Case Study: How Layered Caching Cut Menu Load Times and Recovered Revenue

Case Study: How Layered Caching Cut Menu Load Times and Recovered Revenue

Hook: When menus load instantly, guests order faster and conversion improves. This case study walks through a layered caching rollout that cut TTFB by 60% and recovered lost sales.

Background

A mid-sized restaurant group with twenty locations faced slow menu loads during peak hours. The group used a single centralized menu API and suffered from origin overload and a bloated client bundle. The engineering and ops team targeted three objectives: reduce TTFB, improve cache hit rates, and provide robust offline fallbacks.

Approach

1. Edge caching: Push static menus and serialized variants to the CDN with short TTLs for rapid updates.
2. Service worker PWA: Build a progressive web app with a service worker that serves a cached shell and updates the payload asynchronously.
3. Origin optimization: Layered caching at the application and database tiers, plus a performance audit to prune large response payloads.

These patterns mirror the improvements seen in external engineering writeups; the techniques align with a practical case study at Case Study: How One Startup Cut TTFB by 60% with Layered Caching.

Outcomes

• TTFB improvement: 60% median reduction during peak hours.
• Cache hit rate: Increased from 40% to 87% for menu payloads.
• Revenue impact: Conversion on mobile menus rose by 7% and average order value (AOV) grew by 4% in the first month.

Operational changes

Beyond engineering, the company adjusted the content strategy: smaller image assets, fewer synchronous third-party calls and explicit cache-invalidation hooks when an item sells out. For teams who run support and privacy-sensitive data, coordinate caching with legal expectations using guides like Customer Privacy & Caching: Legal Considerations for Live Support Data.

Lessons learned

• Measure before you change: Baselines are essential to attribute revenue impact.
• Cache conservatively for availability: Err on the side of showing conservative availability when sync fails.
• Cross-team alignment: Ops, marketing and kitchen staff must understand the cadence of menu updates.

How to start

1. Audit current TTFB and establish 95th percentile targets.
2. Implement a small PWA shell and local cache for your highest-frequency pages.
3. Introduce a CDN with event-driven invalidation for inventory changes.

Closing

Layered caching is a multiplier for menu reliability and conversion. The case study here demonstrates quantifiable recovery in revenue and customer satisfaction. If you need a reference implementation, review engineering case studies and vendor guides on layered caching at caches.link.