How to Check If AI Platforms Recommend Your Business or Your Competitors

Start with five to ten questions that a customer might ask before choosing a business like yours. Avoid questions that artificially include your brand name unless you specifically want to test branded visibility. The most useful questions are category, comparison, suitability, trust, price, location, and objection questions.

For example, a pet service might test questions such as: which pet grooming options are suitable in Singapore, what should I compare before choosing a pet care provider, who is trusted for anxious dogs, and what are good alternatives near a specific area. A dental clinic might test emergency care, braces suitability, wisdom tooth extraction, price context, and trust signals.

Keep the questions stable. If you change the wording every time, it becomes hard to see whether visibility is improving or whether the answer simply changed because the prompt changed.

Run the same questions across the platforms that matter to your customers. For most businesses, a basic set can include ChatGPT with search, Gemini, Perplexity, and Google AI Overview where available. Depending on your market, Claude, Grok, DeepSeek, or other systems may also matter.

Do not assume all platforms behave the same way. One may mention your business, another may ignore it, and another may cite a directory or competitor page. Those differences are useful. They show where your public information is strong and where the answer ecosystem is weak.

When possible, save the answer text, cited sources, date, platform, and prompt. You do not need a complex tool at the beginning. A spreadsheet is enough for a first pass.

Separate the outcomes. A mention means the AI answer named your business. A recommendation means it suggested your business as a suitable option. A citation means it pointed to a source that supports the answer. Competitor exposure means another business appeared in the same decision space.

This distinction matters because a weak mention is not the same as a strong recommendation. Your brand might appear in a list but not be chosen. Or it might be recommended but with no source. Or it might be absent while competitors are described in detail.

A simple scoring sheet can track prompt, platform, brand mentioned, brand recommended, source cited, cited URL, competitors named, answer quality, and notes. After a few prompts, patterns usually become visible.

If your business is absent from category questions, improve entity and service clarity. If it is mentioned but not recommended, add stronger reasons to choose you: proof, process, service detail, location fit, and customer examples. If AI cites third-party pages instead of your site, improve first-party pages that can support the answer.

If competitors appear more often, study what public information makes them easier to recommend. They may have clearer service pages, stronger reviews, better category positioning, or more useful FAQ content. The goal is not to copy them. The goal is to close evidence gaps.

Retest after meaningful updates. Do not retest every hour and overreact to variation. AI visibility work is most useful when you connect changes to prompt-level movement over time.

Manual testing is useful for learning the basics, but it becomes slow when you need to compare multiple platforms, prompts, competitors, citations, and follow-up actions. This is where automation helps.

Aitrack.sg helps automate this process with AI visibility scans. It checks whether AI platforms mention, cite, or recommend a business, where competitors appear instead, and which page-level actions are worth fixing first. You can still use manual testing to understand the logic, then use automation to make the process repeatable.

The first mistake is testing only branded prompts. Asking an AI platform about your exact business name is useful, but it does not show whether you appear in discovery or recommendation moments. Customers often begin with a need, not a brand.

The second mistake is treating one answer as final. AI systems can vary. Look for repeated patterns across platforms and prompt types. If your business is absent from most category questions, that is more meaningful than one unusual answer.

The third mistake is ignoring cited sources. Sources explain why an answer happened. If AI platforms cite directories, review pages, or competitor content more often than your own site, that is a clear signal to improve your first-party pages.

The final mistake is collecting data without changing anything. The value of AI visibility testing comes from turning missed questions, weak citations, and competitor exposure into concrete content and proof improvements.