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Unlike SEO (where you can just pull keyword volumes), nobody publishes exact user prompts from ChatGPT, Gemini, or Perplexity. But you can still build a smart system to know what prompts are worth tracking.
Take your highest-value keywords from Google Search Console / Ahrefs / Semrush.
Rephrase them into natural-language questions people would actually type into a chatbot, e.g.:
SEO keyword: “best travel wallet app”
Prompt: “What’s the best app to keep all my tickets and bookings?”
Think in terms of jobs-to-be-done:
Scan Reddit, Quora, forums, and Twitter/X — copy real user phrasing. These are often close to how people ask chatbots.
Create prompt buckets to cover the main angles:
The key mindset: treat prompts like keywords in SEO — but more conversational, intent-driven, and flexible. You’ll never capture 100%, but with clusters you’ll cover 80% of real user demand.
Start with your SEO keywords and reframe them as natural questions beginning with what, how, which, why, where. Then expand using customer intent, competitor comparisons, and real phrasing from communities like Reddit or Quora.
Begin with 30–50 prompts across different intent clusters. That’s enough to see patterns without being overwhelming.
Review monthly. Drop low-performing prompts and add new ones based on customer conversations, competitor moves, or community chatter.
No. Think of prompts as a new layer. SEO keywords still matter for Google, but prompts help you appear in AI-driven answers.
Focus on ChatGPT, Gemini, and Perplexity. They’re currently the most widely used for product and service recommendations.
