Analyzing Your Brand Visibility Changes
Knowing whether your Answer Engine Optimization (AEO) efforts moved the needle is the difference between strategic iteration and expensive guesswork. Melanie walks you through the exact analytics workflow in AirOps to connect your content actions to measurable visibility outcomes, and shows you how to diagnose every underperforming prompt until you find the fix.
What You'll Learn
Analyzing your brand visibility changes
You've built your brand foundation, read the competitive landscape, and taken action. You refreshed pages, published new content, and started off-site outreach. Now comes the question that determines whether any of it was worth the investment: did it work?
This lesson walks you through how to answer that question with data using AirOps Insights. Melanie covers the visibility tab, tags, the prompts page, and how it all maps back to the FACT diagnostic framework so you can connect specific actions to specific outcomes.
Start with the visibility tab
The visibility tab on the AirOps analytics dashboard is your starting point for measuring impact. It tracks three core metrics over time:
- Mention rate: how often AI engines mention your brand in their answers
- Share of voice: your brand's share of mentions relative to competitors
- Average position: where your brand appears in AI-generated answers
You can break these down by topic, by platform, and against competitors across all AI engines.
Filter by topic to see your momentum
When you've invested in a specific area, filter the visibility tab to that topic. For example, if you ran a content refresh sprint on your AI website builder pages, select that topic and watch the trend line.
- A climbing mention rate signals the market is responding to your work.
- A flat or declining trend tells you something needs to change.
As Melanie explains, Answer Engine Optimization (AEO) doesn't work like traditional SEO. You won't see a single rank jump. You're looking for trend direction across a set of prompts over a period of time, not point-in-time snapshots. LLMs are probabilistic, so the macro view matters more than any individual data point.
Use tags to measure specific initiatives
Topics can be broad, especially category-level topics. If you ran a focused sprint (refreshed 30 pages over two weeks, published a batch of comparison content), you need a tighter lens. Tags give you that precision.
- Tags organize prompts into custom groupings beyond topics.
- Create tags that map to specific initiatives: "webflow landing page sprint," "arch-refresh batch," or "product launch pages."
- Tags are optional and flexible. Add as many as you need to keep measurement aligned to your actions.
How to tag your prompts
- Navigate to the prompts page in AirOps.
- Select the prompts you want to group using the checkboxes.
- Click "add tag" in the toolbar that appears.
- Choose an existing tag or type a new name to create one on the spot.
Filter the visibility tab by tag
Once your prompts are tagged, return to the visibility tab and filter by that tag. Now you see the trend line for the exact prompts affected by your initiative, not the entire topic. This is how you connect a specific set of actions to a specific set of outcomes.
Diagnose results on the prompts page
The visibility tab shows the trend. The prompts page shows you what's driving it.
Filter the prompts page by your relevant tag. The prompts table displays each tracked prompt alongside:
- Topic and tags
- Prompt volume
- Mention rate and citation rate
- Per-platform mention rate breakdown (ChatGPT, Gemini, Perplexity, AI Mode, and Claude)
Use this view to identify wins and gaps:
- Prompts where mention rate or citation rate moved up are your wins.
- Prompts that didn't improve as expected are where diagnostic work begins.
Walk underperforming prompts through the FACT framework
The FACT framework is the diagnostic model introduced earlier in the course. Each gate helps you ask a different question about why your content isn't earning the citation.
- Findable: Is your page being discovered by AI engines?
- Agent-Aligned: Does your meta information signal the right answer so the model retrieves the page?
- Citable: Does your content offer something the model can't assemble from other sources?
- Trusted: Are third parties amplifying your brand?
Gate 1: Findable
Navigate to the page you'd expect to drive results for the underperforming prompt. Pull it up in Page360 and check whether it has impressions.
- If it has impressions, your page is being discovered. The issue is downstream. Move to gate 2.
- If it has no impressions, pause here. You may have a technical issue preventing the page from being surfaced (indexability, crawl access, or something else blocking the AI engine). Solve for that before moving forward.
Gate 2: Agent-aligned
If the content is findable but you're not getting mentioned, verify that your page signals match user intent.
- Does your title use the same language your audience searches with?
- Does the meta description preview the answer?
- Does the page format match the query type?
AI agents decide whether to open your page based on URL, title, and snippet before they read your content. Melanie recommends previewing your page's meta information on a tool like Open Graph. Paste your URL, see the title, description, and image that AI engines see as the "cover" of your page, then compare back to the prompt you're trying to win.
Gate 3: Citable
If your content is findable and the signals look right, but citation rate is still underperforming, the issue is on-page.
Check the query fan-out view for the prompt in AirOps. It shows the subqueries AI engines generate: the specific angles and variations they search for. Use those fan-out queries to prioritize your work:
- Which topics need more depth?
- Which angles are missing?
- Which subqueries aren't you covering?
Instead of guessing what to improve, let the fan-out guide your editorial decisions. Add original data, sharpen the answer, and improve information gain on the page.
Gate 4: Trusted
If your on-site content is strong and you want to accelerate growth, look at who else is getting cited for that prompt. Find the third-party answers in the citations: review sites, editorial roundups, and comparison pages that AI engines pull from. Reach out to get your brand mentioned there.
The full diagnostic loop
Here's how the pieces fit together:
- Start at the visibility tab. Filter by topic and tags to see whether your actions moved the needle.
- Go to the prompts page. Identify the prompts that didn't improve.
- Walk each underperforming prompt through the FACT gates to find where it breaks down.
- Is the page being found?
- Are the signals aligned?
- Is the content earning citations?
- Is it time to expand off-site?
Every underperforming prompt has an answer somewhere in that sequence. You now have a repeatable way to go from "this isn't working" to "here's exactly what to fix next."
Key takeaways
- One data point tells you nothing in AEOUnlike SEO, where a single rank check can confirm progress, Answer Engine Optimization (AEO) relies on probabilistic AI engines. The same prompt can produce different answers at different times. You need multiple data points across weeks before a trend becomes meaningful.
- Tags turn broad topics into precise measurementCategory-level topics are too wide to measure a focused sprint. Creating tags like "webflow landing page sprint" or "product launch pages" lets you isolate the exact prompts tied to a specific initiative and filter your visibility data accordingly.
- Zero impressions means a technical problem, not a content problemWhen a page has no impressions in Page360, the FACT framework tells you to stop optimizing content and start debugging discoverability. Indexability issues, crawl access restrictions, or blocked resources are likely preventing AI engines from finding the page at all.
- Fan-out queries replace guesswork with a data-driven editorial planEach prompt can generate 8 to 12 subqueries covering different angles like pricing, features, integrations, and reviews. The fan-out view shows you exactly which subqueries your content doesn't cover, turning "what should I improve?" into a specific list of gaps to fill.
- Preview your page's cover before optimizing its contentAI agents see your URL, title tag, and meta description as a "cover" before deciding whether to read the page. Melanie recommends using a tool like Open Graph to preview those signals and compare them against the prompt you're trying to win. If the cover doesn't match, the content never gets read.
FAQs
Share of voice in AI search is the percentage of AI-generated responses that mention your brand compared to competitors for a given set of prompts. You calculate it by dividing your brand's mentions by the total mentions across all tracked competitors. Tracking share of voice over time reveals whether you're gaining or losing ground relative to competitors on specific topics.