Buying is decided in a layer nobody sees. We see it.

Every screenshot on this page shows the real product with demonstration data. The monitored client (Demo Brand), the competitors, the domains and the numbers are fictional. The product works in English end to end: interface, weekly report, PDF, alerts and CSV export.

• ~1.2×

  Visitors arriving from AI convert above organic search. And AI-driven conversions grew +6,432% in a year.

• -58%

  The click on Google's first position drops to less than half when an AI block sits on the page. The sale gets decided inside the answer.

• 62%

  Of the brands in a first answer vanish at the buyer's second question. Whoever survives the follow-up keeps the shortlist.

Sources: NetElixir 2025 · Ahrefs, 300,000 keywords, Feb 2026 · Clovion, 69,120 B2B conversations, 2026. Your brand's own number is the one we measure: answer to visitor, before and after every action.

Running the models is the easy part. The rest is the stack.

Any tool can ask a model questions. Periscopy runs ten collection and analysis systems crossing into the same weekly read, and that depth is what cannot be copied in a weekend.

• 01 · AUDIT ENGINE

  Eleven engines and surfaces, two modes per engine (model memory vs live web search), every week, with full history. Two numbers, not one: share of voice, which divides the mentions, and share of recommendation, which divides the choices. Being on the list and being the answer are counted apart.

• 02 · PRESS, COMMUNITY AND SOCIAL MONITOR

  The press read every day, plus Reddit with comments, Hacker News, local forums and the networks (YouTube, LinkedIn, Instagram, TikTok, X), in the rooms that matter for your brand. Every mention classified by relevance and sentiment, and cross-checked against what the engines cited: it separates noise from sources that decide purchases.

• 03 · CRAWLER ANALYSIS

  The AI robots (GPTBot, ClaudeBot, PerplexityBot) visiting your site, cross-referenced with your visibility in answers. You watch the machine read you before it cites you.

• 04 · SOURCE GRAPH

  Which domains feed your category's answers, with co-citation, down to the exact place inside the platform: the subreddit, the channel, the profile, the review page. We never say “get on Reddit”; we name the room, with the count of answers it fed.

• 05 · ENTITY ENGINE

  Wikidata, Knowledge Panel, schema, sameAs: how machines identify you as an entity. The layer that decides whether models retain you in memory.

• 06 · COMPETITOR RADAR

  A dossier per competitor: where they appear, which sources feed them, moves, observed pricing, and the presence × narrative perception map.

• 07 · COMMERCE OBSERVATORY

  The shopping carousels inside the assistants, observed the way a buyer sees them: title, brand, merchant, price, rating, position and the sponsored label, item by item. What no API shows, seen through the buyer's eyes.

• 08 · PROOF PER ACTION

  Every completed action gets a date and a before/after citation reading. The plan is not a task list: it is a closed loop with measurement.

• 09 · OPPORTUNITY ENGINE

  A proprietary intelligence layer reads every answer of the week and turns gaps into a plan: each opportunity is born from a measured source, mapped to the 8 SINAL dimensions and 4 horizons, with severity and effort.

• 10 · PREDICTIVE MARKET MODELS

  Our systems learn from the data we collect every week: they record sources, cross layers, and detect patterns before they become trends. That is where the insights on unclaimed positionings come from: recommendations that are in no playbook yet, because they are born from your market.

Periscopy is not a dashboard. It is an intelligent agent working for your brand.

Every week, without being asked: it measures, reads, explains, decides what matters and prepares the pieces, with one goal: more buyers choosing you when they ask the AI. Ten things it does that you will not find in another product:

• Explains every answer

  Every answer carries its written why: why it cited you, or cited the competitor and not you, with the evidence of that answer (the sources, the route, who appears). Not a score; the reason.

• Splits your business lines

  Visibility broken down by your lines: the emergency-care question never mixes with maternity, nor the fuel station with the energy plan. Rate per line, who dominates each one, and where you are losing revenue blind.

• Checks the facts

  What the AI claims about you, checked against your recorded facts: prices, addresses, features, terms. A detected divergence becomes an actionable correction before a buyer reads it.

• Measures by persona

  The questions are not generic: each one goes out framed as a persona in the funnel, the decision-maker, the technician, the local buyer, at their stage. Visibility reads per persona, and segment focus gets decided through that lens.

• Sets the target, and names the path

  Pick the question that matters to you and declare what you want to change in the answer: be named, be the pick, or be tied to a theme. The agent says what to do from what is measured in that answer: the sources that engine read, and the words the buyer searched for. The starting point is kept from that day, and the next measurement says whether anything moved.

• Declares what you want the AI to say

  A target on one question serves one question. Some things run across thirty: the discount you want tied to a whole category, the guarantee that sets your offer apart, the argument that never shows up. Declare it once, apply it to the questions it serves, and the agent works towards it. With no public proof behind it, the first step is to write that proof: an engine is never asked to state what is not evidenced.

• Shows who wins in each engine

  Not only the competitors you declared: every brand each engine picks, including the ones nobody has classified yet. It is where the market moves in plain sight, because the brand entering your category shows up here weeks before anyone gives it a label.

• Hands over finished pieces

  Every action in the plan can ship as the final piece: the corrected copy, the structured-data block, the outreach email with its subject line. Your team applies; it does not decipher.

• Knows your industry

  Every piece of advice starts from your market: what changed in your industry this week (prices, launches, regulation, campaigns), the sources the engines cite most in it and the words buyers search with. Not advice about AI search in general; advice about your market.

• Writes the copy

  In the Studio you pick the type of copy (a website article, a LinkedIn article or post, an FAQ, a service page, or a rewrite of a page you already have) and the subject: the questions it should win, or a topic where you see an opportunity. It comes out ready to publish, in your brand's voice, from what you sell, what is happening in your industry and who the engines cite on each measured question. A number we do not know is left marked for you to fill in, never made up.

We measure where your buyers actually ask.

• Two routes per engine

  Training memory (what the AI knows about you without the internet) and live web search (what it answers when it searches). The contrast between the two tells you whether the problem is the brand entity or presence on the web.

• Buyer questions

  The questions a buyer actually asks, put to the engines in the voice of a persona (CEO, CMO, technical decision maker) and by decision stage. The persona is a framing we write and send ahead of the question. The same question also runs with no persona at all, to measure how much the persona changes the answer.

You see it in a live panel, not a monthly PDF.

• Every answer, kept

  Each answer from each engine, stored by week, with citation, position, tone and the competitors detected in that answer.

• Next to your traffic

  Search Console, AI bot visits to your site, and a correlation panel between visibility and traffic, side by side.

• Reporting

  Monthly PDF report and a weekly email digest, with the highlights and one action for the week. CSV export of everything.

Your competition, mapped in detail.

• Named and classified

  Every name the AI mentions is classified: direct competitor, tool, or media. We do not count an SEO tool as a rival of yours.

• A dossier each

  Which engines cite it, the exact sources feeding those citations, the questions where it appears and you do not, real excerpts of how the AI describes it, and the share of voice trend, week by week.

• What it is doing

  Services it announces, who it sells to, content themes, channels where it is active (blog, LinkedIn, podcasts, press, reviews) and recent moves. Facts with a source, nothing else.

We tell you where there is room to win.

Not everything is taken. Part of the questions and sources in your category have no owner yet. Periscopy finds that territory and tells you when it changes.

• Unowned questions

  Where the AI still recommends nobody. Whoever arrives first with quotable content takes the answer. Buying-intent questions are flagged as priority.

• Unowned sources

  The domains the engines cite in the category where no competitor dominates: the cheapest way in.

• Alerts

  When a competitor enters a question that was yours, when a new name appears in buying questions, or when an open question finds an owner.

We close the loop: from analysis to proof.

• A brief per question

  Every open question has an attack button: it generates the brief of the content that can win it, with title, structure, and the sources where to plant presence.

• Eight dimensions, four horizons

  Every gap tied to a concrete action, with severity and effort estimated. Appearing is not just a website problem, so the plan is not just technical.

• Before and after

  Each completed action is dated, and the panel shows citation before and after it. Results measured, not promised.

Measurement tells you where you are. Here you declare where you want to be.

A supermarket that wants its discount mentioned, a consultancy that wants to be named when someone asks about price: that does not belong to one question, it belongs to a subject. You declare it once and it holds for every question on that subject. The following week the measurement says whether it started being said, with the sentence that proves it.

The starting point is frozen. It is read the day you declare it, not the day you go and look at the result. Otherwise the before moves with the after and the movement disappears.

With no public proof, writing it is the first step. We never ask an engine to assert what is not published. With the piece in place, the work is getting the engine to it; without it, the work is a different one, and the plan says which.

A claim nobody has read yet shows as unmeasured. Not as zero. They are different things and they lead to different work.

Your site, read the way the AI reads it.

Beyond measuring where you are cited, Periscopy audits what the engines find when they reach your site: the foundation once, and then page by page, with no practical ceiling. A site of 2,000 pages is analysed in rounds that continue on their own.

• The foundation

  Robots, llms.txt, structured data, entity. Each signal opens and explains itself: what it is, whether it is yours to fix or depends on a third party, and the correction already written.

• Two scores per page

  Technical (can the crawler read it) and answering (does it answer what it promises), with the concrete problems and the fix for each.

• Patterns, not noise

  What repeats across the site is aggregated. One duplicated title across 500 pages is a template problem, fixed once.

• Products agents can read

  If you sell online there is one more layer. A shopping agent reads price, stock, delivery time and returns from your data, not from the page. We measure the fill rate across a sample spread over the whole catalogue, then product by product. In a catalogue of 10,000 items what counts is not the one lucky page, it is the percentage, which is where Merchant Center fails you.

Software and local brands.

• Digital

  SaaS, software, platforms, sites and e-commerce. When the buyer asks the AI about the category, you want to be one of the brands that appears.

• Local

  Clinics, restaurants, tourism and retail. When someone asks for the best option in the area, your reputation and your Google listing decide whether you make it into the answer.

The same question changes answer depending on who asks it.

A technical director and a finance director do not ask the same thing about the same product, and AI does not answer them the same way. Asking “what is the best X platform” without saying who is asking measures an average that describes no real buyer.

The concept: a synthetic persona

A synthetic persona is a buyer written out in full and used as a variable in the measurement. It goes in front of the question, so the assistant answers as it would answer that person, rather than nobody in particular.

It is not a slide persona. A marketing persona lives on a deck and changes nothing; a synthetic persona is executable: it changes the question that goes out, and therefore the answer that gets measured. Two personas on the same product produce two different measurements, and the gap between them is the information.

• Role and segment

  Whether it is B2B or B2C, and which side of the table they sit on.

• Context

  The sentence that goes in front of the question.

• Goals

  Feeds the generic and feature questions.

• Pains

  Feeds the comparison and objection ones.

• Decision criteria

  Where the choice is played out.

• Vocabulary

  The words THEY use, which are not the brand catalogue's.

The last field is the one most people forget. A brand describes itself in its own vocabulary; the buyer searches in theirs. Where the two do not meet, the brand does not show up, and it is not for lack of content.

An incomplete persona is a label, and the product says so. Every profile shows how much of it is filled in. A persona with only a name changes nothing in the measurement, and presenting it as though it did would be selling a reading that does not exist.

The limit, written down because it is honest: a synthetic persona is a hypothesis about a buyer, not the buyer. It does not replace talking to customers. What it does is make the measurement conditional and comparable: instead of an average that describes nobody, a result per profile, which can be argued with and corrected because it is all written down.

Before answering, AI runs its own searches.

When somebody asks “which GEO consultancy do you recommend in Lisbon”, the assistant does not go looking for that sentence. It breaks it into the questions it thinks it needs to answer first, searches each one, and only then writes. That middle step is the most actionable thing in this measurement, and almost no tool shows it.

Three things you only see here

• The words it searched with

  If the question was about price and it searched for pricing table and how much per month, the page missing from your site has a name.

• In how many sub-questions it found you

  A question can be split into four. Appearing in one of the four is not the same as not appearing, and you know which one.

• Who is in your place in the others

  For every sub-question where you are absent, the domains it read instead of yours. That is the list of pages to write, in order.

The engine searches for brands by name before it knows what it will find. On another question that same week, about proven case studies, Gemini ran nine searches and six of them named a specific brand. That is the candidate list it already carries. Being on it is a different measure from being cited, and it comes first: what is never searched for cannot be found, and no work on the page fixes that.

Markets slip. On the same pricing question, ChatGPT ran a single search and it ended in “preço Brasil”. On a Portuguese question, that pulls competitors from another market into the answer your buyer reads.

Honest note: not every assistant declares this step. Where it is not declared, Periscopy says it did not see it, rather than counting zero.

If AI always searches the same way, there is a door. If it changes words, there is a market.

Week after week, the internal searches either repeat or they do not. The two mean opposite things, and both are actionable. If it converges on a handful of sources and terms, being in those terms is a finite job with an end in sight. If it brings vocabulary from outside your sector, the category has no owner yet: that is a window, and windows close.

The last line is the one that changes conversations. “We do not show up” and “we show up, it read the page, and it picked someone else” call for opposite work. The first is presence; the second is the page failing to convince, which is the most expensive problem and the easiest to hide.

The thresholds for what counts as much or little repetition do not live in the code: they live in the method, and they change when the measurement forces them to. What the product does is count; the reading is kept separate on purpose.

Being on a list of ten is not being the answer.

Almost every AI visibility measurement counts mentions. A mention can be your name in the middle of a list, and it can be the sentence “and the best of these is X”. Counting both the same way erases the one difference that matters to whoever is selling.

• Citation rate

  Present, or not. One answer, one yes or no.

• Share of voice

  The mentions in the category. Being one of three is worth more than one of twelve.

• Share of recommendation

  The choices in the category. Only answers where the assistant picks somebody count.

The denominator for choice is the answers that pick somebody. An answer that explains, lists and compares without picking has no pie to divide, and stays out. All three metrics use the same scale on purpose: two numbers read side by side have to be comparable.

Three real answers, and what each one is worth

These are answers about destaque.ai, measured by Periscopy itself. We use our own because the ruler we apply to others has to apply to us. The excerpts are translated; the originals are in Portuguese and unedited.

The criterion is not invented per client. It has been fixed in writing since the 616-answer study that produced it: a place in an ordering counts as a choice, so does a verdict on a criterion naming one brand, or the closing sentence. Belonging to the set (“the big three”) does not count, nor does a niche superlative. When in doubt, it does not count.

The distinction is no longer only ours. Marketeer, a Portuguese marketing publication, ran the study on 3 September 2026 using the same pair of words, under the headline “EDP is the Portuguese brand most chosen by AI”.

Read the study →

The report also reads inside your Claude or your ChatGPT.

Once connected, “what does my brand have to do this week” is answered from the report, not made up. Four tools, all read-only: the assistant reads what we measure and changes nothing.

How to connect. In Claude’s connectors, as a remote MCP server, with the address https://tracker.destaque.ai/api/mcp. Sign in with your Periscopy account, no key to paste, and each connection sees one brand only.

Your whole portfolio, under your brand.

Periscopy was built to measure several brands at once. An agency gets its own account, puts as many clients in it as it likes, and everyone on the team sees the whole portfolio. Clients of one account never show up to anyone outside it.

And the model is that the tool becomes yours. Not a report with our name on it: the whole product, with the agency’s logo, your house colours, the domain people log in through and the address the emails come from. Whoever opens the dashboard sees the agency. The measurement is ours; the tool in front of it is yours.

• Each client on its own

  Every brand has its own questions, its own competitors and its own history. One brand’s measurement never leaks into another’s numbers.

• Reports to send on

  The monthly report comes out as a PDF carrying the agency’s logo and the measured brand’s, ready to hand to the client.

• Logo, colours and domain

  Upload the logo, pick the colours, and the dashboard opens on the agency’s own domain. Whoever logs in to read the numbers sees the agency, not us.

• Or as a service

  Some agencies want the measurement and nothing else. Others would rather we read the numbers and carry out the fixes. Both are available, and the conversation starts in the same place.

Straight answers.