Boost
Optimizing Performance and Enhancing Search for a SaaS Platform
A leading asset management SaaS platform serving 50,000+ users faced slow search speeds, inefficient filtering, and rising AWS costs. We migrated search to Elasticsearch, implemented caching, and optimized database queries, leading to 15x faster search, 40% quicker filtering, and an 18% reduction in server costs. As a result, user retention improved by 12%, significantly enhancing the platform’s efficiency, scalability, and competitiveness.
Overview:
A well-established SaaS company specializing in asset management was experiencing severe performance bottlenecks. With 50,000+ active users, the platform allows businesses to track, manage, and analyze assets efficiently. However, as the user base grew, performance issues began affecting the platform’s usability and operational costs.
Key Challenges:
🔴 Slow Search Performance – Users had to wait 4-6 seconds for search results, negatively impacting productivity.
🔴 Inefficient Filtering System – Filtering assets based on categories, location, and custom fields became slow, affecting 10,000+ daily queries.
🔴 High Server Costs – Due to inefficient queries and database load, AWS costs surged by 25%.
The company sought a high-performance solution that would reduce response times, enhance user experience, and optimize resource costs.
Solution Implemented:
To address these issues, we conducted an in-depth analysis and implemented a multi-layered optimization strategy:
✅ Migrated Search to Elasticsearch – Enabled advanced indexing and query processing, significantly boosting search speeds.
✅ Implemented Caching for Filters – Integrated Redis caching, reducing repetitive queries by 30%.
✅ Optimized Database Queries – Refactored SQL queries, added proper indexing, and restructured database operations to improve response times and reduce load.
This holistic approach ensured faster performance, cost savings, and long-term scalability for the platform.
Results:
- Search performance improved from 4-6 seconds to 300-500ms, making queries 15 times faster.
- Filter response times were reduced by 40%, allowing users to navigate and retrieve data more efficiently.
- AWS costs were reduced by 18%, lowering infrastructure expenses and improving resource management.
- User retention increased by 12%, as the improved speed and responsiveness encouraged more engagement.
- The platform became more scalable, ensuring future growth without performance issues.
By implementing search and performance optimizations, the platform transformed into a high-speed, cost-efficient, and scalable system. Users now experience faster search and filtering, allowing them to manage assets seamlessly and effectively. These improvements not only boosted productivity but also helped the company maintain a competitive edge in the SaaS market.
"The performance boost drastically improved user engagement. Our customers now complete searches in seconds, making our platform significantly more competitive."