How We Verify Software
Unlike traditional review sites, StackVerified analyzes real usage data from 47+ companies to deliver accurate, unbiased recommendations.
The StackVerified Difference
Most software review sites rely on user-submitted reviews or sales page features. We take a fundamentally different approach:
1. Real Usage Data
We track actual software usage across our portfolio of startups and growth companies. This gives us insight into:
- True implementation costs (not just license fees)
- Migration complexity and data loss risks
- Feature usage patterns (what actually gets used vs. what's marketed)
- Team adoption rates and satisfaction
2. APEX Intelligence Platform
Our proprietary APEX system continuously monitors:
- Pricing Changes: Weekly API checks to catch hidden price increases
- Feature Updates: Automated testing of key features across plans
- Integration Health: Real compatibility testing with popular tools
- Performance Metrics: Speed, uptime, and reliability tracking
3. Expert Analysis
Every review is written by operators who have:
- Implemented the software in production environments
- Managed teams using the tools daily
- Analyzed ROI across multiple companies
- Handled migrations and integrations
Our Verification Process
- Data Collection: Aggregate usage data from portfolio companies
- Hands-On Testing: 30-day real-world usage of both platforms
- Cost Analysis: Build total cost models across different scales
- Migration Testing: Attempt data exports and imports
- Continuous Monitoring: Weekly updates via APEX automation
Confidence Scores Explained
Each review includes a confidence score based on:
- 90%+: High confidence - 30+ active installations tracked
- 75-89%: Good confidence - 15-29 installations analyzed
- 60-74%: Moderate confidence - 5-14 installations studied
- <60%: Limited data - based on testing only
Affiliate Disclosure
Yes, we use affiliate links. Here's why that doesn't compromise our reviews:
- We earn commissions from all major platforms we review
- Our rankings are based on data analysis, not commission rates
- We clearly disclose when products don't meet our standards
- Commission revenue funds our APEX testing infrastructure
Our Promise:
If our data shows a lower-commission product is better for your use case, we'll recommend it. Revenue optimization happens through volume and trust, not by misleading recommendations.
Data Freshness
Reviews are updated:
- Weekly: Pricing data and feature availability
- Monthly: Performance benchmarks and integration tests
- Quarterly: Full re-analysis with updated company data
- On-Demand: Major product updates or pricing changes
Last methodology update: January 7, 2026