Create One Original Data Point Per Topic

LLMs do not need to cite content that restates what they already know. When your article reads like a summary of things that are already widely published, there is no reason for an AI to retrieve and cite it - it already has that information from training. What gives AI tools a reason to cite you is something they cannot get elsewhere: original data, first-hand results, or a unique angle that adds new information to the conversation.

You do not need a research budget or a survey tool to create original data. Some of the most-cited content comes from simple, manual observation. Test a tool yourself and publish the actual results with screenshots. Count something no one has counted before - "I checked the top 50 marketing blogs and here is which schema types they use." Compile publicly available data into a comparison no one else has assembled. Document a specific mistake you made and exactly what the fix was, with real numbers.

The key principle is that your content must contain at least one data point, observation or conclusion that an AI tool could not have generated on its own from its training data. One original insight per page is enough. It makes your content citable where a competitor's version of the same topic is not.