The YouTube Algorithm Is Changing
YouTube’s algorithm in 2025 is evolving, making content discovery more selective than ever. In the past, videos had a fair shot at being seen regardless of the topic. But now? Creators are noticing unpredictable trends—videos spike in recommendations, drop off suddenly, and then surge again weeks later. While it might seem random, there’s a method to the madness.
YouTube Now Pulls Audiences Instead of Pushing Content
One of the biggest shifts? YouTube no longer randomly pushes content to users. Instead, the algorithm “pulls” audiences toward videos based on signals that show value and interest. Essentially, YouTube is mimicking human behavior—like an automated word-of-mouth system. If someone finds a video engaging, they naturally share it. YouTube’s AI is designed to detect these signals and ensure content reaches the right viewers.
Time of Day and Device Type Influence Recommendations
The algorithm now considers when and how people watch videos. Key factors include:
- Time of day: Morning recommendations favor news and educational content, while evenings lean towards entertainment.
- Device type: Mobile users see more Shorts, while TV viewers get more long-form content.
- Posting strategy: Creators should analyze YouTube Analytics to post just before peak viewing times to maximize engagement.
Watch Time Matters Less Than Viewer Satisfaction
While watch time is still a factor, YouTube now prioritizes viewer satisfaction. What does that mean for creators?
- It’s not just about keeping people watching—it’s about how they feel after watching.
- Engagement signals like likes, shares, and qualitative feedback are more important than just minutes watched.
- Comparing watch time across channels or niches is pointless—audience behavior varies too much.
Expect Natural Fluctuations in Views
Creators need to stop panicking over dips in views. A drop doesn’t mean failure—it’s a signal. Reasons for declining views include:
- Audience interests shifting to new topics.
- Oversaturation of a niche or content style.
- A viral trend losing steam.
Instead of fearing dips, use them as feedback to evolve your content strategy.
AI and Large Language Models Are Reshaping Recommendations
YouTube is using AI more than ever to analyze and contextualize content before it even goes live. These advanced models can:
- Understand the deeper meaning of videos.
- Predict audience engagement before publication.
- Improve recommendations with better precision.
For creators, this means understanding how their content fits into a broader audience landscape will be a massive advantage.
The Key to Success: Prioritize Audience Value
At the end of the day, the creators who will thrive are those who focus on value over quick hacks. Sure, optimizing for session time and CTR helps, but long-term success comes down to:
- Understanding what resonates with your audience.
- Creating content that keeps viewers engaged and satisfied.
- Adapting to shifts in the platform and audience preferences.
YouTube isn’t what it was five years ago—but that’s not a bad thing. If you stay adaptable and focused on delivering real value, the platform still offers massive opportunities for growth.
Are you adjusting your content strategy for these changes? Let me know your thoughts!
Theory of YouTube 