Additionally, the article introduces an automated tool called the Cannibalization Detector, developed with Nicole Guercia from AirOps, which automates the detection of content cannibalization through a 37-step AI workflow. This tool analyzes keyword rankings, content similarity, and historical data to generate actionable reports. The article encourages regular checks for cannibalization and stresses the importance of adjusting content strategies to prevent future issues, while also inviting feedback to improve the tool further.
Key takeaways:
- Content cannibalization occurs at the user intent level, not just the keyword level, and can affect organic traffic and revenue.
- Different types of sites, such as integrators and aggregators, have unique challenges with content cannibalization.
- Detecting cannibalization involves analyzing content similarity using techniques like cosine similarity and requires regular monitoring.
- Fixing cannibalization involves short-term actions like canonicalization and consolidation, as well as long-term strategies like creating a content roadmap and developing clear site architecture.