TL;DR — Open Insights > Query Fan-Out and filter by your product area to see queries real users are asking AI tools in your category. Use the “Add to Prompts” button for queries you want to track visibility on, and “Create Content” for queries where no strong source exists yet. Cross-reference with Strategy > GSC for high-impression, low-click keywords that suggest users are getting answers from AI instead. Pro tip: filter Query Fan-Out by a competitor’s brand name to find the competitive battles you are not even monitoring yet.
The Question
“How do I use Query Fan-Out to discover prompts I should monitor?”Monitoring prompts you guessed at during onboarding is a starting point, not a strategy. Query Fan-Out surfaces what real users are actually asking AI tools about your category — including phrasings, intent variants, and topics you would not have thought to monitor. More importantly, it distinguishes two different things you can do with a discovered query: add it to your monitoring set (to track AI visibility on it) or create content to answer it (to fill a gap where no strong source exists yet). This page covers both workflows in detail. You might also be wondering:
- “What is the difference between ‘Add to Prompts’ and ‘Create Content’ in Query Fan-Out?”
- “How does Qwairy know which queries are being asked in my category?”
- “How many prompts should I be monitoring in total?”
Where to Go in Qwairy
Start here: Insights > Query Fan-Out
Navigate to Insights > Query Fan-Out — your query discovery hub.
Query Fan-Out shows a continuously updated list of queries being asked in your category across AI platforms. Each query card shows: the query text, estimated search volume or frequency signal, the current AI citation landscape (whether any strong sources are consistently cited, or whether the answer space is contested or empty), and two distinct action buttons: Add to Prompts and Create Content.
Begin with a keyword or topic filter matching your primary product area. Scan the results for queries that are high-frequency, relevant to your business, and not already in your monitoring set.
Go deeper: Two Distinct Workflows
Workflow 1: Add to Prompts — Use this button when the query is a genuine category question where your brand should appear in AI answers and you want to track your visibility on it. Clicking “Add to Prompts” takes you directly to the monitoring setup for that query, pre-filled with the query text, so you can assign a topic tag, funnel stage, and run frequency before adding it to your monitoring set. This workflow grows your measurement coverage.Workflow 2: Create Content — Use this button when the query is a topic gap where AI models have no strong source to cite and you want to fill that gap with new content. Clicking “Create Content” opens the Content Studio pre-loaded with the query as the target topic, letting you immediately start an outline or brief for content designed specifically to answer this query and earn AI citations. This workflow grows your content coverage.The two workflows are complementary: ideally, you add a query to monitoring AND create content to answer it, so you can track your visibility improvement on that specific query after publishing.
Complete the picture: Strategy > GSC + Workspace > Monitoring
Cross-reference Query Fan-Out findings with Strategy > Google Search Console.
GSC surfaces queries where your pages appear in traditional search results but users are not clicking — a strong signal that users may be getting the answer from an AI tool instead. These are among the highest-priority queries to add to monitoring: your brand already has some presence, the query clearly exists, and the traffic opportunity is being captured by AI rather than by your own click.
After adding new prompts to monitoring via Query Fan-Out, review the full updated list in Workspace > Monitoring to ensure proper tagging, topic assignment, and run frequency.
What to Look For
Query Fan-Out — Query Card Signals
Each query card contains the information you need to make the “monitor vs create content” decision quickly. The citation landscape signal is the most important: if top AI platforms are already consistently citing 2–3 strong sources for a query, the create-content ROI is lower (strong competition). If the citation landscape is empty or citing low-authority fallbacks, create-content ROI is very high — you can earn first-mover citation advantage with good content.| Signal | Add to Prompts? | Create Content? |
|---|---|---|
| High frequency, empty citation landscape | Yes — track your first entry | Yes — high creation ROI |
| High frequency, competitor dominates citations | Yes — track competitive gap | Maybe — assess competition depth |
| Low frequency, empty citation landscape | Maybe — niche monitoring | Yes — low competition, easy win |
| Already in monitoring set | Skip | Review content quality |
Monitoring Coverage — How Many Prompts
A well-calibrated monitoring set has enough prompts to be statistically meaningful but not so many that credit usage is unsustainable. General guidance: 15–30 prompts for a focused product, 30–60 prompts for a multi-product company with multiple audience segments. Query Fan-Out is the tool for systematic expansion — use it quarterly to discover new prompts as your category evolves and as new AI query patterns emerge.Pro Tip: Filter Query Fan-Out to your main competitor’s brand name to find queries where a competitor appears in AI answers but you do not. These are the highest-priority prompts to add to monitoring — you are not tracking competitive battles you are currently losing. The visibility data on these prompts will also drive the most compelling stakeholder presentations: “We are absent in 68% of AI answers where our main competitor appears.”
Filters That Help
| Filter | How to use it for this question |
|---|---|
| Topic / keyword | Focus discovery on a specific product area or use case — avoids overwhelming the prompt set with broad, low-priority queries |
| Funnel stage | Filter to decision-stage queries specifically — these have the most direct impact on pipeline and are often the most under-monitored |
| Citation density | Filter to “low citation density” to find the highest-ROI create-content opportunities where no strong source exists yet |
How to Interpret the Results
Good result
Query Fan-Out surfaces 10–20 new high-relevance queries per quarter that are not yet in your monitoring set. At least 5 of these have empty or low-authority citation landscapes (create-content opportunities). After adding the top 10 to monitoring and publishing content for the top 5 gaps, your monitoring set is both more comprehensive and directly tied to active content investments — creating a closed loop between measurement and action.Needs attention
Query Fan-Out shows very few new queries after the initial setup — this usually means the topic filter is too narrow or the category is small enough that query discovery is exhausted quickly. Try broader synonyms for your category. Or: Query Fan-Out surfaces hundreds of queries but they are all too generic to be actionable for your brand (e.g., “what is software”) — tighten the topic filter to your specific product differentiators rather than your entire category. Or: all discovered queries already have dominant high-authority sources with deeply established citation patterns — this indicates a highly competitive category where content quality alone will not be sufficient and citation-building via partnerships is the necessary next step.Example
Scenario: A real estate technology platform connecting property buyers with agents and listings runs a quarterly Query Fan-Out review to expand their 22-prompt monitoring set and discover queries that prospective homebuyers are asking AI tools.
- Open Insights > Query Fan-Out and filter to “real estate” and “property buying.” 53 query cards appear. Apply the “Low citation density” filter — 21 remain. Scan the 21 for business relevance to the platform’s core offering of connecting buyers with listings and agents.
- The highest-priority discovery: “best real estate platforms for first-time buyers 2025” — high frequency, no dominant source cited, directly relevant to the platform’s primary audience. Click Add to Prompts: assign to the “first-time buyers” topic tag, decision funnel stage, weekly frequency. Also click Create Content: open Content Studio with this query as the target and start a brief for a “first-time buyer guide with platform comparison.”
- Second discovery: “how to find a buyer’s agent in [city] who negotiates well” — medium frequency, low citation density, aligns with the platform’s agent matching feature. Add to Prompts (agent matching topic tag, consideration stage) AND Create Content (a guide on “what to look for in a buyer’s agent” optimized for AI citation with the platform’s agent profiles as supporting evidence).
- Third discovery: “Zillow vs Redfin vs alternatives for home search” — high frequency, competitor names dominant in citations. Add to Prompts (competitor comparison tag, decision stage) — this is a must-monitor prompt to track the competitive battle against the major incumbents. Do not create content immediately; assess the platform’s existing comparison pages first before deciding whether to invest in a head-to-head comparison guide.
- After the session: 7 new prompts added to monitoring (from 22 to 29), 3 content briefs queued in Content Studio. Review in 30 days to check baseline visibility on the new prompts and verify whether the first-time buyer guide starts earning citations.
Go Further
Discovered prompts dashboard
Build a discovered prompts dashboard in Looker Studio using the search-insights data source
Query Fan-Out guide
Read the Query Fan-Out documentation for the complete guide to automatic prompt discovery
Auto-discover prompts via Claude
Connect the Qwairy MCP server to Claude to automate prompt discovery and add new monitoring queries
Related Questions
Am I monitoring the right prompts?
Audit your full prompt set for coverage gaps before running a Query Fan-Out expansion
How do I create content AI models are likely to cite?
Turn Query Fan-Out Create Content findings into AI-optimized content
What are the highest-priority actions to improve AI visibility?
Combine Query Fan-Out findings with the full prioritized action queue