Third-Party Citation Prioritization Framework
A model for deciding which third-party sources are worth targeting for AI-search citation influence, rather than pursuing coverage indiscriminately. Introduced by Aleyda Solis in 2026.
The problem it solves
Everyone in this field now agrees that third-party sources drive AI citation. Almost nobody says which third parties, and the honest answer is that they are not equal: some are heavily retrieved by models, most are not.
The framework supplies criteria for choosing: how often a source is actually drawn on in the answers that matter to you, how attainable a placement is, and how much a mention there would move anything.
Why it beats a coverage list
Traditional digital PR chases domain authority, which measures link value to a ranking system rather than retrieval value to a model. The two lists overlap but are not the same list.
Some heavily-cited sources are unglamorous: forums, review platforms, niche trade publications, community wikis. A framework that surfaces those beats one that sends everyone at the same national titles.