naverOriginal articleAnalysis of Naver Integrated Search AIB (opens in new tab)
The integration of AI Briefing (AIB) into Naver Search has led to a noticeable increase in Largest Contentful Paint (LCP) values, with p95 metrics rising to approximately 3.1 seconds. This shift is primarily driven by the architectural mismatch between traditional performance metrics and the dynamic, streaming nature of AI chat interfaces. The analysis concludes that while AIB appears to degrade performance on paper, the delay is largely a result of how browsers measure rendering in incremental UI patterns. ### Impact of AIB on Search Performance * Since the introduction of AIB’s chat-based UI in July 2025, LCP p95 has moved beyond the 2.5-second target, showing a direct correlation with AIB traffic volume. * The performance degradation is characterized by a "tail" effect, where a higher percentage of users fall into slower LCP buckets despite stable server response times. * Unlike Google’s AI Overview, which renders in larger blocks, Naver’s AIB uses word-by-word animations and frequent UI updates that place a heavier burden on the browser's rendering engine. ### Client-Side Rendering Bottlenecks * Performance profiling indicates that the delay is localized to the client-side rendering phase rather than the network or server. * Initial rendering includes a skeleton UI period of roughly 900ms, followed by sequential text animations that push the final paint time back. * Comparative data shows that when AIB is the LCP candidate, the p75 value reaches 4.5 seconds—significantly slower than other heavy components like map modules. ### Structural Misalignment with LCP Measurement * **DOM Reconstruction:** After text animations finish, AIB rebuilds the DOM to enable citation highlighting and hover interactions, which triggers Chromium to update the LCP timestamp to this much later point. * **Candidate Fragmentation:** Streaming text at the word level prevents the browser from identifying a single large text block; instead, small, insignificant fragments are often incorrectly selected as the LCP candidate. * **Paint Invalidation:** Chromium’s rendering pipeline treats every new word in a streaming response as a layer update, causing repeated paint invalidations that push the `renderTime` forward frame-by-frame until the entire message is complete. ### New Metrics for AI-Driven Interfaces * To more accurately reflect user experience, Naver is shifting toward Time to First Token (TTFT) as a primary metric for AIB, focusing on how quickly the first meaningful response appears. * Standard LCP remains a valid quality indicator for static search results, but it is no longer treated as a universal benchmark for interactive AI components. * Future performance management will involve more granular distribution analysis and "predictive" performance modeling rather than simply optimizing for a single threshold like the 2.5-second LCP mark. To effectively manage performance in the era of generative AI, organizations should move away from relying solely on LCP for streaming interfaces. Implementing TTFT as a complementary metric provides a better representation of perceived speed, while optimizing the timing of DOM reconstructions can prevent unnecessary measurement delays in Chromium-based browsers.
