How do you generate prompts for tracking LLM performance?
You generate prompts for tracking LLM performance by coming up with queries that mirror how real customers might ask questions about your brand, products, or industry.
These prompts help you test whether large language models (LLMs) like ChatGPT, Perplexity, or Gemini mention your brand—and how they describe it.
Here’s how to generate these prompts effectively:
- Start with customer intent. Think about the questions buyers ask at different stages of their journey, such as “what is a CRM?” or “best CRM for small businesses.”
- Cover brand and competitor queries. Include prompts that mention your brand directly (“Is [Your Brand] good for enterprise teams?”) and compare it against competitors (“[Your Brand] vs. [Competitor] for mid-market companies”).
- Include generic category searches. Test prompts without brand names, like “top CRM software,” to see if your brand appears in comparisons.
- Vary phrasing and format. Use both conversational and direct styles (“Which CRM should I choose for startups?” vs. “best CRM software for startups”) since AI users ask in natural language.
- Track region or persona-specific queries. If you market globally or to different audience segments, create prompts that reflect those contexts (“best fintech app for students in the UK”).
You can use toolks like Semrush Enterprise AIO and AI Visibility Toolkit to track prompts at scale and measure how LLMs represent your brand across AI platforms.
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