How to Target Questions AI Answers Poorly or Where Your Site Is the Primary Source

What does a poorly answered question look like?

Inconsistency is a particularly useful signal. Research on language model hallucination has found that when a model genuinely knows something, repeated answers tend to agree. Invented facts vary from sample to sample. OpenAI researchers have also argued that models guess when uncertain because training rewards guessing over admitting uncertainty. A question that gets a different answer each time is a question the model cannot anchor.

Where is your site the primary source?

You are the natural primary source for:

• Your own product or service: features, limits, prices, integrations, availability, policies.
• Your own data: customer surveys, benchmarks, anonymised usage patterns, test results.
• Your methods: how you do something, in enough detail to be useful.
• Your local market: prices, rules, suppliers and conditions in the area you serve.
• Your niche: specialist knowledge in a narrow field where few others publish.
• New things: a launch, a change in rules affecting your customers, a new version.

When an assistant answers these questions badly, the fix is almost always a page from you. Google's guidance on AI search encourages exactly this kind of non-commodity content, meaning information that is original and hard to find elsewhere.

How do you find these questions systematically?

1. Gather real questions from support tickets, sales calls, site search logs, reviews, community forums and customer interviews. Keep the customers' wording and context.
2. Run each question in ChatGPT, Gemini, Perplexity, Claude and Google, three to five times each, with web search where available.
3. Record the answer, the sources cited, and whether you are mentioned.
4. Score each answer from 1 to 3 on four criteria: accuracy, specificity, source quality and consistency across runs.
5. Mark whether you are the natural source for a better answer.
6. Prioritise questions that score low, sit close to buying decisions, and where you have the evidence to answer.

How to see which pages are cited for your questions is covered in how to find which pages AI answer engines cite for your target questions.

How do you write the page that fills the gap?

• Answer in the first sentence, with the specific fact: "[Product] works offline on iOS and Android; changes sync when you reconnect. The web app needs a connection."
• Name the subject in full rather than "it", so the passage makes sense when lifted out.
• Show the evidence: data with its method, documentation links, dates, examples.
• State the date the information applies to, and update it when it changes.
• Cover the follow-up questions people ask next. Answers often draw on several related searches.
• Make it the one canonical page on the topic. Link to it from related product, help and pricing pages, and remove or redirect older pages that say something different.
• Keep it in plain HTML text, with tables for comparisons.

How to write answer-first content is covered in how to write direct-answer-first content for AI search. How to match the specific questions people ask is covered in how to create content that answers specific questions people ask AI.

Why are these questions easier to win?

For a popular question with a strong existing answer, you are competing with established pages that many sources support. For a poorly answered question, the bar is low. A single clear page with evidence can become the best available source. Studies also show AI answers do not only cite top-ranking pages. Ahrefs' 2026 analysis found that only about 38% of AI Overview citations came from the top ten organic results. So a page that answers a gap well can be cited before it ranks strongly.

Search-based answers can change within weeks of a page being indexed. Answers built from model knowledge change only with new model versions, so they lag.

What should you avoid?

• Chasing questions nobody asks. Start from real customer questions, not from keyword lists alone.
• Inventing data to fill a gap. A made-up figure that answers repeat is worse than no figure.
• Claiming more certainty than you have. If the honest answer is a range or "it depends on X and Y", say that, and explain X and Y.
• Fragmenting. Ten thin pages for ten phrasings of one question are weaker than one strong page.
• Ignoring your own errors. If an assistant gets your product wrong, check first whether your own pages are unclear or contradictory.

How do you measure the result?

Re-run the same questions monthly. Track whether answers become more accurate and consistent, whether your page is cited, and whether you are named. Track AI-referred visits to the new pages and what those visitors do next. A gap filled well usually shows up first as a citation, then as a more accurate answer, and only later as traffic.

What might an illustrative case look like?

Consider an illustrative maker of field service software whose support team kept answering the same question: whether the app worked without mobile signal. Assistants answered it inconsistently. Some said yes, some said no, and one cited a four-year-old forum post. The company published a page titled "Does [product] work offline?". It opened with a two-sentence answer, followed by a table of what works offline on each platform, how syncing works, and the date the behaviour was last changed. It linked the page from its pricing and features pages. Within five weeks, ChatGPT and Perplexity cited the page and gave the same, correct answer on every run.

What do people ask about targeting AI answer gaps?

How many questions should we test?

Start with 50 to 100 real customer questions. That is usually enough to find a dozen strong opportunities.

Should we target questions where AI is already accurate?

Lower priority. Aim to be cited there too, but gaps offer quicker wins.

Do these pages need to rank in Google first?

Not necessarily. Search-based assistants often cite pages beyond the top results when they answer a question better.

What if the gap is a question competitors could answer?

Then move first, and make your page the most specific and best evidenced.