25 Prompts to Test Your Brand’s AI Visibility (Across 8 Models)

In the era of Generative AI, search is no longer a list of links—it is a conversation. AI assistants like ChatGPT, Gemini, and Claude synthesize information from across the web to deliver a single, curated answer,.

If your brand is not cited in that answer, you are effectively filtered out of consideration before a buyer even reaches your website. The only way to know if you are winning or losing in this new landscape is to test your visibility directly.

Here is a 25-prompt framework to audit your brand across the major AI models, identify hallucinations, and optimize your presence for the age of answer engines.

Why Prompt-Based Testing Works

Traditional SEO metrics like "keyword volume" and "backlinks" do not tell you how an AI model perceives your brand. Prompt-based testing is the only way to see the "hidden layer" of search.

• Fast feedback loops: Unlike SEO, which can take months to show results, prompt testing provides immediate insight into how models currently rank and perceive you.

• Identifies hallucinations: AI models penalize inconsistency. If your product data is contradictory across the web, models may generate inaccurate descriptions—hallucinations—that can cost you revenue. Testing reveals these errors instantly.

• Reveals gaps in structured AI models rely on Answer Engine Optimization (AEO) tactics, such as Schema markup, to extract facts. If a model fails to return your pricing or specific features, it often signals a gap in your structured data hygiene.

The 8 AI Models You Should Test

To get a complete picture, you cannot rely on a single platform. Different models have different biases; for instance, Gemini favors Google-aligned entity signals, while Perplexity favors external citations,.

For a comprehensive audit, test your prompts across these 8 models (all monitored by the Akii AI Visibility Monitor):

1. ChatGPT (OpenAI): The market leader with broad coverage but inconsistent citations.

2. Perplexity: A "transparency-first" engine that provides clickable citations, essential for tracking GEO (Generative Engine Optimization) efforts.

3. Gemini (Google): Heavily biased toward the Google Knowledge Graph and schema markup.

4. Claude (Anthropic): Conservative and stability-focused; hard to penetrate but sticky once you are included.

5. Meta AI (Llama): Increasingly integrated into social platforms.

6. DeepSeek: An advanced reasoning model crucial for technical evaluations.

7. xAI Grok: Real-time access to X (formerly Twitter) data streams.

8. Search+AI Hybrids: Specifically Google AI Overviews, which appear at the top of search results and are highly responsive to FAQ schema.

The 25 Visibility Testing Prompts

We have organized these prompts into five critical categories based on the Akii AI Visibility Index methodology.

Brand Understanding Prompts

Goal: Determine if the AI has a "verified node" for your brand in its Knowledge Graph.

1. "What is [Brand Name] and what specific problem does it solve?" (Tests functional clarity).

2. "Who is the target audience for [Brand Name]?" (Tests market alignment).

3. "Who owns or founded [Brand Name]?" (Tests entity relationships and Knowledge Graph strength).

4. "Is [Brand Name] considered an enterprise or SMB solution?" (Tests positioning accuracy).

5. "Summarize the core value proposition of [Brand Name] in one sentence." (Tests if your "boilerplate" description is consistent).

Product/Feature Prompts

Goal: Check for SKU-level clarity and structured data extraction.

6. "What are the top 3 features of [Brand Name]?"

7. "Does [Brand Name] offer [Specific Feature, e.g., API access]?" (Tests feature extraction).

8. "How much does [Brand Name] cost?" (Tests pricing page schema and crawlability).

9. "Does [Brand Name] integrate with [Major Tool, e.g., Salesforce]?"

10. "What specific use cases is [Brand Name] best suited for?" (Tests product-problem pairing).

Comparison Prompts

Goal: See if you are positioned as a "Leader," "Challenger," or "Alternative".

11. "Compare [Brand Name] vs. [Competitor Name]."

12. "What are the main differences between [Brand Name] and [Competitor Name]?"

13. "Why would a user choose [Brand Name] over [Competitor Name]?" (Tests unique selling proposition clarity).

14. "List 3 alternatives to [Competitor Name]." (Crucial: Do you appear in your competitor’s "alternative" lists?).

15. "Is [Brand Name] cheaper or more expensive than [Competitor Name]?"

Recommendation Prompts

Goal: These are high-intent "Evaluative" queries that drive purchase decisions.

16. "What are the best [Category] tools for [Industry]?" (e.g., "Best CRM for small businesses").

17. "Recommend a [Category] tool that has [Specific Feature]."

18. "Top 5 [Category] brands for 2026."

19. "I need a tool for [Specific Task]. What should I use?"

20. "Which [Category] software has the best user reviews?" (Tests your Review/AggregateRating schema).

Fact-Checking Prompts

Goal: Identify hallucinations and trust signals.

21. "Is [Brand Name] a legitimate company?" (Tests sentiment and trust signals).

22. "What are the common complaints about [Brand Name]?" (Tests negative sentiment ingestion).

23. "Where is [Brand Name] headquartered?"

24. "Does [Brand Name] offer a free trial?"

25. "List the pros and cons of using [Brand Name]."

How to Score the Outputs

When analyzing the results from the 8 models, use this 0–3 scoring scale to quantify your performance,.

• 0 = Hallucination / Invisible: The model says "I don't know this brand," claims you don't exist, or invents incorrect facts (e.g., calling an electric bike a standard bike). Action: Critical Technical Fixes needed.

• 1 = Incomplete: The model mentions the brand but misses key features, pricing, or value propositions. It "knows" you but doesn't "understand" you.

• 2 = Correct but Shallow: The facts are right, but the positioning is generic. You are listed as a "tool" but not a "leader." Citations are missing or point only to your homepage.

• 3 = Correct + Detailed: The model gives a detailed recommendation, cites specific features, aligns perfectly with your value prop, and links to authoritative third-party sources (e.g., G2, TechCrunch).

How to Fix Identified Issues

If your audit reveals scores of 0 or 1, you must engineer your visibility using a mix of AEO (Answer Engine Optimization) and GEO (Generative Engine Optimization).

1. Fix Your Schema (Technical AEO)

If models miss your pricing or features, your content is likely not machine-readable. Implement Product, Offer, and FAQ schema on your core pages. This provides concise, declarative statements that models can extract easily. Use tools like the Akii Website Optimizer to generate these packages automatically.

2. Unify Your Entity (Entity SEO)

If ChatGPT describes you differently than Gemini, you have an entity consistency problem. Create a Master Entity Profile—one unified description, one taxonomy, and one boilerplate—and replicate it across your website, LinkedIn, Crunchbase, and Wikidata,.

3. Update Content with "Quotable Canonicals"

AI models prefer concise answers. Structure your high-traffic pages with "TL;DR" summaries and question-based headings (e.g., "What is [Brand]?") to create quotable canonicals that models can lift directly,.

4. Strengthen External Profiles (GEO)

If you are accurate but rarely recommended (Score 2), you lack authority. Generative models need external corroboration to choose you. Focus on getting cited in high-authority data sources like Wikidata, Crunchbase, and G2 to build the trust signals AI relies on,.

Stop guessing how AI sees your brand.

Manual testing is a great start, but AI visibility is volatile and changes weekly.

👉 Get Your Free Agent-Readiness Scorecard. Run the Akii AI Visibility Score to benchmark your brand across Gemini, ChatGPT, Claude, and Perplexity in under 2 minutes.