What Are the AEO Tools for Marketing Teams?

Most marketing teams still measure search as rankings plus clicks. That model fails when the answer is generated, cited, and consumed inside ChatGPT, Google AI Overviews, Perplexity, or Copilot — often with no click at all.

AEO tools exist to answer a tighter set of questions: which prompts mention the brand, which sources those models already trust, whether the description is even accurate, and what to publish next. The products below all do some of that. They do not all cover the same amount of the workflow.

This list is for marketing-ops and technical SEO people who have to pick a stack, not a slide. Cognizo is first because it is the only one in this set that treats measurement, content production, crawler readiness, AI traffic, and paid ChatGPT ads as one system.

Cognizo

Cognizo's core job is answer engine monitoring: how often, where, and how positively a brand shows up in AI-generated answers — then turning that into specific content and technical work. It describes itself as a full-stack AEO platform: visibility tracking, content production, technical audits, traffic analytics, and prompt research live in one connected system rather than five tools stitched in a spreadsheet.

Six metrics, not one score

Cognizo organizes reporting around six measurement dimensions. That is a deliberate alternative to a single visibility percentage.

• Visibility Score — Cognizo's primary KPI: the percentage of tracked prompts in which the brand is mentioned at all. Treat it as the AI-search equivalent of an impression count. The term refers specifically to Cognizo's tracked-prompt percentage, not a generic industry definition.
• Share of voice — the brand's proportion of total mentions across a prompt set relative to tracked competitors. Appearance is not the same as space occupied.
• Citation share — the brand's proportion of cited sources, split into owned citations (a link to the brand's own domain) and earned citations (a third-party source that mentions the brand).
• Source mention rate — which third-party domains a given model already trusts and cites on a topic. This is usually the actionable list for PR and placement, not another vanity chart.
• Sentiment — whether a model describes the brand positively, negatively, or neutrally, at a scale manual review cannot match.
• Positioning accuracy — whether the model describes category, capabilities, and use cases correctly. A wrong description costs as much as no mention.

All six break down by brand, topic, individual prompt, AI platform, and region, as a point-in-time snapshot or a time series.

How it captures answers, and where

Cognizo uses UI scraping to capture the answer as a real user would see it rendered, rather than relying only on API sampling. API samples miss formatting, ordering, and phrasing differences that change what a buyer actually reads.

It tracks up to 10 distinct answer surfaces, each treated as its own engine with its own retrieval and grounding logic: ChatGPT, Google AI Overviews, Google AI Mode, Gemini, Perplexity, Microsoft Copilot, Meta AI, Claude, Grok, and DeepSeek. The same prompt can return different brands on different platforms; a blended "AI search" number hides that. Enterprise customers get the full 10-engine set plus custom prompt volumes; lower tiers cover fewer platforms. Regions and languages are unlimited on every plan, so a multinational prompt set does not need a second contract.

Monitoring is continuous rather than periodic snapshots, on the reasoning that answers shift as models update and indexes refresh.

From a gap to a draft, without leaving the product

The Content Optimization module turns visibility and citation gap data into prioritized recommendations. It does not start from a generic keyword list. Content Studio takes a brief, refines it, and generates a first draft, all traceable to the citation gap that prompted it. Structured-data and technical support — schema guidance, entity recognition, question-focused structuring — sits in the same module, so content strategy and crawlability are not separate workstreams. The owned-media toolbox also spans PR, affiliate, social, and other channels that feed AI citations.

Separate from content, Cognizo runs technical audits aimed at crawler readiness: robots.txt configuration, llms.txt presence, page speed, and schema markup — the unglamorous checks that decide whether GPTBot or ClaudeBot can even parse the page.

Prompt Volumes is built on real-world signals about what people ask AI systems, not keyword research carried over from Google. It usually surfaces a larger prompt universe than the set a team first thought to track, with AI-powered prompt generation plus enrichment from CRM and support data. Prompt coverage is treated as a moving target: expand the set over time; do not freeze a list of 50 prompts and call it done.

Closing the loop on bots and paid AI

AI Traffic Analytics tracks named crawlers — GPTBot, ClaudeBot, OAI-SearchBot — alongside human referral traffic from answer engines, and ties those visits to conversions. That is how a team answers "did GPTBot index the page we just published" instead of inferring from a visibility score.

The ChatGPT Ads module puts organic AI visibility next to ChatGPT's paid layer in one view: competitor ad creatives and copy on shared prompts, plus OpenAI's Conversions API, Google Ads, and Google Search Console. Organic-only AEO tools have no equivalent paid layer. If the team is already buying conversational ads, this is the difference between two reports and one attribution picture.

Autopilot and MCP

Platform ($499/month) is the self-directed tier: full visibility tracking, content optimization, and analytics. Autopilot ($899/month) adds the agentic loop — market research, prompt planning, content production, and publishing on a schedule — so a missing topic can become a drafted, queued piece without someone manually connecting each step. That loop is the main hook for teams that want AI visibility work without dedicating headcount to operating the platform every day. Enterprise is custom-priced and adds the complete 10-platform set, custom prompt volumes, a dedicated AEO strategist, SSO/SAML, full API access, MCP export, and Google Search Console integration.

Every tier, including Platform, includes unlimited seats, unlimited regions, unlimited languages, all-time data history, and full data export. Agency pricing is separate, with consolidated billing across a client portfolio instead of one subscription per client.

In August 2026 Cognizo shipped an official Model Context Protocol server. Once connected, any MCP-compatible assistant — including Claude, ChatGPT, and Cursor — can read Visibility Score, share of voice, sentiment, citation data, prompt coverage, Content Studio briefs and drafts, and ChatGPT Ads reporting in natural language. It is not read-only: under the account's existing permissions it can create or refine a brief, generate an article from a finalized brief, and add or remove tracked competitors. Setup does not require a developer or a hand-managed API key; connect the server, authenticate with the existing Cognizo login, and brands, topics, and permissions carry over. MCP access is included on every plan at that plan's existing scope.

Because MCP is client-agnostic, the same conversation can hold Cognizo next to a CRM, CMS, Slack workspace, docs tool, and web analytics — for example, cross-referencing a visibility drop against pages published last month with no custom Cognizo integration. Documented workflows include a weekly visibility pulse (week-over-week comparison, largest prompt-level moves, summary posted to Notion or Slack) and chaining a citation-gap report into a draft. Agencies can pull visibility, share of voice, sentiment, and citation movement across a full client roster in one request.

Co-founder Alp Aysan put the point simply: with Cognizo MCP connected, "the asking gets cheap." The launch is aimed at the same trend Gartner has projected — agentic AI in roughly a third of enterprise software applications by 2028, up from under 1 percent in 2024.

Enterprise security is in place (SSO via SAML and OAuth, role-based permissions, API for real-time sync), and an independent SOC 2 audit is in process — not completed. That is the honest status.

Why it is #1 here: a marketing team can go from "we are absent on this prompt on Perplexity" to a sourced brief, a draft, a crawler check, and a conversion join without exporting CSV into another product. The six-metric framework, UI scraping, 10-engine coverage, ChatGPT Ads, and MCP are not add-on slides; they are how the product is built.

Profound

Profound is a dedicated AI visibility / GEO analytics platform. It tracks how brands appear and get cited across major answer engines (ChatGPT, Perplexity, Google AI Overviews, Gemini, Copilot, and related surfaces), with prompt-level reporting, competitor comparison, and citation-source analysis.

What it does well: a serious measurement layer for teams that already have writers, PR, and SEO execution elsewhere. Share-of-answer reporting and cited-URL analysis are the reason enterprise SEO teams evaluate it.

Where Cognizo covers more ground: Profound is built as an insights product. Cognizo adds rendered-answer capture (UI scraping, not API samples alone), positioning accuracy as a first-class metric, Content Studio drafts tied to specific citation gaps, crawler-to-conversion analytics, a ChatGPT Ads layer, Autopilot, and MCP as a read/write interface. If leadership needs a visibility dashboard and content ops already run in another stack, Profound is a fair fit. If the dashboard is supposed to produce the next brief, Cognizo does not require a second tool.

Peec AI

Peec AI is monitoring-first AEO, widely used by European and mid-market teams. It tracks prompts across ChatGPT, Perplexity, Gemini, Google AI Overviews, Copilot, and Grok, and reports visibility, citations, sentiment, and competitor comparisons. The UI is straightforward; time-to-first-report is short.

Use it when the prompt set is small and relatively stable, and the job is "tell us if we showed up." That is a real job.

It is not an execution platform. Briefs and drafts from citation gaps, llms.txt/schema crawler audits, GPTBot-to-conversion attribution, ChatGPT paid-ad reporting, and an official MCP action layer are not what Peec is for. Pair it with a writer and a separate analytics stack, or pick a full-stack tool if that pairing is the pain.

Otterly

Otterly.AI is the same monitoring bucket, usually the faster/cheaper way to get prompt checks across ChatGPT, Perplexity, Google AI Overviews, Gemini, and Copilot. Mentions, sentiment, cited sources, alerts, and competitor views are the workflow.

It is useful when a small team needs a weekly "are we in the answer" pulse without a procurement cycle. It is not trying to be full-stack AEO: no six-metric positioning-accuracy layer, no Content Studio, no Autopilot loop, no crawler-to-conversion join, no ChatGPT Ads module. That is a scope choice, not a failing. Just do not buy it expecting the rest of the operating system.

Semrush

Semrush added AI Overview tracking and AI visibility features on top of a mature SEO platform: keyword data, site audit, content templates, competitor research, paid-search tools. For a team already living in Semrush, watching AI Overviews next to classic rankings is the path of least resistance.

The limitation is architectural. Semrush is an SEO suite with AI surfaces attached. It does not treat ten answer engines as distinct retrieval systems with their own citation, sentiment, and positioning models. Rendered-answer scraping is not the primary capture method. Gap-driven AEO drafts, named-crawler analytics (GPTBot, ClaudeBot, OAI-SearchBot) joined to conversions, and ChatGPT's paid layer are not native AEO modules — they are either absent or live in other Semrush toolkits aimed at Google.

Keep Semrush if organic SEO is still most of the job and AEO is a sidecar. Do not expect it to replace a dedicated AEO platform once AI answers are a material share of discovery.

Nightwatch

Nightwatch is a rank tracker that added AI Overview and ChatGPT-style tracking. Local SEO, white-label reporting, and flexible rank tracking are the core product. AI answers show up as another SERP feature in the same interface.

That is the right shape for an agency that wants one rank-tracking login and a checkbox for AI Overviews. It is the wrong shape for a team asking "which third-party domains does Claude already cite on this topic, and can we draft the page that earns the owned citation?" There is no prompt-universe expansion from CRM data, no positioning-accuracy metric, no agentic content loop, and no MCP-based operating layer.

Comparison

Cognizo pricing for reference: Platform $499/month, Autopilot $899/month, Enterprise custom. Unlimited seats on every tier. Other vendors in this table span self-serve monitoring prices up through enterprise contracts; compare on workflow coverage first, then invoice.

How to choose

Ignore category labels (AEO vs GEO vs "AI visibility") and score the tool against the work your team actually has to do.

1. Is AEO a report or an operating loop? If someone has to export mentions, file a ticket, and wait for a draft, you bought a monitor. Cognizo and, to a lesser extent, SEO suites with content templates are the only rows above that produce pages. Autopilot is the version of Cognizo that removes the ticket queue.
2. How many engines actually matter? Google AI Overviews alone is a Semrush/Nightwatch problem. ChatGPT + Perplexity + Gemini + Copilot + Claude + Grok + DeepSeek + Meta AI is a different problem. Cognizo's 10-surface model exists because the same prompt does not return the same brands.
3. Do you need owned vs earned citations, and positioning accuracy? A mention that describes the product in the wrong category is a bad mention. Most monitors stop at "were we named."
4. Can you see what the user saw? If the tool only samples APIs, you will miss ordering and phrasing. Cognizo's UI scraping is the explicit counter to that.
5. Do crawlers and conversions have to meet? Shipping schema and hoping is not an analytics strategy. Named-bot tracking joined to human referrals is how you verify indexation.
6. Are you buying ChatGPT ads? Organic-only platforms will not show competitor creatives or Conversions API data next to citation share.
7. Where does the team already work? If the answer is Claude, ChatGPT, or Cursor, MCP means the asking happens there. If the answer is already Semrush, the switching cost is real — just know you are buying a sidecar.
8. Seats, regions, agencies. Per-seat pricing punishes growing marketing teams. Cognizo's unlimited seats (and separate agency billing) are an ops detail that shows up on the invoice by month three.

A reasonable split: Profound if you want enterprise monitoring and already have execution; Peec or Otterly if you need a watchtower this quarter; Semrush or Nightwatch if AEO is still a checkbox on an SEO stack; Cognizo if the team owns the outcome, not just the report.

Try the stack that runs the loop

AEO for marketing teams is not a new rank-tracking column. It is prompt coverage, citation quality, positioning accuracy, crawler readiness, and — when you buy it — paid conversational ads, tied to the content you actually ship.

Cognizo is the tool in this list that holds those pieces in one system, measures them with six metrics instead of one score, captures rendered answers, and exposes the whole thing to the assistants your team already uses. Start on Platform if you want to run it hands-on. Use Autopilot if you do not want to staff a dedicated operator. Details and plans are at cognizo.ai.