This tutorial goes from end to end: from a gap in the data to a published piece that answer engines quote.

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1. Start from a real gap

Use Content opportunities. A content opportunity is a question that users ask, where a competitor is present and you are absent. Apply an honest filter: can you credibly be the answer? If the question is about a capability that you do not have, visibility cannot help.

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2. Use the query fanouts, not the title

Open the query fanouts for the topic. They show what retrieval actually looked for. They tell you the sub-questions that the piece must answer and the words to use. Group the query fanouts by intent. One group is one piece.

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3. Write a good brief

The brief holds the analysis: the questions, the audience, and the sources. A brief from query fanouts gives the writer a list of questions, not only a subject.

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4. Generate the article, then edit it as an editor

Generate the article. Then, apply one test to each paragraph: does the paragraph answer a question by itself, without the paragraph before it? If it does not, the paragraph is not quotable, also when it reads well. Read Structuring content for LLMs.

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5. Publish so that answer engines can read it

  • Do not put the content behind a gate.
  • Do not publish it only in a PDF or a video.
  • Publish it on a URL that crawlers can read.
  • Include the schema markup.
Read Publishing content.

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6. Measure with patience

Record the date, and continue to run the topic. Then, find if the page occurs in Most cited sources. Citations come some weeks after publication. One run is not a verdict. If the page is still absent after many runs, read the sources that answer engines cite for that question. Then, compare them honestly with your page.