general
Pitchside Ai
Problem
The problem
High Latency: Page load times averaged 4.5 seconds during live match windows.
Conversion Friction: A clunky, non-responsive mobile UI led to a 60% bounce rate among users checking stats on the go.
Scalability Bottlenecks: During peak match times, the server frequently crashed, resulting in significant revenue loss during high-traffic broadcast windows.
Goals
What needed to happen
Reduce Latency: Bring Largest Contentful Paint (LCP) under 1.2 seconds.
Mobile First: Rebuild the interface to prioritize mobile users, who account for 85% of traffic.
Infrastructure Resilience: Implement a microservices architecture to ensure 99.99% uptime during peak concurrent load.
Conversion Optimization: Improve the lead-to-subscription funnel via a simplified, high-converting UX.We transitioned Pitchside AI from a legacy monolithic stack to a modern, serverless-first architecture:
Frontend: Migrated to Next.js 15 for superior SSR (Server-Side Rendering) and ISR (Incremental Static Regeneration).
Backend: Decoupled data processing into a Node.js/TypeScript microservices cluster using Redis for sub-millisecond caching of live sports data.
Design System: Adopted a "Mobile-First" component library, focusing on touch-friendly interactive charts and minimal friction.
Strategy
The strategy
We transitioned Pitchside AI from a legacy monolithic stack to a modern, serverless-first architecture:
Frontend: Migrated to Next.js 15 for superior SSR (Server-Side Rendering) and ISR (Incremental Static Regeneration).
Backend: Decoupled data processing into a Node.js/TypeScript microservices cluster using Redis for sub-millisecond caching of live sports data.
Design System: Adopted a "Mobile-First" component library, focusing on touch-friendly interactive charts and minimal friction.
Execution
What we shipped
Month 1 (Audit & Design): UX overhaul and database schema optimization.
Month 2 (Engineering): Migrating data pipelines to edge computing to place data closer to the UK-based user base.
Month 3 (Optimization): Implementing AI-driven predictive caching to pre-load match data before the user requests it.
Results
The result
Latency: LCP reduced from 4.5s to 0.8s.
Conversion: Paid subscription conversion rate increased by 42%.
Performance: Achieved a consistent Core Web Vitals "Pass" across all templates.
Resilience: Zero downtime recorded during the most recent FA Cup Final peak traffic surge.
Metrics
4.5s
Avg. LCP
0.8s
60%
Mobile Bounce Rate
5,000 req/s
Concurrent Load Capacity
50,000+ req/s
2.1%
Conversion Rate
3.0%
Timeline
1
Discovery & Architecture Blueprint (Weeks 1-2)
Development & Integration (Weeks 3-10)
UAT & Performance Stress Testing (Weeks 11-12)
Live Migration & Monitoring (Week 13)
Ready to transform your digital infrastructure?
Book a Discovery Call with our Engineering Team
Start with a free audit