Topics matter for third-party authority signals

Artificial intelligence models select different trusted sources for different topics, a phenomenon that significantly impacts off-property authority building efforts. For instance, when AI models process queries about invoicing, they rely on competitor domains for 33.5% of their citations. In contrast, for queries related to starting a business, competitor domains constitute only 7% of the cited sources. This indicates that the type of source AI prioritizes is highly topic-specific, requiring a tailored approach to digital PR and link-building strategies. Simply aiming for high-authority links across the board may be inefficient if those links are not relevant to the specific topics being targeted by AI search engines. The analysis suggests that a topic-based backlink strategy is crucial, focusing on acquiring links from sources that hold authority within the target topics or resonate with the relevant audience. While video and social media platforms have their own distinct mechanics and citation patterns, this analysis focuses on publisher, research, and expert sources that function as earned media. Understanding these topic-specific citation patterns allows for more targeted and effective allocation of resources in building third-party authority and enhancing AI visibility.