Track the questions your customers ask when they discover your category, evaluate options, compare providers and validate a purchase. The best list reflects the products you sell, the people you serve and the markets where you compete.

Start with the conversations and questions customers bring to your sales and support teams, then choose a manageable set you can learn from. A useful list shows where your brand appears, how it is described and which sources support the answers. Add questions when they represent distinct customer needs, not just another wording of the same topic.

This guide explains what to include, how to handle variations and how to maintain useful tracking as your business changes. We use examples from Superlines, our GEO platform, alongside a hypothetical CRM shortlist you can adapt to your own category.

TL;DR

  • Start with customer conversations. Track natural questions for the products, audiences and markets you serve.
  • Cover the buying journey. Superlines starts with 25% educational questions, 50% evaluation and comparison questions, and 25% decision questions. Adjust that balance to your business.
  • Give each important brand enough coverage. Plan around 50–100 distinct questions as a starting range, using background variations instead of spending slots on minor rewordings.
  • Measure discovery separately. Branded questions can inflate overall visibility. Keep non-branded reporting distinct and retain a stable core as you add questions.

Start With the Questions Your Customers Actually Ask

Your sales team hears the questions prospects ask before buying. Your support team hears what customers need after buying. Start there:

  • Sales calls and demo requests: “How does your tool compare to [competitor]?” “Can it handle [requirement]?” “What would it cost for our team?”
  • Support tickets and onboarding: “Does it integrate with [platform]?” “How do we set up [feature]?” “What is the best way to [accomplish a goal]?”
  • Customer interviews, website chat and FAQs: recurring questions, objections and the language customers use to describe their problems.

Prioritize recurring questions and objections that affect whether customers can understand, choose or use your product.

People often ask AI assistants for recommendations in the context of their situation. “What CRM should a five-person SaaS sales team use?” and “Which CRM meets an enterprise’s data residency requirements?” are different customer needs, even though both concern CRM software. Write the questions so the audience, task and important requirements are clear.

A short prompt can still express a clear task, such as “Salesforce alternatives.” The goal is not to make every question longer, but to include enough context for the answer to reflect a real customer decision.

What We Learned From an Agency’s Tracking Setup

A US agency working with Superlines initially set up tracking with keyword-style prompts, such as “crm startup,” rather than conversational questions such as “What is the best CRM system for a startup?”

The initial prompts had low Branded Response Rates: relatively few answers mentioned any brand at all. After the agency switched to conversational prompts, more answers named brands, and the customer’s brand and website citations appeared within those tracked conversations.

This helped the agency see visibility that the original questions had not captured. It was a change in what they were measuring, rather than evidence that the customer’s underlying visibility had suddenly improved. Branded Response Rate describes whether answers name any brand; it is different from how often they name your brand.

Cover Discovery, Evaluation, Comparison and Decision Questions

Different questions reveal different parts of the buying journey. Use these four categories to spot missing coverage, without forcing every question into a rigid funnel stage.

Awareness: How People Discover Your Category

Awareness questions help people understand a problem or approach:

  • “What is [your category]?”
  • “How does [your product type] work?”
  • “How can a small sales team keep track of customer follow-ups?”

These are useful for understanding category explanations and cited educational resources. An answer may explain the topic well without recommending a provider, so a missing brand mention is not automatically a problem.

Consideration: How People Evaluate Options

Consideration questions connect the category to a particular need:

  • “What is the best CRM for a SaaS startup?”
  • “Which [product type] works with [existing system]?”
  • “How should an enterprise choose a [product type]?”

Include requirements that matter in real buying conversations, such as team size, integrations, security or budget. Avoid adding constraints simply to make your product the obvious answer.

Comparison: How People Narrow Their Shortlist

Comparison prompts test how alternatives are presented:

  • “[Your brand] vs [competitor] for [use case]”
  • “What are the best alternatives to [competitor]?”
  • “Which is better for [requirement]: [brand A] or [brand B]?”

Prioritize competitors that customers actually consider. Read the full answer to understand the tradeoffs it describes, rather than treating a mention as a recommendation.

Decision: How People Validate Their Choice

Decision questions focus on practical checks:

  • “How much does [your brand] cost for [team size]?”
  • “What are the pros and cons of [your brand]?”
  • “Does [your brand] integrate with [platform]?”
  • “How do I get started with [your brand]?”

These can expose outdated pricing, misunderstood features or missing implementation guidance. They are useful for brand monitoring even when discovery is your main growth objective.

Use the 25/50/25 Split as a Starting Point

Across millions of prompts analyzed through Superlines, we have consistently observed the greatest variation in brand recommendations among middle-of-the-funnel prompts. Small wording changes in evaluation and comparison questions can influence which brands an AI engine recommends. Top- and bottom-of-the-funnel prompts generally produce more consistent responses in our analysis.

When Superlines allocates an initial prompt set on a customer’s behalf, it uses this default:

  • 25% top of the funnel: educational and category-discovery questions.
  • 50% middle of the funnel: evaluation, comparison and alternatives questions.
  • 25% bottom of the funnel: pricing, reviews, product checks and getting-started questions.

Use that balance to start, then adapt it to your business. A new category may need more educational coverage; a company facing repeated product misconceptions may need more brand-specific questions. The split is Superlines’ default allocation, not a requirement for every tracking list.

Track Different Needs Without Filling Your List With Rewordings

You do not need a separate tracked prompt for every minor wording change. Start by asking whether the audience, task or requirements have changed.

“What is the best CRM for startups?” and “Which CRM should a startup use?” can represent the same need. “Which CRM meets an enterprise’s data residency requirements?” asks a different question, even though both concern CRM software.

This hypothetical CRM shortlist shows how to make those decisions:

A CRM shortlist: keep, combine or track separately

Keep: “What is the best CRM for startups?”
A clear recommendation question for a target customer segment.
Combine: “Which CRM should a startup use?”
Use as a wording variation of the first question unless comparing exact phrasing is the goal.
Track separately: “Which CRM meets an enterprise’s data residency requirements?”
The audience and purchase requirement differ from the startup question.
Track separately: “Does [our CRM] integrate with [platform]?”
A product check that can reveal factual errors; label it as branded monitoring.

Keep a wording variant separately when comparing that exact phrasing is the purpose of the test. Otherwise, spend your tracking capacity on distinct needs before adding more ways to ask the same question.

How Superlines Handles Variations and Exact-Match Analysis

With prompt variations enabled, Superlines tests different wordings in the background, so customers do not have to fill their tracked list with minor rewordings of the same intent. Those variations do not require additional tracked-prompt slots. Customers can also request exact-match analysis, which uses the specified prompt without variations.

Use variations to explore how wording affects a buying question. Use exact-match analysis when you want to follow a particular formulation consistently. Keep the analysis mode consistent when comparing results over time.

How Many Prompts Should You Track?

As a practical starting range, allocate around 50–100 distinct tracked prompts for each important brand whose AI Search visibility you want to improve. This gives you room to examine different buying questions rather than relying on a handful of results. A narrower pilot may need fewer; brands with multiple offerings, audiences or markets may need more. The number is a planning guide, not a universal minimum or guarantee of representative coverage.

Different products and services can attract different customers and competitors, even under the same brand. A startup-focused CRM and an enterprise CRM may be evaluated against different vendors and requirements. Organize enough relevant questions by offering, target audience and market to see where each group is visible or missing, and to choose specific improvements rather than acting on one blended visibility figure.

Prioritize questions that recur in customer conversations, matter to your offering and could lead to a useful decision. That might mean correcting a product misconception, improving a pricing explanation or understanding why competitors are recommended for a relevant use case.

Competitor appearances can help identify questions worth investigating, but they do not establish how many customers ask them or how much revenue is at stake. Likewise, Google keyword volume can help prioritize topics without measuring demand for the corresponding AI prompt. Do not discard a valuable customer question just because it has no reported Google search volume.

Build and Expand the List in Superlines

Superlines generates initial question suggestions by analyzing your business, offerings, target audiences and competitors. SEO data and trending online topics can provide additional ideas, and you can add, edit or remove suggestions to match the conversations you actually want to track.

You can also bring in existing material:

  • Connect Google Search Console to import keywords or longer queries.
  • Upload a CSV of questions, or turn an existing keyword list into conversational prompt suggestions for review.
  • Provide a website URL for Superlines to suggest conversations relevant to that offering.

Review suggestions against what you know about your customers. An automatically generated question is a candidate to track, rather than evidence that customers are asking it.

Superlines also automatically tests additional prompt opportunities outside the tracked list. These tests do not consume the customer’s prompt quota. If an opportunity is valuable, adding it to tracking takes one click; only then does it use one prompt from the quota.

Keep Branded and Non-Branded Reporting Separate

Branded and non-branded prompts answer different questions. “Superlines pricing” checks how the brand is presented when it is already named. “Which GEO platform should a marketing agency use?” checks whether it appears in a broader recommendation.

Branded prompts usually mention your company by name, so AI answers are much more likely to mention it. Mixing those results with non-branded questions can inflate your overall Brand Visibility and make your discoverability look stronger than it is. Review non-branded questions separately to understand how often AI engines bring up your brand when people are exploring the category, comparing options and choosing a provider without naming you first.

Superlines gives you different ways to keep those views apart. You can create a separate “Branded Prompts” brand for a dedicated reporting view, or keep the questions under your existing brand and use custom labels to filter branded and non-branded results. You can also label by buying stage, product or market. Choose the setup that suits your team, but use the non-branded view when reporting discovery visibility.

Keep the classification useful: “[Your brand] vs [competitor]” includes your name, while “[Competitor] alternatives” does not. Both can reveal comparison opportunities, but they should not be treated as equivalent tests of unprompted brand discovery.

Compare the Same Questions Across Relevant Engines and Markets

Track the same question across the AI platforms your audience uses so you can see where answers differ. Keep country and language consistent for a direct comparison, then examine other markets separately.

For example, questions about startup CRMs in the US and enterprise CRMs in Germany can involve different buyers, requirements, languages and competing vendors. Compare equivalent questions within each market and audience first, then look across those groups to decide where content or positioning needs attention.

Superlines supports custom prompt sets and prompt-level analysis across engines and markets. Select coverage that fits your audience and plan: current self-service plans include three chosen answer engines from the available range. Check current plan allowances when expanding tracking.

When an AI search system searches the web, it may expand a prompt into related searches, often called query fan-out. These searches are different from the question being tracked and from the sources eventually cited in the answer.

Superlines surfaces available fan-out queries for investigation. For a CRM recommendation, searches about pricing or integrations might suggest a useful gap in your question list. Check whether the need matters to your customers before adding it. A fan-out is evidence of a search performed during answer generation, not a customer-demand count or proof that a particular page was used.

For content work arising from those findings, see our guide to improving content visibility in AI Search.

Review the List Without Losing Your Baseline

Check priority prompts monthly and review the whole list quarterly as a practical starting cadence. Add questions sooner when you launch a product, enter a market or repeatedly hear a new customer concern.

Keep a stable core of relevant questions for trend comparisons. Label additions so you can inspect them separately before combining them with the established set. Record meaningful changes to wording, market, language or analysis mode; a new test can produce a different result even when nothing else has changed.

Retire questions when the product or audience is no longer relevant, or when they duplicate another question without adding useful insight. In Superlines, pausing a prompt stops new tests and preserves its history, but the paused prompt still counts toward your tracked-prompt allocation. Deleting it frees the slot but also deletes its historical data. Keep commercially important questions even when their visibility is low.

This avoids three common mistakes: expanding the list only where your brand already performs well, replacing difficult questions with easier ones, and interpreting a changed prompt mix as a performance gain. For a wider review beyond prompt selection, use the GEO audit guide.

How to Know You’re Tracking the Right Prompts

A useful list should help you answer specific questions:

  • Where does our brand appear for the customer needs we serve?
  • Are answers accurate about our pricing, features and fit?
  • Which competitors and cited sources appear for those same needs?
  • What differences between products, markets or engines deserve attention?

Read the answers behind the metrics. An educational prompt that rarely names brands may still reveal useful cited resources. A recommendation prompt that repeatedly names competitors may deserve a closer look at how the answer explains their fit.

Use Brand Visibility, Citation Rate and Sentiment to understand presence, website citations and how the brand is described. Share of Voice adds competitive context. These describe your sampled answers; assess referred visits and business outcomes separately. Our guide to generative search metrics explains the measures in more detail.

Start Tracking the Conversations That Matter

Start with the questions customers actually ask and plan enough coverage for each important brand, offering and market. Keep non-branded discovery separate from branded monitoring, use the 25/50/25 allocation as an initial mix, and expand when a new question helps you make a better decision.

Superlines is a full GEO platform centered on AI Search visibility. Custom questions, background variations, opportunity tests and label-based reporting help teams track relevant conversations, while competitor and source intelligence and Action Center recommendations help decide what to do next. Website audits, technical and schema optimization, and content generation support the work that follows.

Start a Superlines trial to build your prompt list and explore where your brand appears today.

Frequently Asked Questions

How many prompts should I track for AI search visibility?
For each important brand whose AI Search visibility you want to improve, around 50–100 distinct prompts is a useful starting range, not a fixed minimum. Cover the relevant products or services, customer groups, competitors and markets separately enough to identify useful improvements; a narrow pilot may need fewer and a complex brand may need more. Superlines starts with a 25/50/25 top-, middle- and bottom-of-funnel mix, which you can adapt. Background wording variations and additional opportunity tests do not consume extra tracked-prompt slots; adding an opportunity to tracking uses one slot.
Should I track the same prompts on every AI platform?
Track the same questions across the AI platforms that matter to your audience, keeping country and language consistent for direct comparisons. Different products, customer groups and markets may have different competitors and requirements, so examine those segments separately instead of blending them into one overall picture. You do not need every available platform to start. Superlines self-service plans currently include three selected answer engines; choose coverage that fits your audience and plan.
How often should I update my AI search prompt tracking list?
Check priority prompts monthly and review the whole list quarterly as a practical starting cadence. Add questions sooner for product launches, new markets or recurring customer concerns. Keep a stable core for trends, label additions and record meaningful changes to wording, market, language or analysis mode. Retire irrelevant or redundant questions, rather than removing important questions because visibility or reported Google search volume is low. In Superlines, a paused prompt preserves its history but still uses one tracking slot; deleting it frees the slot and deletes the historical data.
What is query fan-out and how does it affect prompt tracking?
When an AI search system searches the web, it may expand a prompt into related searches called fan-out queries. These are different from the tracked question and from sources visibly cited in the final answer. Superlines surfaces available fan-outs to help investigate related topics. Use them as ideas for questions or content worth examining, then check their relevance to your customers. They do not measure customer demand or prove that a particular page was used.
What percentage of my prompt list should be branded vs unbranded queries?
There is no universal branded-versus-unbranded percentage. Track non-branded questions to measure whether AI engines recommend your brand without being prompted with its name; use branded questions to monitor pricing, features, comparisons and reputation. Mixing them can inflate overall Brand Visibility and hide weaker discovery performance. In Superlines, create a separate “Branded Prompts” brand for its own view, or use custom labels to filter branded and non-branded prompts under one brand. Choose what fits your reporting, but compare discovery separately. The 25/50/25 funnel split is a different classification.

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