What is the best AEO tracker for ChatGPT, Gemini and Perplexity together?

What should a tracker cover?

A useful test starts with the engines your buyers use. Ask to see ChatGPT, Gemini and Perplexity in the same view. Then ask what each result represents. A tool may use an app, an interface for software, or a search setting that differs from your own test. The name of the engine alone does not tell you how the answer was gathered.

Ask for the exact question sent to each engine and the full answer returned. Check whether the view keeps each engine separate as well as showing the whole set. You need to see where your name appears and where it does not. A combined score can hide a gap in one engine behind a stronger result in another.

Example: Justin’s case study includes AI-answer captures from his own sites. For your own test, keep the answer from each engine separate so you can see where your business appears.

Ask which settings you can choose and which you cannot. The model, web search setting, location, account state and date can all be useful context. If a setting is unknown, the report should say so.

Keep the question set tied to real decisions. Include questions about your service, your market and the problems buyers need to solve. Include your brand name in some questions and leave it out of others. A branded question tests whether an engine can discuss you when prompted. An unbranded question tests whether your business appears without that cue. Both are useful, but they answer different questions.

What should be on your tracker checklist?

• Separate views for each engine and a shared view of the same questions
• Saved answer text with dates and known settings
• Repeat runs with past results kept for review
• Names and source links counted in separate fields
• Exports that include the raw answers and links
• Clear labels for failed runs and unknown settings

Why should you run the same questions again?

Repeat runs help you see a range of answers rather than relying on a single snapshot. Google says its AI search features can return different answers and links. Keep past answers so you can compare the actual text.

Keep the wording fixed while you test change over time. If you change the question, place and search setting at once, you cannot tell what drove a difference. Save the date and time of each run. Keep the old answer when a new one arrives, so your team can inspect the change rather than trust a chart alone.

Example: A firm appears in one saved answer to a local service question, then a later run leaves it out. Keep both answers and their settings together for review.

Choose a repeat schedule that fits the decisions you make. Ask how the tool handles missed runs, engine errors and changes to a model or search mode. A failed run is not the same as a valid answer that leaves you out. The report should make that difference easy to see.

You can add new questions as your business changes, but keep the old set intact for fair comparisons. Label any new or edited question and note when it entered the set. If you remove a question, retain its past results. Otherwise a trend can move simply because the questions changed, even if the answers to the old set did not.

How do mentions differ from citations?

A mention names your business; a citation points to a source. Keep them separate and see the guide to AI visibility tools compared for more on the difference.

Perplexity says its answers include numbered links to sources. OpenAI says search answers can include citations, but those results and citations can be incomplete or wrong. In OpenAI’s web search tool for software, sources consulted can exceed the references shown inline. Do not assume every page consulted is visible to the reader or that a cited page caused a mention.

Example: An answer names your firm but links to a general guide. Record the name as a mention and open the link to see whose page it cites.

Ask the tracker to keep the text around the name, the link target and the source title. Check whether it counts a link to your site, a link to a third party, or a plain name in the answer. Ask how it treats a link that fails to open or points to a page that has moved. A list of raw links is useful, but labels and saved text make it easier to review.

Also read the claim itself. Your business might be named with the wrong location, service or contact detail. A positive count can hide an answer that sends a buyer in the wrong direction. Google says Gemini can produce inaccurate information, so check key claims against your own records before you act on them.

How can you test a tracker by hand?

Test a sample of your own buyer questions in each engine and compare the saved answers with the tracker. Start with a short list that covers your brand, a service and a market. Write each question in full. Use the same words in the tracker and in your own checks, without adding a follow-up that changes the request.

For each manual check, save the full answer, visible source links and the time. Record the engine and any search mode you used. Note your location, whether you signed in, and whether memory was on when that detail is available. OpenAI says ChatGPT search can use an approximate location and saved memory when it rewrites a query.

Example: Say your team tests a question about a service in a city. One person saves the answer from each engine and notes the account and location. The team then checks the tracker’s record for the same question. It reviews the actual text and links before it compares any counts.

Do the checks close together when practical. Answers can vary, and the tool’s setup may differ from yours. Ask the seller to show the source record and explain any gap.

Look for specific errors. Did the tracker save the wrong engine? Did it miss a name that is plainly in the answer? Did it label a third-party link as your own page? Did it save only a summary when you asked for the full answer? Record the issue beside the source text so the seller can respond to the same evidence.

Try a question where your business is named and one where it is absent. Then inspect a cited page and a mention with no link. Ask a colleague to review the same saved answers without seeing the tool’s labels. Agree on definitions before you buy.

What history and reports should you ask for?

Ask for a history you can inspect and take with you. Each saved run should show the question, engine, date, answer and source links. It should also show the settings the tool knows. A chart is useful for spotting a shift, but the underlying answer lets you decide what the shift means.

Ask to see an export before you sign. Check that it includes the raw text as well as labels and totals. Ask whether you can filter by engine, market, question and date. If the tool makes a score, ask for its formula and the set of questions behind it. A score without those details is hard to use in a budget meeting.

Example: Say your team adds a new market to its question set. A chart rises after the change, but the old and new questions are mixed. By splitting the set, you can see whether the old market changed or the new questions drove the result. Keep that context beside the chart.

For a large firm, ask how the tool groups brands, locations and teams. Check who can see the data, who can change questions and who owns the account. Ask what happens to saved answers if you stop using the service. For more buying and proof questions, see the guide to choosing an AI visibility agency.

Agree on a simple report for decision makers. Show the questions that matter, the engines checked, the date range and the saved examples. Put names, source links and factual errors in separate fields. For counting formulas, see the guide to AI share of voice tools. Add the next action and its owner.

Example: Before you commit, ask the seller for a sample export from a test using your own questions. Open it with the people who will use the report. Find the full answer, the source links and the settings for each run. Check whether a person can trace a total back to the answers behind it. If the export leaves out details your team needs, ask to see how you would get them before you sign. Keep a copy of the sample so you can compare it with the report you receive later.

What can a tracker tell you about business results?

A tracker shows observations from the questions and runs it records. It does not, by itself, show every answer seen by real buyers or prove that an answer led to a sale. Treat the saved set as a test sample. Its value rests on the questions, settings and care used to read the results.

Google says no third-party tool has access to its internal ranking or AI systems. Be wary of a seller who claims such access. Google’s own generative AI report covers impressions for its search features. It is useful context for Google, but it is not a combined report for the three engines in this guide.

Example: If saved checks show your brand more often after a site update, inspect the new answers and links. Look at your lead and sales records for the separate question of business results.

If a source link is missing, check that the page exists and can be reached. OpenAI and Perplexity describe search crawlers with their own access rules. Check the relevant platform guidance before changing site access.

Start with a hand check of your buyer questions in each engine. If you need to cover many markets, use that record to evaluate a tracker.