TLDR: AI content experiment shows massive scale brief success; long-term success likely favors quality over quantity, impacted by Google updates.
This article is a summary of a You Tube video “I Tried 7,000,000 AI Articles. Here’s What Google Did…” by Matt Diggity
Key Takeaways:
- Massive Scale AI Content: The experiment involved publishing a vast amount of AI-generated content (7 million articles) to test its efficacy in ranking on Google post the helpful content update.
- Initial High Traffic: Initially, websites publishing large volumes of content saw significant traffic; one site achieved 22,800 organic visits in a month.
- Short-lived Success: The high traffic from mass content production was not sustainable. One site’s traffic plummeted after an initial surge, suggesting Google’s potential penalization for perceived spam.
- Drop in Participation: From 174 original participants, only about 50 remained active after four months, indicating a high dropout rate due to various challenges.
- Importance of Content Quality: Sites with fewer, higher-quality articles tended to perform better over time, emphasizing the importance of content quality over quantity.
- Impact of Google’s Updates: The experiment started shortly after Google’s helpful content update, testing how AI content performs under new SEO conditions.
- Diverse Performance Across Niches: Participants in various niches experienced different levels of success, highlighting niche selection’s impact on SEO outcomes.
- Community Engagement and Sharing: Participants shared results and strategies on a community platform, fostering a collaborative environment.
- Real-Time Adjustments: The ongoing nature of the experiment allowed participants to adjust their strategies based on real-time data and results.
- Long-Term Strategy Indicators: Early indications suggest that a more methodical and quality-focused content strategy might be more effective long-term.
