Frequently Asked Questions

Start with three things:

1. Review your searches — these are the phrases indextr uses to test your AI visibility. Make sure they reflect how your customers actually describe what they need. Add or adjust them under the Searches tab.
2. Add competitors — add your top 1–2 competitors under the Competitors tab so your score reflects how you rank against the businesses you actually compete with.
3. Check your recommendations — once your first scan completes, go to your dashboard and start with the top recommendation on your list. Each one shows how long it typically takes to see results.

Don't worry about getting everything perfect on day one. Your score will improve as you take actions and indextr learns more about your business over time.

AI visibility measures how often and how prominently AI engines — ChatGPT, Google AI Overview, Gemini, Perplexity, and Claude — recommend your business when someone asks a relevant question. As more people use AI to find products and services, showing up in those answers has become as important as showing up in Google search results.

indextr runs a set of search phrases through the AI engines your plan covers and records whether your business was mentioned, whether your website was cited, how you were described, and how you compared to competitors. After each scan, your Visibility Score is updated and new recommendations are generated based on what the scan found. Your dashboard always reflects the results of your most recent scan.

Searches are the phrases someone might type into an AI engine when looking for a business like yours — for example, “best estate planning attorney in Denver” or “affordable HR software for small teams.” Choose phrases that reflect how your actual customers describe what they need, not how you describe what you sell. indextr can suggest phrases based on your business description, or you can add your own.

Competitors give indextr a reference point. During each scan, it checks whether your competitors appear in the same AI responses as your tracked searches. This lets your score reflect not just whether you showed up, but how you ranked relative to the businesses you actually compete with.

Your score is a weighted average across the AI engines your plan covers — ChatGPT on Free; ChatGPT, Gemini and Google AI Overview on Starter; all five including Perplexity and Claude on Pro and Done-for-You. Each engine is weighted by its estimated share of consumer AI search, with ChatGPT and Google AI carrying the most weight and Claude the least. indextr updates these weights as the AI landscape shifts. Within each engine, your score is based on how often you were mentioned, whether your URL was cited, how positively you were described, and how you ranked against competitors.

They measure different things. Mentioned In is a straight count — the share of all the answers we collected where your business was named, with every result counting equally. Your Visibility Score weights each engine by how much it is actually used, so being named only by a smaller engine lifts your mention rate without moving your score much. The score also folds in whether your site was cited, how you were described, and how you placed against competitors. A high mention rate with a low score usually means you are visible on the engines fewest people use.

Each scan runs every phrase you track through every AI engine on your plan, so three phrases on Starter is nine answers. Sometimes fewer are counted, and you will see something like “Across 8 of 9 answers”. The usual reason is that Google does not show an AI Overview for every search — it decides per query and is inconsistent about it — so for that search there is no answer to read. Rather than record it as “you were not mentioned”, indextr leaves it out of the count: an answer that never appeared is not evidence you are invisible. The same applies when an engine replies by asking where you are instead of answering. Counting those as misses would report a worse score than the truth.

AI engine responses vary naturally from run to run — the same question can return different answers on different days as models update, new content gets indexed, and query phrasing shifts slightly. Early scores (1–3 scans) are less stable than scores built from many scans over time. A single-scan change of a few points is normal. A consistent trend in one direction over multiple scans is the meaningful signal to watch.

AI search results are personalized — based on your signed-in Google account, search history, saved locations, and even the specific moment you search. The same person searching the exact same phrase twice, minutes apart, can get different results. This isn't unique to indextr or to Google; it's true of every AI search surface.

indextr scans from a consistent baseline — no signed-in account, no search history, and your city supplied as the place the search is made from — so every scan is measured the same way every time. That makes it possible to track a consistent, comparable signal over time, rather than a snapshot of any one person's session.

If you want to sanity-check a result yourself, search in Guest Mode (or a signed-out incognito window) rather than your regular signed-in browser. That removes your own personalization and should align much more closely with what indextr shows.

What indextr is built to show you is the trend — whether your visibility is going up or down across many scans and search phrases, and how you compare to competitors — not a promise that any single scan will exactly match any single search you happen to run yourself.

A score of 0 means your business was not mentioned in any of the AI responses for your tracked searches. This is actually the most common starting point — most businesses have little to no AI visibility before actively working on it. Your recommendations are specifically designed to move this number.

Your search phrase and nothing else — the same thing a person types into the box. We deliberately don't attach hidden instructions telling the AI how to answer. We used to, and it inflated results: on a broad question where the business genuinely never came up, the extra instruction pushed ChatGPT to name a local business anyway about half the time. Sending only the phrase means what you see in indextr is something you can go and check yourself.

Because the phrase decides what you're measuring, and that's your call rather than ours to guess. There are three cases:

• You name a city — “smart home installer denver co” — that's a local search, and we send it exactly as written.
• You say “near me” — that's a local search too, but without a place in it. A person typing that into ChatGPT has their location filled in automatically from their internet connection; an API request has none, so we supply your business's city the same way. Without it, ChatGPT would just ask which city you're in and name nobody.
• You name no location at all — “what does smart home installation cost” — we send nothing extra, because that's a national question and adding a city would change what you asked.

We never rewrite your phrase in any of these cases. The words we send are the words you typed.

Most of the time you won't. In our testing, whether a business appears at all is highly consistent — if indextr says you show up for a phrase, you'll almost always see yourself show up too, and if it says you don't, you won't. That part is solid, and it's most of what matters.

When a check does disagree, it's usually about where you ranked rather than whether you were there — you were named both times, just higher in one answer than the other.

And for some phrases, your position genuinely moves. On a competitive search, ChatGPT might put you first today and fourth tomorrow. That isn't our measurement being unreliable — there simply isn't one fixed answer to find. Check it twice yourself and you'll often disagree with your own first result.

For those phrases, visibility is better understood as how often than as a single position. If ChatGPT names you in two of every three answers, then one time in three someone asking won't see you — so a check that comes back empty isn't a contradiction, it's that one in three. It's why the Last 3 Scans column shows “2 of 3” rather than a single verdict.

Two things can widen a gap unnecessarily. If you're signed in, ChatGPT remembers what you've discussed before, so asking about your own business repeatedly teaches it to mention you — that reflects your chat history, not your visibility. And ChatGPT's app isn't identical to the service underneath it; it adds its own instructions, so a little difference is built in.

To compare fairly: open a Chrome guest window, stay signed out of ChatGPT, and use a fresh window each time. If the phrase is one where your position moves, check three times and compare the pattern against your Last 3 Scans rather than one answer against another.

At least three. Because ChatGPT gives different answers on different runs, one scan is a single sample rather than a verdict — reading too much into a single result is the most common mistake. Your Analysis page has a Last 3 Scanscolumn for exactly this: it shows how many of your three most recent scans found you for each phrase. Appearing in three of three is a consistent result; one of three is within normal variation; none of three means you're genuinely not showing up. Until you have three scans it tells you how many more you need rather than guessing. The automatic weekly scan gets you there in three weeks, but your on-demand scans get you there far sooner — running one now, one after you make a change, and one a couple of weeks later is a better set of three than three consecutive days, because the readings are spread across the time your change would actually take effect.

Your website, overwhelmingly. We measured every source ChatGPT cited across 128 answers to local service questions: about 97% were businesses' own websites. Google Business Profile, Yelp, BBB and Facebook were cited zero times. Directory listings still matter for other AI engines — Google AI Overview in particular — but for ChatGPT specifically, your own site is what it reads.

There's one thing that overrides all of it. OpenAI requires that its search crawler, OAI-SearchBot, be allowed to reach your site — sites that block it don't appear in ChatGPT's answers at all. This is worth checking even if you never chose to block anything: several web hosts and security services began blocking AI crawlers by default in 2025, so sites get locked out without their owners knowing. indextr checks this on every scan and will tell you if it's the problem.

A current OpenAI model with live web search enabled, so results reflect what the web says today rather than what the model memorised during training. We tested several models against real searches and the differences between them were smaller than ChatGPT's own run-to-run variation — meaning no model was measurably more accurate than another. Where accuracy is indistinguishable we choose the least expensive option, which keeps your plan's price down rather than buying a difference nobody can detect.

It depends on the type of change, and the honest answer is that these are estimates of when to look rather than promises of when something will move.

Google reviews and Google Business Profile updates are worth checking after 2–4 weeks, because those sources are re-read often. Website changes are worth checking after 4–8 weeks, which is roughly how long crawling and indexing takes. Third-party citations — industry publications, local news, directories — are a 2–3 month horizon.

Those ranges come from how frequently each kind of source is re-crawled, not from measuring your results or anyone else’s. No engine publishes a timetable — Google documents that it crawls a site more often when the site changes often, but gives no number, and neither OpenAI nor Anthropic publishes one at all.

Perplexity is the exception, and it is faster.Its documentation says that when someone asks it a question it “might visit a web page to help provide an accurate answer” — it fetches at the moment of the question rather than working from something crawled weeks earlier. So a change to your site can show up there almost straight away. Bear in mind Perplexity carries the least weight of the five engines, because fewest people use it, so movement there lifts your overall score only slightly.

Every recommendation carries the same estimate so you know when it is worth looking again — and if nothing has moved by then, that is information too.

Google Search Central — managing crawl budget · checked 29 August 2026

Perplexity — bots and crawler documentation · checked 29 August 2026

Run an on-demand scan a few days after you make one, and watch Perplexity first — if it is on your plan.

Most engines answer from a copy of your site made whenever their crawler last visited, so a change you publish today stays invisible until they come back, which can be weeks. Perplexity documents that when someone asks it a question it may go and read the page right then. So it is the one engine that can reflect a change almost immediately.

That makes it an early signal rather than a result. If Perplexity picks your change up, the page is live, a crawler can read it, and it says what you meant — you can stop worrying about the change itself and wait for the slower engines. If it does not, something is wrong with the change and you have found out in days instead of six weeks.

It will not move your score much on its own. Perplexity carries the least weight of the five, because fewest people use it. What it gives you is confirmation, early.

Perplexity — bots and crawler documentation · checked 29 August 2026

Start with the highest-priority recommendation at the top of your list. indextr puts the ones it judges most important first, and within those the quickest to show a result. In general: reviews and Google Business Profile updates are the fastest way to move your score; website content changes are medium-term; building citations and press mentions is a longer play that pays off over time.

Being mentioned means an AI engine named your business in its response. Being cited means the AI engine included a direct link to your website as a source. You can be mentioned without being cited — the AI knows about you but pulled the information from elsewhere. Citations are especially valuable because they send traffic directly to your site and signal to other AI engines that your website is an authoritative source.

Two different places, and the difference explains a lot of otherwise confusing results.

Some of it is looked up while it answers. ChatGPT, Gemini and Google all search the web mid-answer, read what comes back, and summarise it. That part behaves like search: it reflects what is on your site and on other sites today, and it changes within weeks when you change something. Every recommendation indextr gives you is aimed here, which is why you can act on them and then watch your next scan.

The rest is what the model already knew. Language models absorbed an enormous amount of text while they were built, and they can answer from that memory without looking anything up. That knowledge comes from what has been written about you over years — press, forums, reference sites, books — and it only changes when a new model is trained, which is not on any schedule you control.

This is usually why a business is named in an answer but its website is never cited as the source: the engine is describing you from memory rather than from reading your site. It is also why a well-known brand can be mentioned everywhere while a better business nearby is invisible — one of them has been written about for a decade.

We do not pretend the second one is something you can fix this quarter. It is worth understanding, because it explains your numbers, but the work that actually moves your visibility is all on the first.

It can, but for most businesses it does not — and the more useful answer is what we can and cannot measure.

Scans run with live search on, so your score reflects the whole answer, which may blend what the engine just read with what it absorbed during training. Memory only reaches some of the numbers. It can put your name in an answer, but it cannot produce a citation, because a citation needs a real source URL and memory has none. Sentiment, rank and competitive position are all measured only on answers where you appeared, so they inherit whatever caused the mention.

What we cannot tell you is how much of your score comes from memory. It is tempting to assume that being named without being cited proves it, and that is wrong: a citation matches your own domain, so an engine may have found someone else’s page mentioning you and named you from that — which is retrieval, not memory. The two look identical from the outside.

The only clean test is asking with search switched off, which we do not yet run as part of a scan. When we tried it by hand in August 2026, two local businesses were unknown to all three models we tested, while a nationally published methodology was known to one of the three.

So for a business without wide public coverage, the honest expectation is that memory contributes nothing and your score is earned entirely by what is findable today. Which is the better position to be in, because that is the part you can move.

A little, slowly, and you will not be able to watch it happen.

What a model can say about you without searchingwas absorbed when it was trained. Getting into that memory means being written about repeatedly, across many independent sources, over years — press, trade publications, forums, Wikipedia, other people’s case studies. One page saying it once contributes essentially nothing. What survives training is repetition across a great many separate places.

Allowing the training crawler is a choice, not a lever. It does not make you memorable; it only avoids excluding you. Refusing it is a perfectly reasonable position and costs you nothing in search visibility, because search and training are separate crawlers with separate permissions.

And the payoff lands whenever the next model is trained, which nobody publishes and you cannot observe. Anyone promising to get your business into an AI’s training data is selling something they cannot measure either.

The useful part: most of this work counts twice. A trade write-up or a supplier case study naming you is a crawlable page that helps your visibility now, and may feed a future model as a side effect. Do it for the reason you can measure.

Because it isn’t the priority it once was, and we’d rather point you at things with more evidence behind them. Google states plainly that “structured data isn’t required for generative AI search, and there’s no special schema.org markup you need to add.” OpenAI documents one requirement — that its crawler can reach your site.

This is not a reason to remove what you already have.Schema drives Google’s rich results, which is a real benefit that has nothing to do with AI. Bing is also widely reported to reward structured data, and ChatGPT’s search results have drawn on Bing’s index — we have not been able to confirm Microsoft’s own wording on that, so treat it as a possibility rather than a reason. If it’s on your site, leave it.

What changed is its rank on the list, not its value. It used to be near the top. It is now a maintenance item rather than a project.

Google Search Central — AI features and your website · checked 29 August 2026

OpenAI — crawlers and site owner controls · checked 29 August 2026

It’s a reasonable expectation, and it was true once. Schema markup exists because older search technology couldn’t reliably pick out “this is the phone number, this is the service area, this is the price” from ordinary sentences. Labelling those facts in hidden code solved a real problem.

Language models don’t have that problem. They read the visible page the way a person does, and they pick up things the markup can’t carry — that you install two competing brands, that you cover these suburbs but not that one, that commercial work is a small part of what you do. Schema was a workaround for a limitation that the technology now reading your site no longer has.

There’s a second thing worth knowing, though we’d put it as an observation rather than a rule. Schema is your own description of your own business, in a field no visitor ever sees. What indextr measures is where AI engines actually got their answer — and in practice that is overwhelmingly reviews, directories and pages other people wrote about you, not what a business says about itself. Nobody has published why, so we won’t claim to know. We can only tell you where the citations come from.

We’d rather be straight with you than sell you a task list. If an engine publishes something that changes this, we’ll change our advice and say so.

Into the visible page. Write the facts where a customer can read them too — your service area, the brands you carry, what you charge, what you don’t do. That’s the same job schema markup was invented for, done in a way that works for the engine and for the person deciding whether to call you.

Put another way: if you have schema, keep it and keep it accurate. If you don’t, writing a clear service page will do more for your AI visibility than adding markup would — and it’s the one of the two that also wins you the customer reading it.

AI engines and Google use different signals to decide what to recommend. Google ranks pages; AI engines synthesize information from many sources — your website, reviews, directories, press mentions, and their own training data. A business with strong Google rankings may still have low AI visibility if it hasn't built the broader digital footprint that AI engines draw from.

Every plan gets one automatic scan a week. On top of that you can run scans on demand whenever you want one: Free gets 1 a week, and every paid plan gets 5.

Weekly rather than daily on purpose. AI answers vary from run to run, so scanning a business that has not changed anything produces a jittery line rather than information — and reacting to that noise is the most common mistake. The scan that tells you something is the one you run after you have made a change, which is what the on-demand allowance is for. If you are on a trial, the first three scans run daily so you can see movement quickly, then it settles to weekly. You can also trigger a manual scan from inside your dashboard at any time.

Yes — from the Dashboard, Searches or Competitors pages, and that is the scan worth paying attention to, because you run it after changing something. Free gets 1 a week and every paid plan gets 5, on top of the weekly automatic scan. The allowance is a rolling week, so it refills as you go rather than resetting on the 1st.

Upgrading increases the number of AI engines scanned (ChatGPT on Free; ChatGPT, Gemini and Google AI Overview on Starter; all five on Pro), how many scans you can run on demand (1 a week on Free, 5 on any paid plan), the number of searches you can track, and the depth of your recommendations. Free accounts see what to fix. Starter accounts get up to 5 recommendations per scan across all categories, each with step-by-step actions you can follow. Scans pause adding new ones while you still have a dozen open, so the list stays something you can work through. Pro accounts get 7 recommendations with fuller action plans — suggested wording, tool names, competitive gap analysis and technical guidance drawn from your own scan data.

If you cancel your subscription, your account moves to the free tier. All of your scan history, scores, and recommendations are retained — nothing is deleted. If you resubscribe later, your full history will still be there and your trend chart will show data from before and after the gap.

Yes. Email us at support@indextr.ai with the subject line “Delete my account” and we will permanently remove all of your data within 5 business days.