Product Strategy
Product Management
Data-driven product development with customer research, impact-based prioritization, and continuous experimentation.
47
Features Shipped
This Quarter
72
Customer NPS
+8 YoY
12
Active Experiments
Running
156
User Interviews
This Year
RICE Framework
Quantitative prioritization using Reach, Impact, Confidence, and Effort scoring.
# RICE Scoring Framework ## Formula RICE Score = (Reach × Impact × Confidence) / Effort ## Scoring Guide ### Reach (users/quarter) - 10,000+ users → 10 - 5,000-10,000 → 7 - 1,000-5,000 → 5 - 500-1,000 → 3 - < 500 → 1 ### Impact (on key metric) - Massive (3x) → 3 - High (2x) → 2 - Medium (1.5x) → 1 - Low (1.2x) → 0.5 - Minimal → 0.25 ### Confidence (in estimates) - High (data) → 100% - Medium (some) → 80% - Low (guess) → 50% ### Effort (person-weeks) - 1-2 weeks → 1 - 3-4 weeks → 2 - 1-2 months → 4 - Quarter → 8 # Example: Batch Valuation API Reach: 5,000 (score: 7) Impact: High (score: 2) Confidence: High (score: 1.0) Effort: 3 weeks (score: 2) RICE = (7 × 2 × 1.0) / 2 = 7.0
Prioritized Backlog
Real-time Marketplace Data
RICE: 12.5Current
Mobile SDK (iOS/Android)
RICE: 9.8Next
Enhanced AI Explainability
RICE: 8.4Next
Sustainability Report Export
RICE: 7.2Q1 2025
GraphQL Subscriptions
RICE: 6.8Shipped
Batch Processing API
RICE: 6.5Shipped
Customer-Driven Development
Every feature backed by research and validated with experiments.
156 User Interviews/Year72 NPS Score47 Features Shipped