How to Check If Your Business Appears in ChatGPT Recommendations
Table of Contents
There’s no Search Console for ChatGPT. No Semrush dashboard that tells you which AI engines are citing your business across which prompts. The tools that exist for this in 2026 are improving, but they’re inconsistent, expensive, and often produce noisy data that doesn’t match what a careful manual check shows.
This is the part of GEO most founders find frustrating. You can do all the work, suspect it’s compounding, and have no clean way to prove it. The honest reality is that the most reliable monitoring method right now is manual prompt testing across the major engines, on a fixed cadence, with the results logged in a spreadsheet. Tools help; they don’t replace this. Below is the workflow I use for our own engagements, the tools worth knowing about, and how to make sense of the data when you have it.
The Manual Method, in Detail
Manual prompt testing is the lowest-tech and most reliable starting point. It also gives you a calibrated sense of what AI engines are actually doing in your category, which makes the tool-based dashboards more interpretable later. Below is the workflow that works.
Build a list of 15–25 prompts a real buyer would ask. These should be the questions your prospects are likely typing into ChatGPT during research. Mix three types: discovery prompts (“who should I talk to about X in Singapore”), comparison prompts (“what’s the difference between X and Y”), and specific prompts (“can you recommend X for [specific situation]”). Avoid generic prompts like “what is X”; they’re too broad to produce category-specific recommendations.
Run each prompt across four engines. ChatGPT (the free version is fine for monitoring), Claude.ai, Gemini, and Perplexity. Each engine cites different mixes of sources, so visibility on one doesn’t predict visibility on others. BrightEdge’s AI Catalyst research found ChatGPT cites a flatter, more diverse range of sources than Gemini, which favours .gov and .edu more heavily; Perplexity commits to shorter, more authoritative shortlists; Gemini behaves more conservatively. The patterns vary by category, but the engines do behave differently and you need to see all of them.
Log three things per prompt per engine. Was your business named (recommended)? Was your content cited as a source? Were any of your competitors named or cited? A simple spreadsheet with columns for prompt, engine, named (Y/N), cited (Y/N), and competitors named is enough for the first three months of monitoring.
Run the test cadence weekly or fortnightly. Weekly produces noisier data but catches faster shifts; fortnightly is what most founder-led businesses can sustain over a year. Either way, the discipline of running on a fixed cadence matters more than the cadence itself. Inconsistent monitoring produces uninterpretable trends.
How to Read the Data
AI visibility moves slower than people expect, and the pattern is usually directional rather than smooth. Three patterns worth recognising in the first 6 months of monitoring.
Citation lifts before recommendations. Most businesses see their content cited as a source 1–3 months before they start being named in answers as a recommendation. The early signal is your URL appearing in the citations panel of an answer; the later signal is your business name being part of the answer text itself. If you’re being cited but not recommended, the gap is usually entity authority and trust signals (covered in the cluster articles on entity SEO and E-E-A-T).
Visibility appears unevenly across engines. It’s normal to appear on Perplexity 2–3 months before ChatGPT, or vice versa, depending on category and existing entity signals. Don’t read this as failure on the lagging engine; it usually catches up within another 1–2 months once the underlying signals propagate. The exception is Gemini, which tends to lag the others more substantially in trust-heavy categories because of its stronger institutional bias.
Specific prompts win before broad prompts. A founder-led business will typically appear in answers to narrow, specific prompts (“who in Singapore handles shareholder disputes under S$2M”) well before broad ones (“best lawyers in Singapore”). The narrow prompts have less competition and lower thresholds for inclusion. The broad prompts come later, if at all, and often require category-level visibility that takes 12+ months to build.
FULL GUIDE
Want the full GEO playbook, end to end?
The guide walks through the 12-month roadmap for getting your business cited by ChatGPT, Perplexity, and Google AI Overviews: entity authority, content structure, schema markup, citation patterns, and the Singapore-specific moves that compound fastest.
Read the full guide: How to Get Found in AI Search →The Tools Worth Knowing About
Several tools have emerged in 2025–2026 to automate AI visibility monitoring. Each has trade-offs worth understanding before paying for any of them. Below is what I’d recommend looking at, and the limitations to be aware of.
Profound is one of the more established players, with monitoring across ChatGPT, Claude, Gemini, Perplexity, and other engines, plus citation analysis and competitive comparison. It’s enterprise-priced and aimed at agencies or large brands; full multi-engine coverage typically requires a custom contract. For a founder-led SME, it’s overkill in the first year but useful once you have a baseline and want to scale monitoring.
Otterly.ai is a more accessible option for SMEs, with tiered prompt-based pricing that starts low (a small entry plan) and scales up with the number of prompts you want to track. It tracks brand mentions and citations across major AI engines, with a cleaner dashboard than the enterprise tools. Worth looking at once you’ve established a baseline through manual testing.
Ahrefs Brand Radar combines brand-mention tracking with AI visibility features. The full AI tracking modules are paid add-ons on top of the base Ahrefs subscription, starting at $199/month per AI platform. Useful if you’re already an Ahrefs customer with budget for the AI add-ons; harder to justify as a standalone purchase given the layered cost structure.
BrightEdge AI Catalyst publishes free public research that’s worth following even if the platform itself is enterprise-priced. Their monthly insights on AI engine behaviour are some of the most rigorous data available in this space.
Free options worth using. Most of the value can be captured for free if you’re willing to do the manual work. ChatGPT free tier, Claude.ai free tier, Gemini free tier, and Perplexity free tier together cover the four engines that matter most. A Google Sheet with the prompt list and weekly results captures the longitudinal trend. Total cost: zero.
What to Do With the Data Over 12 Months
A few checkpoints worth structuring monitoring around.
Month 1 baseline. Run the prompt list across all four engines, log everything. This is your starting point. Most founder-led Singapore businesses score zero or close to zero on this baseline, even if they have decent SEO; AI visibility is genuinely a separate track.
Month 3 first signal check. By this point, if you’ve done substantive entity work and content production, you should see citation appearing on 1–3 of your most specific prompts on at least one engine. If you’re still at zero across the board, the diagnosis is usually weak entity foundations (the AI can’t find a coherent business to attach to your content), shallow topical depth (one or two cluster articles isn’t enough), or content that doesn’t match the question shape.
Month 6–9 trend interpretation. This is where the data starts being interpretable as a trend. Look for two things: are citations broadening across more prompts, and are recommendations starting to appear in addition to citations. The healthy pattern is steady, not spiky: your citation count grows from 2–3 prompts to 8–10 over the period, with the first recommendations appearing somewhere around month 6 in trust-heavy categories.
Month 12 review. If the trend has been positive throughout, you’re now in compounding territory. The work shifts from “build foundations” to “defend and extend”. If the trend has been flat throughout, the diagnosis is harder and usually requires re-examining the underlying strategy: are you building topical authority on the right topic, are your prompts genuinely the ones buyers are asking, is the content actually substantive enough to earn citation.
Where To Start
Build the prompt list this week. Run the first manual check across all four engines. Log the results. That’s it for the first session — under an hour of work, and it gives you a baseline you can measure everything else against.
If the results show your business already appearing somewhere, you have an existing visibility you can compound from. If the results show nothing, you have a clean starting point to track against. Either way, the manual baseline is worth more than any tool subscription you might pay for in month one.
Frequently Asked Questions
How often should I run the manual check?
Weekly is ideal but unsustainable for most founders. Fortnightly (every 14 days) is the cadence that most engagements settle into and produces clean longitudinal data. Monthly is acceptable if fortnightly isn’t feasible; less than monthly produces too few data points to read a trend reliably.
Why do AI engines give different answers each time I run the same prompt?
AI engines use probabilistic generation, which means the same prompt can produce different responses across runs. This is normal. To control for it, run each prompt 2–3 times per check and record the most common pattern across the runs, not a single response. Brand mentions that appear in 2 of 3 runs are reliable signals; mentions that appear in 1 of 3 runs are uncertain. Tools that automate this typically run dozens of variations per prompt to get statistical reliability.
Should I use logged-in or logged-out versions of ChatGPT for monitoring?
Logged-out, or a logged-in account that has no personalised history with your business or category. Personalisation can bias results in ways that don’t reflect what a real prospect would see. Some tools claim to control for this by running through fresh sessions automatically; for manual testing, using an incognito window or a separate test account works.
Read More
Read the full guide: How to Get Found in AI Search (Pillar 2)
Related: How to get your Singapore business recommended by ChatGPT
Related: The Singapore business owner’s guide to being found in AI searches
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