How many prompts should I track per project?

Most TAMGIO projects start with 30-40 approved prompts spread across the five intents. Fewer than that and single-answer noise dominates your metrics; more than that rarely adds new signal unless you're tracking many product lines.

Should I include my exact brand name in every prompt?

No. Real buyers rarely search by brand name before they've heard of you, so most prompts should describe the problem or category instead. Reserve a smaller subset of brand-name and comparison prompts for tracking recall once you're already known.

Can TAMGIO generate prompts for me?

Yes. TAMGIO can AI-generate a candidate set across best-of, comparison, how-to, pricing, and local intents; you review and approve each prompt before it's added to a tracked project.

Why doesn't a prompt's result match what I see when I ask ChatGPT myself?

AI answers are non-deterministic — the same prompt can return a different answer on different runs. That's why TAMGIO measures each prompt N times and reports rates like Mention Rate and Share of Voice instead of a single-shot yes or no.

What happens if a prompt doesn't trigger Google AI Overviews?

That's recorded as no_surface, not as a missed brand mention. AI Overviews doesn't appear for every search, and TAMGIO keeps that distinction visible instead of folding it into a lower mention rate.

How to Write Prompts That Actually Measure AI Visibility

A good AI-visibility prompt is a question a real buyer would actually type into ChatGPT or Perplexity — not a keyword phrase stuffed with your product category. It should read like natural research: "what's the best tool for X," "how do I check Y," "is Z worth the price," because that is the language grounded AI answers are built to respond to. Prompts written like search-engine keywords produce artificially low or misleading mention rates, because the model itself is reasoning over a different kind of input than the one you actually want measured.

1. Anchor each prompt in a real buyer question

Start from the question a prospect asks before they've heard of your brand, not the phrase you wish they'd search. If you sell project-management software for agencies, the real question is "what project management tool works best for a 10-person creative agency," not "project management software." One is something a buyer types into ChatGPT while researching a decision; the other is a keyword you'd have bid on in a search-ads dashboard a decade ago. Grounded AI answers respond to intent and context, so a prompt shaped like a real question surfaces the same reasoning path — and the same competitor set — a real buyer would see.

2. Write like a person, not a keyword list

Keyword-stuffed prompts ("AI visibility tracking tool GEO software comparison 2026 best") don't just read badly — they measure something different from what you think they measure. A grounded model treats that string as an ambiguous, low-context query and may search, summarize, or hedge differently than it would for a clear sentence. Compare:

Keyword-stuffed: "AI visibility tracking tool comparison best"
Natural: "What's the best tool for tracking how often my brand gets mentioned by ChatGPT and Perplexity?"

The second is what someone actually types, and it's what TAMGIO runs against real engines. Ongoing tracking runs on three engines — OpenAI web_search, Perplexity Sonar, and Gemini grounded search. Google AI Overviews (via SerpAPI) is added in Audit Mode, for four measured surfaces in total. You're measuring real answers to real questions, not answers to a string nobody would ever type.

3. Cover the five core intents

One well-written prompt tells you about a single moment in the buyer journey. A set spread across intents tells you where you win and where you're invisible:

Best-of — "What are the best [category] tools for [audience] in 2026?"
Comparison — "TAMGIO vs [competitor] — which gives better evidence for AI mentions?"
How-to — "How do I check if my brand shows up in AI Overviews?"
Pricing — "How much does an AI visibility monitoring tool typically cost?"
Local — "What's the best AI visibility tool for a marketing agency in Baku?"

Each intent produces a different answer shape and often a different competitor set — best-of prompts tend to return lists, comparison prompts produce head-to-head reasoning, pricing prompts often trigger disclaimers instead of numbers. If your prompt set skews toward one intent, your Share of Voice reflects that skew, not your actual visibility.

4. Vary phrasing and specificity within each intent

Don't write ten near-identical best-of prompts. Vary the audience ("for a solo founder" vs. "for an enterprise marketing team"), the phrasing ("best tools" vs. "top options" vs. "which tool should I use"), and the specificity (a broad category vs. a narrow use case). This isn't padding — non-deterministic AI answers can shift meaningfully with small wording changes, which is exactly why N-sample measurement across a varied set matters more than any single prompt's result.

5. Review and approve before you track anything

Writing 30-40 good prompts by hand is slow, so most teams start from an AI-generated candidate list and edit from there. In TAMGIO, you can generate a batch of candidate prompts across all five intents and approve, edit, or discard each one before it enters a tracked project — nothing gets measured that a human hasn't signed off on. That review step is where keyword habits get caught: read each prompt out loud and ask whether you'd actually type it.

6. Refresh the set as the market shifts

Buyer language changes as a new competitor launches, a feature becomes table stakes, or a pricing model shifts. Revisit your prompt set every few months and retire prompts that no longer reflect how buyers actually ask. A stale set doesn't just miss new competitors — it quietly drifts your Mention Rate and Prompt Coverage away from what buyers are really asking today.