
Understanding your current AI recommendation visibility is the essential first step in any optimization effort. This guide provides a structured approach to auditing your brand's presence across major AI assistants in approximately 30 minutes.
By the end of this audit, you will know whether AI assistants recommend your brand, how they describe you, which competitors appear instead, and where your optimization priorities should focus.
Before starting, prepare the following:
Create a list of questions that potential customers realistically ask when researching your category. These should be the types of questions someone would ask an AI assistant when seeking recommendations.
General category queries: "What is the best [your category]?" or "Can you recommend a good [your product type]?"
Problem-based queries: "What should I use to solve [problem your product addresses]?" or "How do I [task your product helps with]?"
Comparison queries: "What are the alternatives to [competitor]?" or "How do I choose between [option A] and [option B]?"
Specific use case queries: "What is the best [category] for [specific use case]?" or "Which [product type] works best for [specific situation]?"
Budget-based queries: "What is the best affordable [category]?" or "What [product type] offers the best value?"
For a project management software company, queries might include:
Write down 5-10 queries relevant to your specific business.
Now test each query across the major AI assistants. Work through each platform systematically, recording results as you go.
Open ChatGPT and test each of your prepared queries. For each query, record:
Use a fresh conversation for each query to avoid context from previous queries influencing responses.
Repeat the same process with Claude. Note that Claude may provide different recommendations than ChatGPT, and the style of response will differ.
Record the same information:
Perplexity operates differently because it searches current web content. Pay attention to:
Complete the same testing with Gemini, recording:
Create a simple matrix to capture results:
| Query | ChatGPT | Claude | Perplexity | Gemini |
|---|---|---|---|---|
| Query 1 | Position/Description | Position/Description | Position/Description | Position/Description |
| Query 2 | ... | ... | ... | ... |
For each cell, note whether you appeared (Y/N), your position if applicable (1st, 2nd, 3rd, or "mentioned"), and a brief note about how you were described.
With your results recorded, analyze patterns to understand your current position.
Count the total number of query-platform combinations you tested. If you tested 7 queries across 4 platforms, that is 28 total combinations.
Count how many times your brand appeared in any capacity. Divide appearances by total combinations to get your visibility percentage.
Example: 8 appearances out of 28 combinations = 29% visibility
Look for platform-specific patterns:
Platform-specific gaps indicate where you might focus optimization efforts.
Look for patterns across query types:
Query-specific gaps reveal positioning and content opportunities.
Note which competitors appear frequently:
Understanding competitor presence helps you identify what they might be doing differently.
Based on your analysis, identify your highest-priority optimization opportunities.
Your priority is establishing basic presence. Focus on:
Your priority is strengthening and expanding presence. Focus on:
Your priority is optimization and defense. Focus on:
Write down your top 3 optimization priorities based on this audit. Be specific about what you will address and why.
Example priorities:
This initial audit provides a baseline. Schedule regular follow-up audits to track progress and identify changes.
Monthly audits provide good balance between staying informed and avoiding excessive time investment. Use the same queries each month to track changes consistently.
Add new queries periodically as you identify additional relevant questions or as your business evolves.
Maintain a running record of your visibility scores and key observations over time. This historical data helps you understand whether optimization efforts are working and identify trends.
Note significant changes in competitor presence as well. New competitors appearing or existing competitors improving their visibility may require strategic response.
This quick audit provides directional understanding but has limitations.
Testing a limited number of queries provides useful signals but may not capture your full visibility picture. Important queries you did not test may show different results.
AI responses can vary based on when you ask. Testing at different times or on different days might produce somewhat different results.
Some AI assistants may personalize responses based on user history or context. Your results may differ from what other users experience.
This audit shows whether you are recommended but does not directly measure whether AI recommendations drive business results. Attribution requires additional tracking.
Use your audit findings to inform a structured optimization plan. Address your highest-priority gaps first, then expand to secondary opportunities.
If your audit reveals significant visibility gaps, consider whether internal resources can address the optimization work or whether external expertise would accelerate progress.
Repeat this audit monthly to track improvement and identify new opportunities. Over time, you will build a clear picture of your AI recommendation presence and the factors that influence it.
The 30 minutes invested in this audit provides foundational understanding that informs all subsequent optimization decisions. Without knowing your current position, optimization efforts cannot be properly prioritized or measured.