Case Study: How One Maker Cut TTFB by 60% and Doubled Conversions

Case Study: How One Maker Cut TTFB by 60% and Doubled Conversions

Hook: Technical improvements are not just for big SaaS companies. For one Agoras maker, a focused engineering sprint in 2025–26 reduced Time To First Byte (TTFB), improved page stability, and materially increased sales.

The business problem

A small home-goods brand experienced lost traffic during seasonal pushes and saw conversion drop-offs on product pages. The shop’s pages were image-heavy and used a monolithic database for inventory, customer, and order queries.

Actions taken

1. Layered caching: Implemented CDN caching for static assets and edge cache for rendered product snippets. The team followed proven patterns from a layered caching case study: Case Study: How One Startup Cut TTFB by 60% with Layered Caching.
2. Partitioned queries and predicate pushdown: Rewrote slow inventory queries to use partitioning and push down predicates to reduce scan times; see advanced performance techniques here: Performance Tuning: Reduce Query Latency by 70%.
3. Moved to a managed DB for critical workloads: Migrate read-heavy catalog data to a managed DB with automatic scaling and read replicas; reference managed DB comparisons: Managed Databases in 2026: Which One Should You Trust.

Results

Within six weeks the maker measured:

• TTFB reduction: 60%
• Page load improvement (First Contentful Paint): 30%
• Conversion rate lift on product pages: 2.1x baseline
• Cart abandonment reduction: 18%

Why these changes matter for small shops

Faster pages directly affect shopper trust and impulse purchase behavior. Technical spend is often seen as luxury for small brands, but the case above shows targeted engineering work focused on the catalog and checkout paths produces outsized returns.

Implementation checklist for founders

1. Audit slow pages and identify top 10 queries by median response time.
2. Introduce CDN caching and set conservative cache TTLs for product lists.
3. Refactor the worst queries using partitioning and predicate pushdown, targeting reads under 50ms.
4. Evaluate managed DB pricing and SLA against expected growth: Managed Databases in 2026.

Operational guardrails

Keep these guardrails in place to avoid regressions:

• Monitor cache hit rates and set alerts for TTL expirations around promotional pushes.
• Run load tests for peak-sale scenarios.
• Have a rollback plan for DB migrations and schema changes.

Further reading and resources

If you want practical, implementable guidance, read this performance tuning walkthrough: Reduce Query Latency by Partitioning and Predicate Pushdown, and the managed database review to pick production-ready services: Managed Databases in 2026. For a developer-facing caching playbook, this layered caching case study is a compact, actionable read: Layered Caching Case Study.

Author: Priyanka Rao — Head of Engineering, Agoras. Priyanka led the performance sprint and helped transition the maker to a modern, resilient stack.

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