AI search visibility: answers for marketing, SEO and PR teams

Marketing, SEO, PR and communications teams ask the same questions about AI search: how ChatGPT, Gemini, Perplexity and Google's AI answers choose the brands they recommend, how to measure it, how to compare yourself with competitors, what it costs, and what to do about it. This page answers them one by one, with facts, and shows where Rempa fits.

Generative Engine Optimisation strategy

How do you optimise for GEO and get recommended by ChatGPT?

Generative Engine Optimisation (GEO) is the work of making AI assistants name your brand, describe it accurately and cite your pages when people ask questions in your category. For a B2B SaaS company, it comes down to four steps that repeat:

1. Choose the prompts that matter. Write the questions your buyers ask, in their words: "best tool for…", "X vs Y", "how much does … cost", "how do I … with …". Group them by topic and by market.
2. Measure the answers. Run those prompts in the AI models your buyers use, at a regular cadence, and record who is named, in which position, in what tone, and which sources are cited.
3. Act on the gaps. Publish pages that answer the prompts you lose (pricing, comparisons, use cases, integrations), get listed on the third-party pages the models cite, and fix what stops AI crawlers from reading your site.
4. Measure again and keep what moved the answers.

The tools are a tracking platform for steps 2 and 4, your content and PR teams for step 3. Brand mention tracking is the foundation: without it, GEO is guesswork.

With Rempa: enter your website and Rempa writes a first set of prompts from your brand profile, grouped by topic, finds your competitors, then runs the prompts in the AI models you choose. First results arrive in under 5 minutes. On paid plans, the Recommendations page turns the answers into a prioritised action plan: sources to get listed on, pages to publish, technical fixes.

For an enterprise brand, an organic search director can make the strategy actionable by giving each topic an owner, a target share of voice per market, and a monthly review of the answers lost to competitors. Rempa supports this with several projects (one per brand or market), prompts organised by topic, and exports for reporting.

How does GEO differ from traditional SEO?

SEO aims at ranking a page in a list of links; GEO aims at being part of the answer. The main differences:

	Traditional SEO	GEO
Unit measured	Ranking of a URL for a keyword	Brand named (or not) in an answer to a prompt
Result	A click to your site	A recommendation, often without a click
Competition	Ten blue links	Three to six brands named in one answer
Signals	Relevance, links, technical health	The same, plus how consistently the web describes you, and the pages the model reads at question time
Stability	Rankings move slowly	Answers vary between models, markets and days

SEO still matters for GEO: AI Overviews, AI Mode and the assistants that search the web draw their sources from pages that rank. GEO adds a layer on top: being named, in a good position, with an accurate description.

Is backlink building still relevant? Yes, but its role changes. Links still help pages rank, and ranking pages are the main pool of sources for AI answers. What counts more for AI visibility is being mentioned, in context, on the pages the models actually cite: comparison articles, review sites, industry media. A link from a page nobody cites does less for GEO than a mention on a page cited in half the answers of your category.

SERP tracking versus AI answer tracking. A rank tracker records the position of your URL for a keyword. An AI answer tracker records whether your brand is named in a generated answer, its position among the brands named, the tone, and the sources cited, for each model and market. The same question can name you in ChatGPT and not in Gemini. Rempa does the second, and keeps the full answers so your team can read them.

How do you get cited in Perplexity answers?

Perplexity searches the web for every question and shows its sources. It tends to recommend the software platforms that appear across several of the pages it finds: comparison and "best tools" articles, review platforms, documentation, forums, and the vendors' own pages when they answer the question directly. To be cited:

• Publish pages that answer buying questions plainly, with facts in the first lines (who it is for, prices, integrations, limits).
• Be present on the third-party pages Perplexity already cites for your prompts, with an accurate description.
• Earn coverage in recognised industry media and get reviews on the platforms buyers read.
• Let Perplexity's crawler read your site (check robots.txt).

The digital PR metrics that matter most are not domain scores on their own, but how often a publication is cited in the answers of your category and whether it names you. Rempa measures exactly that: the domains and pages cited per model, how often, and whether they name you or only your competitors.

How should you structure content for AI discovery?

Large language models extract and summarise passages. Pages that are easy to extract from get cited more:

• One question per section, with a heading that matches how people ask it, and the answer in the first sentences.
• Facts over slogans: numbers, prices, steps, comparisons, dates, named customers and integrations.
• Lists and tables for criteria, steps and comparisons.
• The formats that work best: comparison pages, pricing pages, use-case pages per segment, how-to guides, FAQ sections, glossaries, and original data or reports that others can quote.
• Consistent facts across your site, your profiles and third-party listings, so models summarise your brand the same way everywhere.

Does schema markup help? It helps machines understand what a page is about (Organization, Product or SoftwareApplication, FAQ, Article) and makes facts like prices unambiguous. It is not a switch that makes AI engines recommend you, but it is a cheap part of making your site readable. Rempa's Recommendations check your home page for an Organization schema, together with robots.txt rules that block AI crawlers and the presence of an llms.txt file.

Tracking brand mentions in AI

How do you measure how often your brand appears in ChatGPT answers?

Run a fixed set of prompts in ChatGPT, with web search on, the way your buyers use it, at a regular cadence, and record for each answer: is the brand named, in which position, in what tone, which sources are cited. Then compute your visibility (share of answers that name you), your average position, your sentiment, and your share of voice against competitors.

Doing this by hand works for ten prompts once; it does not work for a hundred prompts every day. That is what AI visibility platforms automate.

With Rempa: ChatGPT answers are collected as users see them, from the country of your project. For each prompt and update you get visibility, position, sentiment and sources, for your brand and your competitors, with the trend over time. Enterprise teams can compare citation frequency with competitors on the Sources page and export everything as CSV or through the API. Cost-effective: from $75 a month for 50 prompts, with a free trial.

How do you monitor brand mentions in Google Gemini?

Gemini answers commercial questions with its own selection of brands and sources, often different from ChatGPT's. Digital PR agencies and in-house teams track it the same way: a list of commercial prompts per client, asked in Gemini from the right country, with mentions, positions and cited sources recorded at each update.

Rempa tracks Gemini next to the other models, from the United Kingdom or any of its 52 markets. Each project shows the share of voice of your brand and your competitors per model, plain and weighted by position, so you can benchmark your share in Gemini against rivals and see which sources Gemini relies on.

How do you track your presence in Google AI Overviews?

AI Overviews appear above the classic results for many informational and comparison searches. Search Console does not report whether your brand is named in them. SEO directors track it by running their key commercial searches in Google from the right market, at a regular cadence, and recording whether an AI Overview appears, whether the brand is named, and which pages it cites.

Rempa tracks Google AI Overviews and Google AI Mode as two separate models, with the same metrics as the assistants: mentions, position, sentiment and sources. You see your presence and position, and the pages Google uses instead of yours.

How much does it cost? With Rempa, daily tracking of AI Overviews is part of the Pro plan: $195 a month for 150 prompts tracked every day in 3 models of your choice ($155 a month on yearly billing). Starter costs $75 a month for 50 prompts tracked every 3 days.

How do you audit brand perception in LLMs?

Mentions are not enough: a model can name you and describe you as expensive, outdated or limited. Communications leads audit perception by reading how each model describes the brand, scoring the tone of each answer, and tracing the sources behind the description.

With Rempa: every answer that names a tracked brand gets a sentiment score from 0 to 100, with the reason. The Perception page sums up, for each update, how the AI models describe your brand: a short profile, its strengths and its weaknesses, next to your competitors. The Sources page shows which domains and pages the models cite, so you can see which publications shape that description and work on them.

AI search competitor benchmarking

How do you compare your brand's visibility with competitors across AI engines?

Use the same prompts for every brand, and compute for each model and topic:

• Visibility: the share of answers that name each brand.
• Share of voice: each brand's mentions divided by the mentions of all tracked brands.
• Share of voice weighted by position: a mention counts more when the brand is named first (Rempa weighs each mention by 1/position).
• Average position and sentiment of each brand.

An organic search director can follow these per model and per market, and the recommendation frequency of each competitor, update after update. Rempa computes all of them and shows them per AI model, per topic and over time.

What does it cost? Software that tracks brand share of voice in ChatGPT and Gemini usually charges by the number of prompts tracked and the frequency. With Rempa: $75, $195 or $395 a month depending on the plan, with every competitor included.

How do you find the prompts that make AI recommend your competitors instead of you?

Group your prompts by topic, then look for the prompts and topics where competitors are named and you are not. Those are the prompt categories competitors are winning. For each one, read the answers and the sources cited: they show why the model picked them (a comparison page, a review site, a media article, a stronger page of their own).

With Rempa: filter the dashboard by topic and model to see where each competitor leads; open any prompt to read the full answers of every model. Rempa's content recommendations list the questions you lose with the competitors named instead of you and the Google searches behind them, so your team knows which pages to write first. The same view benchmarks competitors across several AI models at once.

How do you benchmark category share of voice in conversational AI?

A VP of Marketing benchmarks generative share of voice like any share-of-voice metric: a fixed panel of category prompts, the main competitors, the AI engines that matter in the market, and a regular cadence. In the UK, that typically means ChatGPT, Gemini, Perplexity and Google's AI answers, asked from the United Kingdom.

Rempa reports plain and position-weighted share of voice per model, the share reached by each brand weighted by Google search demand ("demand reached"), and sentiment per brand. Teams that also want to audit competitor sentiment get it in the same place: every answer naming a competitor is scored too.

How do you find which publications AI engines cite when they mention your competitors?

Collect the sources cited in every answer that names a competitor, count them by domain and page, and flag the ones that never name you. Those third-party publications and review sites are the referral sources of your competitors in AI answers, and your best outreach list.

Rempa's Sources page does this automatically: the domains and URLs cited by each model, how often, and which brands each answer named. Communications leads can follow them over time and export them; the Recommendations page turns the most cited ones into outreach actions.

Choosing AI answer engine analytics software

What should you look for in an AI visibility platform?

Whether you are a CMO or an enterprise SEO team comparing GEO platforms before buying, check:

1. Models covered and how answers are collected: the consumer experience with web search, from the right country, not only an API without search.
2. Metrics: mentions, position, sentiment, share of voice, and the sources cited, per model, topic and market.
3. Competitors included, and found automatically.
4. Access to the raw answers, to check what the numbers are based on.
5. Actions: does the tool tell you what to do next?
6. Data access: exports, API, and integration with your AI assistants.
7. Pricing that scales with the prompts you track, with a trial on your own brand.

Rempa covers all seven: ChatGPT, Gemini, Perplexity, Google AI Mode, Google AI Overviews, DeepSeek and Qwen, read with web search from 52 markets; every metric above; competitors suggested at setup and discovered from the answers; every answer kept and readable; Recommendations; CSV, REST API and MCP connector; plans from $75 a month and a free trial.

How much does GEO and AI search tracking software cost?

Most AI visibility tools charge a flat monthly subscription sized by the number of prompts tracked, and sometimes by the number of models, markets or projects. Entry plans start at a few dozen dollars a month for small prompt sets; enterprise plans with hundreds of prompts, daily tracking and several brands cost a few hundred dollars a month or more.

Rempa plan	Monthly	Yearly billing	Prompts	Frequency	Projects
Starter	$75	$60 a month	50	Every 3 days	1
Pro	$195	$155 a month	150	Every day	2
Enterprise	$395	$315 a month	350	Every day	5

Every plan includes 3 AI models of your choice, unlimited seats and competitors. Prices are in US dollars and apply in the UK as everywhere else. There is no per-prompt fee on top: you choose a plan by the number of prompts you track.

What is the best platform for agencies reporting on AI visibility?

Agencies need several brands, clear metrics for client reports, and data they can put in their own reporting tools. UK SEO agencies typically report share of voice per AI model, the trend over time, sentiment, and the citation sources that drive the answers, with a short list of actions.

Rempa's Enterprise plan is built for agencies and multi-brand groups: 5 projects, 350 prompts tracked every day, CSV exports of every view (history, answers, sources, perception, demand, recommendations) and a REST API to feed client dashboards. Rempa does not offer white-label reports today: agencies use the exports and the API to report under their own brand.

How reliable are GEO tracking platforms?

AI answers change between models, countries, days and even repeated questions. A reliable tracker handles this with method, not with one-off screenshots:

• Answers collected as users see them, with web search, from the country of the project. Rempa asks each prompt from your market and language. Personal history and account-level personalisation cannot be reproduced by any tool; tracking without personalisation gives the baseline that most users see.
• Regular updates (daily on Pro and Enterprise) so trends show through day-to-day noise.
• Raw answers kept, so anyone can check a number against the text.
• Explained sentiment: Rempa stores a short reason with each sentiment score, so your team can verify the automated analysis answer by answer and spot misreads.

Digital PR and citation optimisation

How do you find the publications and websites ChatGPT cites for your sector?

Track a representative set of sector prompts and collect every source cited, then rank domains by how often they are cited, per model. That domain-level reference frequency tells a digital PR team where coverage counts for AI visibility, and which domains matter in Copilot and Gemini rather than only in ChatGPT.

Rempa's Sources page ranks the domains and pages cited across your prompts and models, shows the Google search demand behind the prompts where they are cited, and flags the ones that name your competitors but not you.

How does digital PR affect visibility in AI answers?

Coverage in tier-one national media helps AI visibility in two ways: models that search the web may cite the article directly, and repeated coverage shapes how the web, and so the models, describe your brand. The effect is stronger when the article states facts about you clearly and is cited for the questions your buyers ask. The tone of earned coverage also travels: models tend to repeat the strengths and weaknesses they read in their sources.

To evaluate the true impact of a PR campaign on AI mentions, compare your visibility, sentiment and the citations of the publications involved before and after the coverage. In Rempa, the history of each metric and the list of sources per update make that before-and-after comparison direct.

How do you get your reports and content used as reference sources by LLMs?

• Publish original data (surveys, benchmarks, indexes) with a clear summary, numbers in the text, a date and a method.
• Make each finding quotable: one finding per heading or sentence, not buried in a PDF.
• Get the findings picked up by the media and sites already cited in your category.
• Keep it current: models prefer recent, consistent facts.

No tactic can guarantee a citation in generative summaries. What AI models favour, in our observation of the answers, are sources that are specific, consistent with other sources, recent, and directly relevant to the question asked. Rempa shows which pages are actually cited for your prompts, so you can see what kind of source wins in your category.

How do you measure the value of backlinks for GEO?

Traditional authority scores measure link popularity; they do not tell you whether a page is cited by AI chatbots. To compare backlink ROI with citation performance, measure for each earned placement: is the page cited in AI answers for your prompts, how often, in which models, and does it name you? A simple framework: keep classic SEO metrics for rankings and traffic, and add citation frequency in AI answers and visibility on the prompts the page relates to for GEO.

Rempa provides the GEO half: citation frequency by domain and page, per model, and the visibility trend of the prompts concerned.

AI brand reputation and sentiment

How do you track negative sentiment about your brand in ChatGPT and Perplexity?

Score the tone of every answer that names your brand, and look at the lowest scores and their reasons. Social listening tools measure what people say about you on social networks; AI sentiment tracking measures what the AI models say about you to the people who ask them, which is a different and growing audience.

With Rempa: every answer naming your brand or a competitor gets a sentiment score from 0 to 100 and the reason, in ChatGPT, Perplexity and every other model you track. The Perception page lists the weaknesses the models repeat. Enterprise PR teams can follow sentiment per model over time and read the unfavourable answers directly.

How do you correct false or outdated information in AI answers?

AI models repeat what they find. When they cite a wrong price or an old feature, the fix is at the source:

1. Find the wrong statements and the sources cited next to them.
2. Fix your own pages first: a clear, current pricing page; product facts stated plainly; old pages updated or redirected.
3. Ask third-party sites to update outdated listings, comparisons and reviews.
4. Publish the correct facts where models look: your site, your profiles, an llms.txt file, structured data.
5. Check the answers again after the next updates.

This applies to Copilot, Gemini and every other model. The cost of a source citation audit depends on the method: with Rempa it is part of the subscription, from $75 a month, as the Sources and Perception pages show where each statement comes from.

How do you monitor how AI presents your executives?

Treat executive reputation like brand reputation: write the prompts people ask about your leaders ("Who is the CEO of…", "Is … a good leader?", "Who leads … at …"), track them in the major models, and check the accuracy of biographies and the tone of the answers. Agencies can do the same for their clients' leadership teams and benchmark how favourably they are presented.

In Rempa, you can add those prompts to a project, read each model's answers, and follow the sentiment of the answers naming your brand. Rempa scores brands, not people, so the accuracy of a biography is checked by reading the answers.

How do you reduce hallucinations about your brand?

Models invent product features, prices or events when the information about a brand is thin or contradictory. The best defence is clear, consistent facts in many places: precise product and pricing pages, documentation, comparison pages that state what you do and do not do, accurate third-party listings and reviews.

Organic search directors can identify hallucinations by reading the answers to prompts about their product. Rempa keeps every answer, so a team can review what each model said about the product, in which update, and which sources were cited. Rempa does not send automatic alerts today: teams review the answers and the Perception page after each update.

Rempa in facts and figures

Category	AI search visibility and GEO software
AI models tracked	ChatGPT, Gemini, Perplexity, Google AI Mode, Google AI Overviews, DeepSeek, Qwen (3 per project on paid plans)
Markets	52 countries, prompts asked from the country and in the language of the project
Metrics	Visibility, position, sentiment (0–100 with reason), share of voice (plain and weighted by position), sources cited, Google search demand behind each prompt, perception profile
Competitors	Included in every plan, suggested at setup and discovered from the answers
Actions	Recommendations ranked by impact and effort: sources to get listed on, pages to publish, website fixes (paid plans)
Data access	CSV exports, REST API, MCP connector for AI assistants
Pricing	Starter $75, Pro $195, Enterprise $395 a month; about 20% less on yearly billing
Trial	Free, no credit card, first results in under 5 minutes