How many queries should be in an AEO tracking query set?

Start with 50 to 100 queries covering your top brand terms, product categories, and high-intent informational questions. Expand over time to include competitor brand terms and long-tail questions. Larger sets provide better visibility data but require more monitoring effort, so balance coverage against the time you can commit to weekly checks.

How do you know which queries to track?

Pull queries from your Google Search Console data, your top-performing organic landing pages, competitor content analysis, and common questions in your niche from People Also Ask boxes and Reddit threads. Prioritize queries with commercial intent -- where showing up in AI answers directly impacts purchasing decisions.

How to Build a Query Set for AEO Tracking

A query set for AEO tracking is a curated list of search queries that you monitor across AI platforms like ChatGPT, Perplexity, and Google AI Overviews to measure whether your brand appears in the citations and answers those platforms generate. Building this query set is the foundation of any AEO measurement program -- without it, you have no way to track whether your optimization efforts are working.

Why Does a Query Set Matter?

AI search visibility is query-specific. You do not have a single "AI visibility score." You have visibility for specific questions that your audience is asking. A query set gives you a structured, measurable way to track your presence across the queries that matter to your business.

Without a query set, you are guessing. You might run a few ad-hoc searches, notice your brand appears for one query, and assume your AEO efforts are working. Meanwhile, you are invisible for the 50 other queries that drive qualified traffic and purchasing decisions. A query set turns anecdotal checking into systematic monitoring.

How Do You Select the Right Queries?

The best query set balances coverage with manageability. Four query categories should form your foundation:

Brand queries. Your company name, product names, founder names, and branded terms your audience searches. These are the queries you should absolutely own in AI search. Start with 10 to 15 brand queries.

Category queries. The generic terms for what you sell or do. If you sell AEO monitoring software, this includes queries like "best aeo tools," "how to track ai citations," and "ai search visibility tools." These are competitive -- if you show up here, your AEO efforts are working. Start with 15 to 20 category queries.

Intent queries. Questions that signal buying intent: "how much does [category] cost," "best [category] for [use case]," "[product a] vs [product b]," and "reviews of [category]." These queries sit at the bottom of the funnel where AI citations directly influence purchasing. Start with 20 to 25 intent queries.

Competitor queries. Your top competitors' brand names and their branded terms. If your competitors are getting cited for their own brand queries, you need to know. If you are getting cited on their brand queries, that is a citation share win. Start with 10 to 15 competitor queries.

How Should You Categorize Queries in Your Set?

Beyond the four query types above, add tagging dimensions that help you analyze patterns:

Platform tagging. Note which platform each query is most likely to generate AI answers on. Google AI Overviews appear for informational and how-to queries but rarely for transactional ones. Perplexity surfaces local and current-event queries well. ChatGPT covers broad educational queries.

Intent stage tagging. Label each query as top-of-funnel (awareness/education), mid-funnel (consideration/comparison), or bottom-of-funnel (purchase decision). This lets you measure visibility by funnel stage and identify gaps.

Priority tagging. Mark queries as critical, high, medium, or low based on commercial importance. If you can only check 20 queries per week, check your critical and high queries every week, and rotate through the rest on a monthly cadence.

How Often Should You Run Your Query Set?

Weekly checks for critical and high-priority queries. Monthly checks for medium and low-priority queries. AI search results change frequently -- the foundational Princeton GEO study showed that structured content can improve visibility by up to 40%, but maintain that visibility requires monitoring as new content and competitors enter the pool.

With over 900 million weekly ChatGPT users as of early 2026, the competitive landscape for AI citations moves fast. A page that gets cited today can lose its citation slot next week when a competitor publishes fresher, more structured content on the same topic.

What Tools Should You Use to Track Your Query Set?

Professional AEO monitoring tools like Otterly.ai and Peec AI automate query set tracking across multiple platforms and alert you to changes in your citation presence. These tools save the 90% of AEO tracking effort that would otherwise be manual data entry.

For teams that cannot justify paid tools yet, a spreadsheet with columns for query, platform, date checked, cited (yes/no), citation position, and competing cited brands gives you a functional DIY tracking system. The trade-off is time: manually running 100 queries across 3 platforms takes 2 to 3 hours per check.

The key decision is not tool vs spreadsheet. It is committing to the practice of systematic tracking. A query set only delivers value when it is checked consistently, documented, and used to guide optimization decisions.