A 30-Minute Self-Audit of Your Brand's AI Search Visibility

Most "AEO audits" measure the wrong things: review counts, expert mention totals, press hits. Those are lagging signals. This audit measures what actually drives citations - structured content coverage, attribute explicitness, position stability.

30 minutes, 5 sections, free tools. You'll know exactly where the gap is.

What it measures: The percentage of category buyer queries where ChatGPT cites your brand.

How to do it:

1. Write down 20 specific category queries (not "best shampoo" - rather "sulfate-free shampoo for color-treated hair")
2. Ask ChatGPT each query in a separate session
3. Mark whether your brand is cited (yes/no)
4. Citation Rate = (number cited) / 20

Benchmark

• 0-10%: Invisible. No structured content for these intents yet.
• 11-25%: Emerging. Some intents covered, most not.
• 26-40%: Established. Strong base, room to expand.
• 41%+: Leadership position in the category.

What it measures: Of the 20 queries, how many is your product actually a fit for - but ChatGPT didn't cite you?

How to do it:

1. Go back through your 20 queries
2. For each, judge honestly: does your product actually fit this intent? (Yes/No)
3. For each "Yes" where you weren't cited - that's a Missed Match
4. Missed Match Rate = (Missed Matches) / (Total Yes fits)

Benchmark

• 0-20%: Excellent. You're cited for nearly all your fits.
• 21-40%: Good. Some gaps, mostly closeable.
• 41-60%: Significant opportunity. This is your highest-leverage zone.
• 60%+: Major gap. Your product fits intents you're structurally invisible on.

Note your top 3 Missed Matches. These are your priority deployment targets.

What it measures: Whether your product pages have the four content formats AI engines preferentially cite.

How to do it:

1. Open your top 5 product pages
2. For each page, check whether these four formats are present: FAQ blocks (Q+A pairs), comparison tables (side-by-side with named competitors), claim-evidence pairs (assertion + verifiable source), and schema markup (view page source, search for "FAQPage" / "Product" / "ItemList")
3. Average across the 5 pages

Benchmark

• None of the four: Zero foundation. This is the single biggest gap to close.
• 1-2 formats present: Minimal. Most product pages have prose only.
• 3 formats present: Solid. Missing one structural piece.
• All 4 across product pages: Strong. You're competing on the right axis.

What it measures: Whether your product attributes are stated literally in your content - the way buyers actually search for them.

How to do it:

1. List your 3 strongest product attributes (e.g. "sulfate-free", "color-treated", "vegan")
2. For each, search your top 5 product pages for the exact term
3. Count occurrences across product title, description, FAQ blocks, metafields

Benchmark per attribute

• 0-2 occurrences: Implicit. The model has to infer the attribute - it usually won't.
• 3-5 occurrences: Mentioned. AI engines can pick up the attribute but it's not dominant.
• 6+ across structured content: Explicit. The model has high confidence this is what you sell.

What it measures: How consistently you're cited for the same query across separate ChatGPT sessions. AI models are non-deterministic; the same query can return different brands on different runs.

How to do it:

1. Pick one query from Section 1 where you ARE cited
2. Run the same query in 5 separate ChatGPT sessions (new chat each time)
3. Count how many of the 5 still cite you

Benchmark

• 1-2 of 5: Unstable. You're an occasional mention, not a default answer.
• 3-4 of 5: Moderate. Usually cited, sometimes missed.
• 5 of 5: Stable. You're the default answer for this query.

Citation Rate: ____ % (of 20 queries)

Missed Match Rate: ____ % (of fits)

Structured Content Coverage: ____ formats (out of 4)

Attribute Explicitness: ____ avg occurrences per attribute

Position Stability: ____ of 5

Top 3 Missed Matches:

1. ____________________

2. ____________________

3. ____________________

If Citation Rate is below 15%

Your foundation is the issue. Deploy structured content (FAQ blocks, comparison tables, schema markup) for your top 3 Missed Matches. First citations typically land within 4-8 weeks of deployment.

If Missed Match Rate is above 50%

Big opportunity zone. Your products already fit these intents - you just don't have the structured content for the model to lift. Deploy FAQ + claim-evidence per Missed Match. Most brands move 15-20 points in 90 days.

If Structured Content Coverage is None or Minimal

This is your highest-leverage fix. Deploy FAQ blocks + schema markup across your catalog. RevWay's Storefronts engine produces these systematically from your product data - the manual alternative is 200-400 hours of content authoring.

If Attribute Explicitness averages below 3

Your content uses marketing language ("gentle," "premium") instead of literal attributes ("sulfate-free," "color-treated"). Rewrite product titles, descriptions, FAQ blocks, and metafields to use the exact attribute terms buyers search for.

If Position Stability is below 3 of 5

You're cited inconsistently. Deploy variant content for this query (multiple FAQ block versions, multiple comparison framings), A/B test which version earns citations more reliably, and refresh as patterns shift.

This audit covers 20 queries. RevWay's Brand Report runs the same analysis against the full buyer-query population for your category - typically thousands of queries.

A manual audit is a point-in-time snapshot. The Brand Report refreshes weekly, tracks deltas over time, and surfaces Missed Matches your products fit but you didn't think to test.

The self-audit is a useful starting point. The Brand Report is the system that runs continuously underneath.