more time…
I would have conducted deeper user testing to validate assumptions and refine edge cases.Still, applying behavioral principles helped us move quickly without compromising clarity or impact.
🎉 You’ve reached the end
