How do you track which prompts mention your brand over time? Built a system that finally works

This is exactly the kind of systematic approach more marketers need. I’ve been doing prompt tracking for clients for about a year now.

The tagging system is crucial. Here’s how we organize:

• By intent: informational, comparison, transactional
• By product line: each major product gets its own tag
• By competitor: prompts where specific competitors appear
• By campaign: tied to marketing initiatives

This way you can filter your dashboard to answer specific questions like “how are we performing in comparison prompts for Product X?”

Tool recommendation: Am I Cited has the best tagging system I’ve found for this. You can create custom color-coded tags and filter everything by them. Makes the analysis so much cleaner.

Also +1 on multi-platform tracking. We’ve seen cases where a brand dominates Perplexity but is invisible in ChatGPT. If you’re only tracking one platform, you’re missing the picture.

Great post. We track about 400 prompts across 3 brands and here’s what we’ve learned about scale:

The 40% rule: About 40% of your prompts will account for 90% of actionable insights. Focus your analysis time there.

Platform differences are real:

• ChatGPT tends to be more conservative, mentions established brands
• Perplexity updates faster, catches recent content
• Google AI Overview pulls from search results, so your SEO efforts translate better

Scheduling tip: We do daily checks on our top 50 “money prompts” (high commercial intent) and weekly checks on everything else. This balances thoroughness with cost.

The real-time processing dashboard you mentioned is huge. Nothing worse than wondering if your prompts are actually being checked. Being able to see the queue and status saves so much mental overhead.

Been building in this space and I can add some context on prompt discovery.

The problem most people have: You don’t know what you don’t know. You might be tracking 100 prompts but missing the 50 prompts that actually matter.

Solutions that work:

1. People Also Ask mining - Google shows related questions. These are prompts people actually search.
2. Related searches analysis - The suggestions at the bottom of Google results are goldmines.
3. Competitor reverse engineering - Find what prompts mention competitors and track those.

Am I Cited does this automatically with their prompt suggestions feature. It pulls from Google Search data and suggests new prompts you should be tracking. Saved us probably 10 hours a week of manual research.

The key insight: prompt tracking isn’t just about monitoring what you know. It’s about discovering what you should be monitoring.

We manage prompt tracking for 15 clients. Here’s our workflow:

Onboarding (Week 1):

• Identify 50-100 seed prompts from client knowledge
• Run discovery to find additional prompts
• Set up tags by product, intent, and competitor

Ongoing management:

• Weekly review of new responses
• Monthly deep analysis by tag category
• Quarterly strategy adjustment based on trends

Common mistakes we see:

• Tracking too many generic prompts (focus on specific, commercial intent)
• Not checking response history (the trend matters more than any single response)
• Ignoring Google AI Overview (it affects search traffic directly)

Export tip: Most clients want reports for leadership. The ability to export responses as markdown or bulk data is essential. We pull this weekly for client dashboards.

Love this thread. I run marketing for an ecommerce brand and prompt tracking changed how we think about content.

Our aha moment: We tracked “best [product category] for [use case]” prompts and realized we were mentioned in 0% of them initially. Competitors dominated.

What we fixed:

• Created dedicated comparison pages for each use case
• Added structured FAQ content
• Got mentioned in relevant Reddit threads

The result: 6 months later, we appear in 40% of those comparison prompts.

The key was having the data to see the gap in the first place. Without systematic prompt tracking, we would have just kept doing what wasn’t working.

Pro tip: export your prompt responses periodically. When you make content changes, you can compare before/after to prove ROI.

From a technical perspective, here’s why multi-platform tracking matters:

ChatGPT: Uses a combination of training data and real-time web browsing. Responses can vary significantly between sessions. Regular checking catches these variations.

Perplexity: Real-time web access means your fresh content can show up faster. But it also means competitors can overtake you quickly.

Google AI Overview: Tied to search rankings more directly. Your SEO efforts translate here better than other platforms.

The implication: You need scheduled checks, not one-time snapshots. A prompt that mentions you today might not mention you tomorrow, and vice versa.

The tools that let you configure check frequency per prompt are valuable. You probably want daily checks on high-priority prompts but weekly on broader monitoring.

Let me add the business case perspective since OP mentioned their CEO is asking about this.

Why prompt tracking matters for business:

1. 40%+ of users ask AI before purchasing - If you’re not visible in AI responses, you’re not in the consideration set.

2. Competitors are already doing this - The brands that figure out AI visibility now will have compounding advantages.

3. It’s measurable - Unlike many marketing activities, you can track exactly how often you’re mentioned and how it changes.

Metrics to show leadership:

• Citation frequency (how often mentioned)
• Citation share (your mentions vs competitor mentions)
• Prompt coverage (what % of relevant prompts mention you)
• Trend over time (improving or declining)

The CEO who asks about “AI SEO” is ahead of the curve. This is the next frontier, and the brands that move now will benefit most.

This thread exceeded expectations. Thank you all for the detailed responses.

Key takeaways I’m implementing:

1. Tagging system overhaul - Going to restructure our prompts by intent, product, and competitor like Julia suggested

2. Platform-specific strategy - We were treating all platforms the same. Now building separate approaches for ChatGPT vs Perplexity vs Google AI Overview

3. Prompt discovery - Setting up ongoing prompt suggestions to catch gaps we’re missing

4. Historical analysis - Will start weekly exports to build our own trend database

5. Leadership reporting - Creating a monthly AI visibility dashboard with the metrics Jason outlined

The insight about the 40% of prompts driving 90% of insights is gold. Going to do an audit to identify our highest-value prompts.

For anyone starting out: the manual approach is fine for learning but doesn’t scale. Automated tracking with scheduled checks is the way to go long term.

Will share an update in a few months with results. Thanks everyone!