How to Write Prompts for AI Visibility Tracking (That Actually Matter)
TL;DR
Most GEO (Generative Engine Optimization) prompts are designed to inflate dashboards, not reflect real user behavior. To measure visibility that impacts revenue, you must source prompts from actual data, categorize them by funnel stage (TOFU/MOFU/BOFU—Top, Middle, and Bottom of the Funnel, if you aren't familiar with the jargon), and weight them based on purchase intent. A bottom-of-funnel mention is worth 20x a generic awareness mention. Stop measuring noise.
The Problem: 90% Visibility, Zero Revenue
Your GEO dashboard says you have 90% visibility. Your revenue chart says a different story.
After months of tracking AI visibility for brands, a dangerous pattern has emerged: the metrics look incredible, but the business impact is flat. The problem isn’t the AI platforms, and it isn’t your product. It’s the prompts you are tracking.
Most brands are measuring AI visibility wrong. They track prompts nobody actually asks, celebrate inflated scores, and wonder why the traffic isn't converting.
The "Manufactured Visibility" Trap
Here is an example of a prompt that guarantees high visibility—and zero value:
How should a US-based e-commerce novice in Q3 2025 use Resend's email segmentation feature for abandoned cart recovery workflows?
Of course your brand appears in that answer. The prompt is so specific and tailored that the AI has no choice but to mention you. Your dashboard shows 95% visibility. The marketing team celebrates.
But ask yourself: would any human being actually type this into ChatGPT?
This is Visibility Theater. It’s the result of stacking conditions to force a mention. If you optimize for these "manufactured prompts," you are optimizing for a dashboard, not for customers.
The Funnel Framework for GEO
In traditional SEO, we know that keywords have different intents. In GEO, prompts work the same way. A mention in a purchase-ready query is worth significantly more than a mention in a broad educational query.
The Funnel Framework for GEO
You need to categorize your tracking into three buckets:
1. TOFU (Top of Funnel) — Awareness
- The User: Is learning about the category. No purchase intent yet.
- Example Prompts: What is transactional email?, How do email APIs work?
- Value: Brand awareness.
2. MOFU (Middle of Funnel) — Consideration
- The User: Knows the category exists and is comparing options.
- Example Prompts: Mailchimp vs SendGrid vs Resend, Best email service for developers, Compare email APIs for SaaS startups.
- Value: Getting on the shortlist.
3. BOFU (Bottom of Funnel) — Decision
- The User: Is ready to buy and has specific requirements (price, stack, speed).
- Example Prompts: Best transactional email API under $50/month, Most affordable email service for early-stage startups.
- Value: Direct conversion.
The Insight: If 90% of your tracked prompts are TOFU, your "90% Visibility" score is meaningless for revenue. Often, LLMs simply provide a generic educational answer at this stage with zero brand mentions—meaning your actual commercial value is 0%.
How to Write Effective Prompts (A 4-Step Guide)
Step 1: Source from Real Behavior
Stop brainstorming in meeting rooms. Find what users actually ask.
- Look at: Customer support tickets, Reddit threads, Quora discussions, and Google Search Console queries.
- The Goal: Uncover the raw questions real humans are asking.
Step 2: Use Natural Language
LLMs respond differently to "keywordese" than they do to natural language.
- Bad: Best email API features comparison 2025
- Good: What's the easiest email API to set up for a small dev team?
- Rule of Thumb: Read it aloud. If it sounds like a marketing brief, rewrite it.
Step 3: Categorize by Funnel Stage
Tag every prompt in your tracking sheet. Is this Educational (TOFU), Comparative (MOFU), or Purchase-Ready (BOFU)?
Step 4: Weight by Business Stage
Not all visibility is created equal. Depending on your product's maturity, you should weight your "Total Visibility Score" differently.
| Your Product Stage | TOFU Weight | MOFU Weight | BOFU Weight |
|---|---|---|---|
| New Category (Users don't know it exists) | 50% | 30% | 20% |
| Established Category (Users are comparing) | 10% | 50% | 40% |
| Mature / Commoditized | 10% | 30% | 60% |
Example: If you are selling an Email API (an established category), users already know what it is. They struggle with choosing the right one. Your visibility score should be weighted heavily toward MOFU (Comparison) and BOFU (Decision).
Stop Measuring Visibility. Start Measuring Intent.
The goal isn't a high visibility score on a slide deck. The goal is appearing in the queries that lead to customers.
When you strip away the manufactured prompts and focus on the funnel, your visibility score might drop from 90% to 40%. That is a good thing. That 40% represents real demand.
Write prompts from real behavior. Categorize by funnel. Weight toward outcomes.
Track AI visibility that matters.
Beonai helps brands measure what actually drives growth, not just what looks good on dashboards.
FAQs
How many prompts should I track?
Quality over quantity. Start with 20-30 well-researched prompts per product line. It is better to track 30 questions real buyers actually ask than 300 manufactured ones that nobody uses.
Should I track branded prompts (containing my company name)?
Yes, but keep them separate. Branded prompts measure reputation (existing users). Unbranded prompts measure discoverability (new growth). Focus 80% of your effort on unbranded queries.
How often should I update my prompt list?
It depends entirely on your market's velocity. For fast-moving industries like SaaS or AI, where trends shift in weeks, a monthly review is essential. For stable, traditional B2B markets, quarterly updates are usually sufficient. Regardless of your schedule, always refresh your list immediately if you launch a new feature or a major competitor enters the space.
What if my brand shows 0% visibility?
Don't panic; use it as a roadmap. Identify which competitors are visible and check their citation sources. Those specific blogs, reviews, and documentation pages are your new targets.
Do different AI platforms (ChatGPT vs. Perplexity) need different prompts?
Use the same prompts, but expect different results. Perplexity favors recent news (live web), while ChatGPT favors authority (training data). Track across all models to see where your content strategy is weak.