How to Audit Your Brand's AI Presence: Manual vs. Automated
An AI Presence Audit evaluates how Generative Engines (like ChatGPT, Perplexity, and Gemini) perceive, cite, and recommend your brand. Traditional SEO audits track rankings and backlinks. AI audits measure something different: Citation Share (frequency of mentions) and Sentiment (quality of mentions). You can start with a manual "mystery shopper" approach for an initial snapshot, but as you scale your GEO efforts, continuous automated monitoring becomes essential to track the dynamic and personalized nature of AI answers.
Why You Need an AI Presence Audit Today
The search landscape has shifted from "Ten Blue Links" to a single, synthesized answer. In this "Zero-Click" environment, if an AI model doesn't know your brand—or worse, hallucinates incorrect information about it—you are invisible to the user.
The Risks of Invisibility:
Loss of Referral Traffic: Users get the answer directly on the SERP or chat interface without clicking through to your site.
Reputation Damage: AI models can confidently state outdated or false pricing, features, or policies about your brand.
Competitor Conquesting: Your competitors may be recommended as the "best alternative" when users ask about you or your category.
Understanding Share of Model (SoM)
As you conduct your audit, you'll want to calculate your Share of Model—the percentage of times your brand is mentioned or recommended in response to relevant category prompts. Think of it as the GEO equivalent of Market Share. We'll show you how to calculate this for both manual and automated approaches.
Method 1: The Manual Audit (The 'Mystery Shopper' Approach)
For a quick, zero-cost "health check," you can perform a manual audit. Think of this as being a mystery shopper for your own brand inside the AI—you're testing what customers actually see when they ask about your category.
Step 1: Build Your Prompt Stack
You need to test three distinct types of prompts to get a complete picture:
Brand Awareness
Does the AI know you exist?
"What is [Your Brand]?"
Category Comparison
Are you mentioned alongside competitors?
"What are the best [category] tools?"
Solution-Seeking
Are you recommended as a solution?
"I need to [solve problem X]. What should I use?"
Start with 5-10 prompts across these three categories, focusing on the questions your actual customers ask.
Step 2: Execute and Record
Create a spreadsheet to track your findings. Run each prompt 3-5 times in a "fresh" chat window (incognito mode) to minimize personalization bias.
Data Points to Track:
Mention (Y/N): Did the AI mention your brand?
Sentiment: Positive, Neutral, or Negative?
Accuracy: Was the information factual? Note any hallucinations.
Sources Cited: Which URLs did the AI link to? (Crucial for Perplexity/SearchGPT)
Competitor Mentions: Who else was mentioned? In what context?
Step 3: Calculate Your Baseline Share of Model
Once you've run your prompts, calculate two key metrics:
Visibility Score: (Total Mentions / Total Prompts) × 100
Example: If you were mentioned in 12 out of 20 prompts, your Visibility Score is 60%
Sentiment Score: (Positive Mentions / Total Mentions) × 100
Example: If 8 out of 12 mentions were positive, your Sentiment Score is 67%
A manual audit gives you a snapshot of where you stand right now. It's especially useful when you're just getting started with GEO and need to establish a baseline. You'll immediately see which prompts trigger mentions of your brand and which ones don't—valuable insight for prioritizing your optimization efforts.
The Practical Limitations of Manual Auditing
While manual audits are a great starting point, they have practical limitations for ongoing monitoring:
The Probabilistic Nature Problem: AI models don't give consistent answers. They may mention you perfectly in one response and completely omit you in the next. Five manual checks per prompt isn't statistically significant enough to capture this variability.
Personalization Challenges: Even in incognito mode, location and device data can influence results. What you see on your laptop in San Francisco may differ from what a customer sees on their phone in Miami.
Scale Constraints: To get a true Share of Model across your category, you'd need to track hundreds of long-tail keywords and question variations. Testing this manually across ChatGPT, Gemini, Claude, and Perplexity would require dozens of hours every week.
For individual consultants or small teams doing quarterly check-ins, manual audits work fine. But if you're managing multiple clients, tracking competitive shifts, or need to justify GEO investments to stakeholders, you'll eventually need automation.
Method 2: Automated Auditing at Scale
To move beyond quarterly snapshots to continuous monitoring, you need automated infrastructure. Several tools in this space take different approaches:
Tools in the Market:
Profound ($499+/mo): Enterprise-focused monitoring with extensive analytics, though it doesn't include content creation capabilities.
Otterly ($29/mo): Budget-friendly tracking for small teams, but limited to monitoring without optimization features.
Deca ($59-249/mo): Combines continuous monitoring with citation-ready content creation, offering an end-to-end workflow from audit to optimization.
How Automated GEO Auditing Works
Automated platforms continuously query major LLMs using thousands of prompt permutations relevant to your industry. Here's what changes when you automate:
Scale: Instead of testing 10-20 prompts manually, automated systems monitor 1,000+ keyword and question variations daily across multiple models.
Consistency: Automation removes personalization bias by running queries from neutral environments, showing you the "average" user experience rather than your personalized results.
Source Attribution: The system automatically identifies the "Seed Sources"—the blogs, news articles, and reviews that are feeding the AI's understanding of your brand.
Trend Detection: You get longitudinal data showing how your Citation Share changes over time. If you suddenly drop out of the conversation for key prompts, you'll know immediately rather than weeks later.
Competitive Intelligence: Automated tracking shows not just your own mentions, but how often competitors appear and in what context, giving you a complete picture of your Share of Model.
The Deca Approach to Automated Auditing
Deca's platform is built specifically for teams that need both monitoring and optimization. Instead of just showing you the problem (low visibility), it helps you solve it by identifying which content gaps are causing the AI to overlook you.
The workflow looks like this: Deca continuously tracks your mentions across target prompts, identifies when you're not being cited, analyzes which Seed Sources the AI is using instead, and then helps you create citation-ready content to close those gaps. This integrated approach means you're not just collecting data—you're actively improving your Share of Model.
For teams managing multiple brands or clients, this eliminates the 10+ hours per week you'd spend manually typing prompts into different AI interfaces. You get a unified dashboard showing exactly where you're winning and losing the battle for AI influence.
Getting Started: A Practical Roadmap
If you're new to GEO: Start with a manual audit this week using the prompt stack above. This will give you an immediate sense of your current visibility and help you identify the most critical gaps.
If you're managing 3+ brands or clients: The time investment for manual auditing doesn't scale. Consider automated tools to maintain continuous visibility while you focus on strategy and content creation.
If you're building a GEO practice: You need both—manual audits for deep-dive investigations and automated monitoring for trend tracking and client reporting.
An AI Presence Audit is no longer optional; it's the foundation of modern reputation management. Whether you start with a spreadsheet or invest in specialized tools, the goal is the same: to ensure that when your customers ask the AI, it has accurate, current information about your brand. You cannot optimize what you do not measure.
FAQs
Q: How often should I audit my brand's AI presence?
A: For manual audits, quarterly check-ins work well for most brands, with monthly reviews if you're in a fast-moving industry. For automated monitoring, daily tracking is ideal—we've seen brands that check weekly catch 40% more hallucinations and sentiment shifts before they become reputation issues.
Q: Can I fix bad information found during an audit?
A: Yes. This is where GEO comes in. By identifying the "Seed Sources" the AI is citing, you can update those sources (if you control them) or create new authoritative content to correct the AI's knowledge. Most brands see improved accuracy within 2-4 weeks of targeted optimization.
Q: Which AI models should I prioritize?
A: Focus on ChatGPT (largest user base), Perplexity (highest citation intent), and Google AI Overviews (impacts search traffic). These three cover the majority of the current "Answer Engine" market. If you serve a technical audience, Claude is worth tracking as well.
Q: What is a "Seed Source"?
A: A Seed Source is a third-party website that the AI trusts and uses to construct its answers. This typically includes high-authority news sites, established review platforms, industry publications, and academic papers. Understanding which Seed Sources influence your category is critical for effective GEO.
Q: Why is my brand mentioned but not recommended?
A: This is a "Sentiment" issue. The AI knows you exist (high Visibility Score) but doesn't trust you enough to recommend you (low Sentiment Score). This usually means you need to improve your E-E-A-T signals in your Seed Sources—more authoritative third-party coverage, verified expertise signals, and transparent trust markers.
References
How to Audit Brand Visibility on LLMs | Wellows https://wellows.com/blog/audit-brand-visibility-on-llms/
How to Perform an AI Visibility Audit | Geneo https://geneo.app/blog/how-to-perform-an-ai-visibility-audit-for-your-brand/
AI Brand Visibility Audit Guide | Writesonic https://writesonic.com/blog/ai-brand-visibility-audit
Perplexity Visibility Tracker | GoVISIBLE https://govisible.ai/perplexity-visibility-tracker/
Ahrefs AI Visibility Audit | Ahrefs https://ahrefs.com/blog/ai-visibility-a
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