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Home recommendations favor an older evergreen video while a newer upload with better recent performance receives less surface area

Problem

Home recommendations favor an older evergreen video while a newer upload with better recent performance receives less surface area

Solution

Root Cause / Diagnostic:
YouTube's recommendation system evaluates content based on accumulated historical predictive confidence. An established evergreen video with thousands of hours of high-satisfaction watch time, steady viewer survey ratings, and proven click conversion provides the algorithm with high predictive certainty. Conversely, a new upload—even with strong early metrics—carries higher statistical uncertainty. The algorithm hedges risk by continuing to allocate prime Home surface inventory to the proven evergreen asset.

Actionable Fix:
1. Leverage the Evergreen Asset as an On-Ramp: Embed end-screen elements and pinned comments on the high-performing evergreen video directing its steady stream of viewers to the new upload.
2. Differentiate the New Upload's Semantic Packaging: Ensure the new video's title and thumbnail target a distinct sub-intent or updated angle rather than directly competing for the exact same audience keyword vector.
3. Track Combined Catalog Velocity: Monitor total channel-level watch time and views across both assets, recognizing that back-catalog dominance builds channel authority that benefits future releases.

Pro Tip:
Do not resent your top evergreen video for outshining new uploads; treat it as an automated, free marketing billboard that continuously funnels new subscribers and viewing sessions into your recent catalog.