How do you choose which prompts to track for AI visibility?

Choose prompts by starting from the questions real buyers ask on their way to a purchase, not from your keyword list. Pull them from sales and support conversations, search query data, communities and competitor comparisons, rewrite them the way people talk to ChatGPT or Perplexity, and group them by funnel stage, persona and product. Then freeze the set so trends are comparable.

What makes a good tracking prompt

A good prompt is one where appearing in the answer would plausibly lead to a sale. It should be:

• Realistic: phrased like a person typing into an assistant, often a full sentence with context
• Commercially relevant: connected to a problem your product solves
• Unbranded by default: so you measure discovery, not recall
• Specific enough to be useful: “best SIEM for a 200-person fintech on AWS” tells you more than “best SIEM”
• Stable: worth tracking for months

Where to find prompts

Source	What to extract	Example output
Sales call notes and recordings	Questions prospects asked before choosing you	“How do I get SOC 2 ready in 90 days?”
Search Console and Bing queries	Long question queries and comparisons	“X vs Y for small teams”
Reddit, Slack groups, forums	How practitioners describe the problem	“What do you use for secrets scanning in CI?”
Review sites	Comparison and alternative intent	“Alternatives to [competitor] for startups”
Support tickets and docs search	Use-case and integration questions	“Does [category] tool integrate with Jira?”
People Also Ask	Adjacent informational questions	“What is the difference between DAST and SAST?”

Tools can help generate candidates, for example our free AEO prompt generator, but always check them against what buyers actually say.

The selection process

flowchart TD
  A[Collect raw questions from sales, search, communities] --> B[Rewrite as natural prompts]
  B --> C[Tag by stage, persona, product]
  C --> D[Remove duplicates and low-value prompts]
  D --> E[Balance the mix across stages]
  E --> F[Run a baseline on all engines]
  F --> G[Freeze for one quarter]
  G --> H[Review and add tagged batches]

1. Collect broadly

Aim for two or three times the number of prompts you will finally track. Breadth at this stage reveals topics you would not have guessed.

2. Rewrite for AI assistants

People write longer and more specific prompts in assistants than in search boxes. Convert “siem pricing” into “How much does a SIEM cost for a company with 500 employees?” Add the context real buyers include: role, company size, industry, stack and constraints.

3. Tag every prompt

Use consistent tags so you can slice results later:

• Stage: problem, category, comparison, alternative, pricing, implementation, brand
• Persona: for example CISO, security engineer, CMO, SEO manager
• Product or segment: each product line or market you report on

4. Balance the set

A typical B2B mix:

Prompt type	Share of set	Why
Category (“best X for Y”)	About 30%	Main discovery moment
Comparison and alternatives	About 25%	High purchase intent
Problem and use case	About 25%	Early-stage influence
Pricing and implementation	About 10%	Late-stage evaluation
Branded	About 10%	Accuracy and sentiment

Adjust to your sales motion. These are starting proportions, not benchmarks.

5. Baseline, then freeze

Run every prompt across your priority engines several times, record mentions, citations and position, and freeze the set for at least a quarter. Add new prompts in tagged batches so you can report on them separately.

How many prompts do you need?

• Single product, one market: 50 to 100 prompts
• Several products or personas: 100 to 300, with tags per product
• Agencies: a smaller core set per client (30 to 60) plus category prompts shared across clients in the same vertical

More prompts are not always better. A set you can act on beats a large set nobody reviews.

Example: a starter set for a B2B security vendor

A cloud security posture management (CSPM) vendor might start with prompts like these:

Stage	Example prompt
Problem	How do I find misconfigured S3 buckets across 40 AWS accounts?
Category	What are the best CSPM tools for a mid-size company on AWS and Azure?
Comparison	Compare [Vendor] and [Competitor] for multi-cloud posture management
Alternatives	What are alternatives to [Competitor] for a startup?
Pricing	How is CSPM software usually priced?
Brand	What does [Vendor] do and who is it for?

Each prompt carries context a real buyer would add: cloud providers, company size, stage. Multiply this pattern across personas and products, and you have a set that reflects real demand.

Common mistakes

• Copying the keyword list. Short keywords produce generic answers that do not reflect buyer behavior.
• Too many branded prompts. They inflate visibility scores and hide discovery gaps.
• Changing the set every month. Trends become meaningless.
• Ignoring personas. A CISO and an engineer ask different questions and get different answers.
• Only tracking one engine. The same prompt can produce different brands in ChatGPT, Perplexity and AI Overviews.

Using the results

Once tracking runs, the prompt set becomes your content and outreach plan. Prompts where competitors appear and you do not point to missing pages or missing third-party coverage. See how to measure share of voice in AI answers to turn results into a metric, and how to find your competitors in AI search to use the same prompts for competitive analysis. For keyword-level groundwork, see the AEO keyword research guide.