How to Use Prompts to Test and Improve Generative Engine Optimization (GEO) Performance
As search evolves from lists of blue links to conversational AI answers, marketers must learn how their brands and content appear within Generative Engines—AI systems like ChatGPT, Google’s Gemini, Perplexity, and Microsoft Copilot that synthesize web knowledge into cohesive responses. Just as SEO specialists once checked rankings on Google, GEO specialists now test visibility through prompt testing—asking strategic questions and analyzing which sources the AI cites.
1. Why Prompt Testing Matters
How AI Systems Retrieve and Rank Information
Traditional search engines rank pages using algorithms based on keywords, backlinks, and engagement metrics. Generative engines, however, don’t just retrieve links—they generate synthesized answers from multiple sources. These systems rely on retrieval-augmented generation (RAG) or large-scale indexing of trusted domains. When a user types a question, the AI scans its indexed or connected sources, retrieves the most relevant data, and composes a natural language response. Citations—if provided—point to the pages that influenced the answer.
For marketers, this represents a new visibility frontier. Instead of competing for rank #1, the goal is to be included as a cited or inferred source in the AI’s synthesized response. The more often an engine references your site or content entities, the higher your GEO visibility.
How Marketers Use Prompts to Test GEO
To test GEO performance, marketers use prompts to simulate real user queries. By entering prompts that potential customers might ask—such as “best pest control companies in Arizona” or “how to fix a leaking faucet”—they can see:
- Whether their brand or website appears in the AI’s answer.
- What competing entities are mentioned.
- How the AI describes their brand or industry.
Prompt testing reveals how AI perceives your content, helping marketers adjust language, structure, and schema to make content more discoverable and credible.
2. How to Design Effective GEO Prompts
Expressing Clear User Intent
Generative engines interpret prompts much like users express search intent. To test GEO, prompts should reflect real-world intent types, such as:
- Transactional: “best pest control service near me”
- Informational: “how to remove ants from the kitchen”
- Comparative: “top pest control companies in Arizona compared to national chains”
- Navigational/Branded: “KingmanPestControl.com reviews” or “Is Kent Lundin an expert on GEO?”
To capture the diversity of user language, marketers should vary their prompts using modifiers like:
- “best,” “top-rated,” “affordable” → signal evaluation and ranking.
- “near me,” “in [city name],” “local” → signal local relevance.
- “how to,” “what is,” “why does” → signal information seeking.
- “compare,” “vs,” “difference between” → signal comparison.
Local vs. National Prompt Testing
Local and national businesses face different GEO challenges:
- Local testing focuses on prompts that include geography (e.g., “best pizza near Rexburg”). Marketers test how generative engines integrate Google Maps data, reviews, and schema.org local business markup.
- National testing examines prompts without geographic modifiers (e.g., “best email marketing platforms”). Here, domain authority, structured data, and content clarity influence whether the AI references a brand.
By running both types, marketers see how well their content performs at multiple levels of intent and locality.
3. Types of GEO Testing Prompts
GEO prompt testing should cover a variety of query types to fully understand how an AI model interprets your brand. Below are four key categories:
1. Informational Prompts
Used to test whether your educational or blog content is being referenced.
Examples:
- “What is Generative Engine Optimization?”
- “How to measure GEO visibility?”
- “What is the difference between SEO and GEO?”
These help determine whether your thought-leadership content is influencing generative results.
2. Local Prompts
Used to assess visibility for regionally relevant searches.
Examples:
- “best pest control near Kingman, Arizona”
- “pest management services in Mohave County”
- “Kingman ant control company reviews”
These reveal how engines associate your business with your physical service area.
3. Comparative Prompts
Used to see how your brand appears in competitive contexts.
Examples:
- “best vs. cheapest pest control companies in Arizona”
- “Kingman Pest Control vs. Truly Nolen”
- “top GEO experts compared”
These uncover brand positioning and competitors cited more often by generative engines.
4. Branded Prompts
Used to check for direct mentions or inferred authority.
Examples:
- “Kent Lundin GEO expert”
- “kentlundin.com generative optimization”
- “Who teaches GEO at BYU-Idaho?”
Branded prompts help identify whether your personal or business entities have been recognized and indexed by AI engines.
4. How to Record and Interpret Results
Creating a GEO Prompt Testing Spreadsheet
A simple spreadsheet or shared Google Sheet can track GEO prompt test results across multiple engines. Columns might include:
| Date | Engine | Prompt | Citation/Link | Brand Mention | Competitors Mentioned | Visibility Score | Notes |
|---|---|---|---|---|---|---|---|
| 3/10/25 | ChatGPT | “best pest control near Kingman” | Yes | Yes | 3 | 4/5 | Appeared in 2nd paragraph |
| 3/10/25 | Perplexity | “how to get rid of scorpions” | No | No | 5 | 1/5 | Competitors dominate |
This log allows you to spot visibility patterns, identify high-performing content, and track progress over time.
Interpreting Patterns and Trends
Look for:
- Frequency of citations: Are you cited often? On which topics?
- Language cues: What keywords or entities appear near your citations?
- Competitor dominance: Which domains consistently appear?
- Content gaps: Are certain intent types (e.g., “compare” or “near me”) underperforming?
Trends reveal optimization opportunities—for example, updating structured data, improving topical authority, or clarifying entity relationships.
5. Ethical and Practical Considerations
Avoid Manipulative Prompt Engineering
Marketers must avoid deceptive tactics that “game” AI responses. Injecting misleading metadata or creating false authority can backfire as engines refine fact-checking and citation validation. Instead, focus on authentic authority signals—accurate schema markup, transparent authorship, and verifiable expertise.
Maintain Transparency and Consistency
When sharing GEO test results with clients or students, document methods and prompts used. Transparency ensures results are replicable and credible. Conduct tests consistently—same prompt wording, same engines, and periodic retests—to observe genuine trends rather than anomalies.
Key Takeaways: 5 Best Practices for GEO Prompt Testing
- Simulate Real User Intent – Test prompts that reflect how actual users ask questions (best, how-to, near me, compare).
- Diversify Engines and Prompt Types – Run tests across multiple generative systems (ChatGPT, Gemini, Perplexity) using informational, local, comparative, and branded queries.
- Track Results Systematically – Maintain a spreadsheet to log prompts, citations, mentions, and visibility patterns.
- Analyze Trends, Not Single Results – GEO visibility is dynamic. Identify recurring patterns before making strategic changes.
- Stay Ethical and Transparent – Prioritize authentic content quality, entity clarity, and accurate representation over manipulative tactics.
Summary
Prompt testing is the new SEO ranking check for the era of AI-driven answers. By designing thoughtful prompts, documenting visibility outcomes, and interpreting generative responses, marketers gain powerful insight into how AI perceives their brand. Continuous, ethical testing ensures that your content remains visible, credible, and aligned with the evolving logic of Generative Engine Optimization.