================================================================================ ARTICLE: How to Design Question-Based Headings That Match Search Intent URL: https://omniscient.news/blog/question-based-headings-search-intent Published: 2026-03-20 Updated: 2026-04-01 Category: LLMO & Content Strategy Tags: headings, search intent, LLMO, keyword research, content structure ================================================================================ Headings that match the exact questions users type into AI assistants are retrieved at significantly higher rates. Here is how to research and write them. Search intent research — identifying the exact questions users type when looking for information on a topic — has been an SEO practice for a decade. In the LLMO era, this research directly identifies the H2 headings that maximise retrieval probability. An H2 heading that matches a real user query is retrieved for that query; one that doesn't match any real query may never be retrieved at all. How to Research Question-Based Headings Sources for real user queries: Google's "People also ask" (PAA) feature — the most reliable source of common follow-up questions; AnswerThePublic — visualises all question variations around a keyword; AlsoAsked — maps PAA question trees across related keywords; keyword tools (Ahrefs, SEMrush) — provide search volume data to prioritise questions. Build a spreadsheet of 10–20 real user questions for each article's topic, then select the 5–7 most important as H2 headings. This process takes 15–30 minutes and dramatically improves both SEO and LLMO performance. Frequently Asked Questions Q: undefined A: undefined Q: undefined A: undefined Q: undefined A: undefined