Solve.rs: Building our own Growth Intelligence engine
GSC + GA4 integration with a custom AI analysis layer. Weekly opportunity reports, intent-mapped content gaps, and conversion friction detection — all internal, all measurable.
- Client
- Solve.rs (Internal)
- Industry
- Growth Architecture
- Timeline
- 6 weeks
- Status
- Live & Improving
- Link
- Homepage →
Manual analysis doesn’t scale
- We needed real-time growth intelligence, not monthly reports
- GSC and GA4 data sat in silos and needed manual analysis
- Content gaps identified too late to act on trends
- No systematic way to map user intent to content
- Conversion friction points difficult to detect early
Automated growth intelligence
- Built custom GSC + GA4 integration layer
- Implemented AI-powered analysis for weekly insights
- Created intent mapping system for content strategy
- Automated opportunity detection and prioritization
- Built conversion friction detection with actionable alerts
Measurable impact
What the System Detects
The system continuously monitors multiple data sources and generates actionable insights across six core areas.
Keyword Opportunities
Identifies rising queries, position improvements, and untapped keywords with search volume.
Content Gaps
Maps user intent to existing content, surfaces missing topics and weak coverage areas.
Conversion Friction
Detects drop-off points, unusual bounce patterns, and conversion funnel issues.
Traffic Patterns
Analyzes seasonal trends, traffic source shifts, and engagement quality changes.
Ranking Changes
Monitors position movements, identifies volatility, and tracks competitor displacement.
Technical Issues
Flags crawl errors, indexing problems, and Core Web Vitals degradation.
System efficiency and output
Beyond time savings, the system fundamentally changed how we operate — from reactive to proactive growth.
Data sources integrated
GSC, GA4, internal analytics, conversion events, traffic sources
Automated insights weekly
Keyword opportunities, content gaps, friction points, traffic patterns
Reduction in manual work
Automated data collection, analysis, and report generation
Faster opportunity response
From spotting a trend to shipping content or a fix
Tech stack and architecture
Data Integration
- Google Search Console API
- Google Analytics 4 API
- Custom data pipelines
- Real-time sync
AI Analysis Layer
- Claude API
- Custom prompts
- Intent classification
- Trend detection
Storage & Processing
- PostgreSQL
- Supabase
- Time-series optimization
- Indexed queries
Automation
- Scheduled jobs
- Alert system
- Report generation
- Action recommendations
6 weeks from concept to production
API Integration & Data Model
- GSC API setup and historical data import
- GA4 API integration and event tracking
- Database schema for time-series analytics
- Data normalization and quality checks
- Authentication and access control
AI Analysis Layer
- Custom prompt engineering for insights
- Intent mapping algorithm development
- Content gap detection logic
- Conversion friction identification
- Opportunity scoring system
Automation & Reporting
- Weekly report automation
- Real-time alert system
- Dashboard visualization
- Action prioritization logic
- Integration testing
Refinement & Launch
- Insight accuracy validation
- Performance optimization
- Report template refinement
- Internal user training
- Production launch
Key learnings from this project
Data Quality Beats Data Volume
15 curated data sources with clean integration beat 50 disconnected dashboards. Clean, normalized data lets the AI produce accurate insights instead of hallucinating patterns.
AI Needs Context, Not Just Data
Raw API data means nothing without business context. We built custom prompts that understand our growth goals, content strategy, and conversion funnels to generate actionable insights.
Automation Amplifies Expertise
The system doesn’t replace growth expertise — it amplifies it. Automated analysis saves 3 hours per week, letting us focus on strategy and execution instead of spreadsheets.
Build Internal First, Productize Later
Using our own growth system internally validates every feature and insight before we ever consider turning it into a product. Real-world stress testing beats theoretical features.
Want your own Growth Intelligence system?
We can build a custom growth intelligence system for your product using the same architecture and AI analysis layer we use internally. Real-time insights, automated reports, actionable recommendations.
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