American Battlefield Trust - Algolia Search Engine Implementation
Contributor · Full-Stack
Contributed as Full-Stack Developer on the Interactive Knowledge team for American Battlefield Trust
A comprehensive search engine integration to enhance search functionality, improve relevance, and optimize site performance on the American Battlefield Trust website, leveraging Algolia’s advanced search and filtering capabilities.
American Battlefield Trust: Algolia Search Implementation and Optimization
Client Background:
The American Battlefield Trust (ABT) is dedicated to the preservation and promotion of historic battlefields across the United States. The Trust’s website serves as a rich resource for visitors to explore various historical events, biographies, and learning materials. The addition of Algolia search functionality was crucial to enhancing user experience, improving content accessibility, and delivering accurate, timely search results for a broad user base.
Project Goals:
1. Integrate Algolia as the main search engine for the American Battlefield Trust website to provide fast, relevant, and user-friendly search results.
2. Optimize search functionalities to display thumbnails, biographies, and site-specific filters, ensuring that users can easily discover relevant content.
3. Implement API call reductions and optimize search query handling to manage operational costs effectively.
4. Address specific requirements for displaying curated content, handling hidden pages, and allowing editors to manage search facets and filters dynamically.
5. Improve Algolia’s search accessibility by ensuring the search dropdown and main search pages are functional across all devices and browsers.
Challenges and Solutions:
1. Thumbnail and Content Visibility:
• Challenge: Ensuring that all search results, particularly Map Tours and specific historic site itineraries, display appropriate thumbnails.
• Solution: Configured Algolia’s thumbnail settings to prioritize a “Square-ish” crop across results, replacing the default 4:3 ratio to create a cohesive visual presentation.
2. Hidden Content Management:
• Challenge: Pages marked as “Do not list in search” occasionally appeared in search results, affecting user privacy and content control.
• Solution: Enhanced Algolia filtering to respect hidden page flags in search results, especially in the dropdown search, aligning visibility with the Trust’s guidelines.
3. Performance Optimization with Debounce Functionality:
• Challenge: High volumes of API calls due to per-character query triggers increased operational costs.
• Solution: Implemented debouncing in the search query input, reducing calls per search by only triggering API requests after the user pauses typing. This reduced the load on Algolia, managing costs without compromising search responsiveness.
4. Topics and Tags Filter Consistency:
• Challenge: Search filters for Topics and Tags occasionally failed to apply correctly, particularly across different devices and browsers.
• Solution: Standardized the Topics and Tags filter logic, ensuring smooth functionality across all browsers by adjusting dropdown elements and including faceted checkboxes to maintain filter consistency.
5. API Usage Management and Cost Reduction:
• Challenge: Managing the Algolia operation limits within budget due to frequent empty search queries and external crawler activity.
• Solution: Adjusted API key configurations to restrict usage to the primary ABT domains, blocked Google from crawling facets via robots.txt, and reviewed custom rules to minimize redundant query triggers.
Deployment and Testing:
• Incremental Deployment: Changes to Algolia’s configuration and JavaScript were deployed incrementally on multidev environments to minimize risks and ensure stability.
• Thorough Testing Across Platforms: The search functionality was tested on desktop and mobile platforms, with particular attention to the dropdown search and Topics filter consistency across different browsers.
• Usage Monitoring: Algolia usage reports were actively monitored post-deployment to ensure that debouncing and optimizations successfully controlled API call volumes within limits.
Results:
• Enhanced Search Relevance: Users now experience faster, more relevant search results with curated thumbnails, accurate filtering by Topics and Tags, and optimized search query handling.
• Improved Accessibility and Usability: The Algolia implementation now adheres to ABT’s user experience standards, providing a seamless, accessible search experience across all devices.
• Cost Efficiency Achieved: The API usage management measures effectively reduced operational costs, enabling ABT to stay within budget while retaining a high-quality search experience for users.
Value Added:
• Strategic Search Enhancements: By fine-tuning search facets, thumbnails, and hidden content management, we ensured that users can reliably find the content they need while ABT maintains control over visibility and relevance.
• Operational Cost Control: Debouncing and usage restriction measures effectively reduced unnecessary API calls, demonstrating a balanced approach to cost-efficient, high-quality search experiences.
• Long-Term Usability: The improvements made to Algolia’s implementation establish a robust foundation for future scalability, ensuring ABT’s search infrastructure can adapt to growing content and user demands.
Have an AI project in mind or need a secure, reliable system built? Let's talk.