Wondering how to track your brand in AI search with conversational queries? As tools like ChatGPT, Claude, and Perplexity shape how people discover brands, it’s no longer enough to optimize for Google. These AI models generate answers — and if your brand isn’t mentioned, you’re invisible.

In this guide, you’ll learn exactly how to track your brand in AI search with conversational queries, using a simple 5-step workflow. Whether you’re a local shop in Zurich or a global e-commerce business, this method helps you spot missed opportunities and improve your visibility in AI-generated answers.

We’ll show you how to generate realistic prompts, monitor results using the LLM Visibility Monitor, and create content that closes visibility gaps — all while automating the process with scheduled daily, weekly, or monthly checks.

Step 1: Generate realistic queries

Start by generating natural-language queries that reflect how a real person might look for your product or service in AI search. Unlike traditional keyword research, these prompts should simulate how people talk to AI — often using full sentences, context, constraints, and local details.

Here’s a generic prompt template you can use in ChatGPT, Claude, or your own workflow:

And here’s a specific example tailored to a gourmet food shop in Zurich:

Step 2: Run visibility checks (automatically)

Take your generated prompts and run them through the LLM Visibility Monitor. This tool checks how your brand (and optionally your competitors) appear in AI-generated answers — across GPT-4, Claude, Perplexity, and over 300 other models.

Even better: you don’t have to do this manually. The Monitor lets you schedule queries to run daily, weekly, or monthly, so you can track changes automatically over time.

For each query, you’ll get structured results:

• Whether your brand is mentioned
• In what context and position
• Which AI models mentioned you
• If competitor brands were prioritized

This creates a rich visibility snapshot you can return to any time.

Step 3: Identify gaps

Review the results to spot visibility gaps:

• Are competitors mentioned, but not you?
• Are you visible in some models but missing from others?
• Do certain topics or product lines consistently omit your brand?

This step is not just about presence — it’s about context and relevance. You want to appear where customers are asking questions that relate to your offer.

Step 4: Publish content to close the gaps

Once you’ve identified where and how your brand is missing, respond with targeted content. That might include:

• Blog posts addressing the exact questions
• Landing pages optimized for conversational search
• Product pages that clearly mention local delivery, pricing, or gifting options
• Structured data (schema.org) to improve AI parsing

Use the phrasing of the original queries to mirror user intent — and consider incorporating those prompts into your content strategy or metadata.

Step 5: Monitor again (automatically)

After publishing, don’t stop. Go back to the LLM Visibility Monitor and re-run the same prompts — or let the scheduled runs continue.

You’ll be able to:

• Track whether your visibility improved
• Measure the impact of content changes
• Refine your strategy over time

This creates a continuous loop of discovery, measurement, and action — the key to staying visible in AI-driven search results.

Start your loop

If you’re running a business and want to stay visible in the age of AI-driven search, this workflow gives you a practical, repeatable method. You can start right now by plugging your own business details into the sample prompt above — or use our prompt template to test visibility in any region, category, or niche.