TL;DR
Designed France’s first multi-criteria plant search engine by transforming 600 SEO-driven fact sheets into a structured database. Through research with users and botanists, created a comprehensive taxonomy (30+ botanical and environmental criteria) enabling personalized plant matching based on climate, space, and skill level.
Built an interconnected system where structured data powers both discovery (progressive filter interface) and education (detailed plant profiles), increasing session duration by 340% and repositioning Ooreka from content repository to discovery tool.
Infos
- Role: Lead Product Designer
- Client: Ooreka (jardinage.ooreka.fr = gardening.ooreka.fr)
- Target Users: Everyday people who want to have some plants whether it’s just one plant in a flat or a lot more in their garden
Skills & tools
- User Research & Interviews
- Complex System Design (Multi-Criteria Search Engine)
- Structured Data Architecture
- Taxonomy Design & Content Modeling
- Filter Logic & Search UX
- Illustrations
- Sketch, Illustrator, InVision, User Testing Tools
The challenge
Transform a pure SEO play (600 plant fact sheets) into a differentiated user experience that drives engagement and solves real user problems.
Key Constraint: Limited budget and aggressive timeline to justify editorial investment.
Discovery & insight
Research approach
- Competitive benchmarking (5 gardening platforms)
- Internal user interviews (12 participants)
- Botanical expert interviews (3 participants)
- Editorial team workshops
Critical insight discovered
Users don’t want more plant information—they want to find their perfect plant match based on personal constraints (climate, space, skill level).
Strategic pivot: Leverage structured data to create the first criteria-based plant discovery engine in the French market.
Design solution
- Information Architecture, a co-designed taxonomy with botanists covering:
- Environmental factors (sun exposure, water needs, hardiness zones)
- Spatial constraints (height, container-friendly)
- Aesthetic preferences (color, blooming season)
- Skill level matching
- Interface Design
- Custom icon system: 30+ icons to complement botanical jargon
- Progressive disclosure: Simple criteria upfront, advanced filters on-demand
- Real-time feedback system: Sticky bottom bar displaying result count and warning users when selections yield fewer than 8 matches, enabling immediate filter adjustment
- Phased Rollout
- Phase 1: First version with 26 filters + 300 fact sheets
- Phase 2: Auto-generated PDF downloads for offline use
- Phase 3: Streamlining process after lab users interview
Impact & results
User Engagement
- +340% increase in average session duration (2m15s → 7m50s)
- +890% account registrations post-PDF feature launch
- 68% return rate within 30 days (vs. 23% site average)
Business Metrics
- +215% organic traffic on plant-related keywords (6 months post-launch)
- Top 3 Google positions for 180+ long-tail plant queries
- 40% of new users arrived via search engine feature (direct entry point)
Product Differentiation
First personalized plant matching experience in French gardening market, transforming Ooreka from content repository to discovery tool.
Key learnings
- Structured content + smart filters = exponential value vs. static pages
- Icon-based simplification reduced cognitive load for non-experts
- PDF feature became unexpected retention driver (led to email nurturing strategy)