🌟 My Weekly Design Series: Real-Life Problems, Real Solutions 🌟
As a Product designer, I’m constantly inspired by the potential to solve real-world challenges through thoughtful design. Starting this week, I’ll be sharing a weekly series where I tackle real-life design problems from existing systems and propose innovative solutions.
🎯 What to Expect:
Deep dives into user pain points
Research-backed insights
Practical design solutions with measurable impact
Streamlining Account Recovery for Coinbase Users
Streamlining account recovery for coinbase users
Oura Ring UX Case Study: Enhancing Sleep Tracking & Readiness Score Usability | Wearable Tech | User Experience
11,738 impressions | 320 Article Views | 8,205 People Reached on Linkedin
Enhancing Apple Wallet for Better Digital ID and Ticket Management
Mixed-methods research approach and design suggestions
Levelling the Playing Field: Helping Small Sellers Thrive on Etsy Amidst Oversaturation
It all begins with an idea.
AI Assistant Adoption Journey
Progressive Trust-Building Framework for HubSpot Front Office AI
Product Design Framework
Three-phase approach to building AI trust and adoption
Trust Foundation
- Data Hygiene Assistant: AI suggests data cleanup with transparent explanations
- Meeting Notes Helper: Simple AI summaries users can edit/approve
- Template Suggestions: Email templates based on successful patterns
Confidence Building
- Smart Segmentation: AI suggests customer segments with reasoning
- Follow-up Reminders: Intelligent task creation based on deal stage
- Content Optimization: Subject line improvements with A/B tests
Advanced Capabilities
- Predictive Lead Scoring: AI qualification with transparent factors
- Deal Risk Assessment: Early warning system with actionable insights
- Cross-sell Detection: Revenue opportunities with confidence scores
Key Design Elements
Core components that build trust and drive adoption
Trust Transparency Dashboard
- AI recommendation accuracy over time
- User adoption rates and success metrics
- "AI Impact Report" showing time saved and revenue influenced
Progressive Disclosure Interface
- Shows "recommendations" before "predictions"
- Gradually introduces AI terminology
- "Show me why" explanations for all decisions
User Segmentation Strategy
- Skeptics: Data cleanup and admin tasks
- Cautious: Content suggestions and basic automation
- Early Adopters: Fast-track to predictive features
Feedback Loop System
- Thumbs up/down on every AI suggestion
- Monthly "AI Trust Score" survey
- Success story collection and sharing
User Segmentation Strategy
Tailored experiences for different comfort levels
😤 Skeptics
Start with data cleanup and administrative tasks to prove value
🤔 Cautious Adopters
Begin with content suggestions and basic automation features
🚀 Early Adopters
Fast-track to predictive capabilities and advanced features
Target Success Metrics
Measurable outcomes for the AI adoption journey