The six AEO tools worth paying for in 2026: Peec for share-of-answer tracking, Otterly for citation auditing, AthenaHQ for prompt-portfolio management, Profound for enterprise dashboards, Rankscale for content-gap analysis, BrandRank for sentiment and mention attribution. We use Peec daily at LoudFace, 75 prompts across 9 tags. Below: what each does, who it's for, and the honest tradeoffs.
TL;DR: The best AEO tools for B2B SaaS in 2026 split into three jobs. For share-of-answer tracking (how often AI names you), run Peec, AthenaHQ, or Rankscale. For citation intelligence (which exact URLs the engines pull), run Evertune, Otterly, or Profound. For enterprise reporting across many brands, run Profound, Conductor, or Evertune. We run Peec daily at LoudFace across 75 prompts. Below: 10 tools scored on a fixed rubric, real pricing verified June 2026, and the honest tradeoffs.
I run LoudFace, an agency that builds integrated SEO + AEO programs for B2B SaaS. We are tool-users, not tool-sellers. We re-evaluate this stack every quarter and drop anything that does not earn its line item. This list is ranked on capability. Nobody pays us to be on it.
What counts as an AEO tool for B2B SaaS?
An AEO tool, in the B2B SaaS context, is software that measures how often AI engines name your brand on a defined set of buyer prompts, and surfaces which pages the engines cite as sources. The category sits one layer above traditional SEO platforms. Ahrefs and Semrush track keyword rank on Google. AEO tools track brand mention rate inside generated answers across ChatGPT, Claude, Perplexity, Gemini, and Google AI Overviews.
This is distinct from generic LLM analytics products. Most LLM dashboards report token usage, model latency, or content sentiment. An AEO tool is structured around a different unit of work: the prompt portfolio. You upload 40 to 75 category-relevant prompts, the tool runs them weekly across multiple engines, and the output is a share-of-answer dataset you can attribute back to specific pages on your site.
Three components separate a real AEO tool from a rebranded SEO platform with an LLM tab:
- Multi-engine prompt running. ChatGPT, Claude, Perplexity, Gemini, and Google AI Overviews. Engines disagree often enough that single-engine tracking is misleading.
- Citation attribution to URLs. When the model cites loudface.co, the tool has to record which URL was cited, beyond a brand-level mention. Without URL-level attribution the data cannot feed back into content decisions.
- Prompt taxonomy with tags. Prompts grouped by funnel stage (problem-aware, solution-aware, vendor-aware) and by topic cluster. A flat list of 40 prompts produces a single average that hides where you are actually losing.
One more thing most teams miss: the prompt you track is rarely the search the model runs. AI engines fan a question out into narrower sub-queries before they retrieve, so a tool that only watches your headline prompt misses the fan-out queries that actually decide the citation. The better tools let you track those sub-queries as their own prompts.
How we scored these tools
Every tool below is scored on four capability dimensions, each out of 5, for a capability score out of 20. Price sits in its own column because cheap-but-shallow and expensive-but-deep are different bets, and folding them into one number hides the tradeoff. The four dimensions:
- Engine coverage. How many of the answer engines that matter (ChatGPT, Claude, Perplexity, Gemini, Google AI Overviews, Copilot) it actually tracks. Single-engine tools score low.
- URL-level citation attribution. Does it tell you the exact page the model cited, or only that your brand was mentioned? This is the dimension most tools are weakest on, and the one that decides whether the data can drive content.
- Competitor share-of-voice. Can you see who holds the citations you do not, prompt by prompt?
- Enterprise and multi-brand. Multi-account management, white-label reporting, portfolio-level monitoring.
Scores are our read from hands-on use, vendor documentation, and verified feature pages as of June 2026. They are a starting filter. They are not gospel. The tool you should buy is the one whose strong dimensions match the job you are hiring it for, which is why our own pick does not top the raw capability score.
| Tool | Engine coverage | URL attribution | Competitor SoV | Enterprise | Total /20 |
|---|---|---|---|---|---|
| Profound | 5 | 5 | 5 | 5 | 20 |
| Evertune | 5 | 5 | 5 | 5 | 20 |
| AthenaHQ | 5 | 3 | 5 | 4 | 17 |
| Rankscale | 5 | 3 | 5 | 4 | 17 |
| Peec | 4 | 3 | 5 | 4 | 16 |
| Conductor | 5 | 3 | 3 | 5 | 16 |
| BrandRank | 4 | 2 | 5 | 5 | 16 |
| Otterly | 3 | 4 | 5 | 3 | 15 |
| Ahrefs Brand Radar | 4 | 1 | 5 | 4 | 14 |
| Semrush AI Visibility | 2 | 3 | 5 | 4 | 14 |
Two patterns jump out of the scorecard. URL-level attribution is where the field is weakest: only Profound and Evertune score a clean 5, and Ahrefs Brand Radar scores a 1 despite its SEO-team appeal. And price runs inverse to capability: the two tools that top the table both skew enterprise, while the most accessible tools (Otterly, Rankscale) trade some depth for a $20 to $29 entry.
At a glance
| Tool | Best for | Capability /20 | Entry price (verified Jun 2026) |
|---|---|---|---|
| Profound | Enterprise dashboards + URL attribution | 20 | Sales-gated (~$99/mo+ reported) |
| Evertune | Source-influence analysis at portfolio scale | 20 | Enterprise only, ~$3,000/mo |
| AthenaHQ | Prompt-portfolio tracking, broad engines | 17 | $95/mo (annual) |
| Rankscale | Coverage-per-dollar + content-gap analysis | 17 | $20/mo (Essentials) |
| Peec | Daily competitor + share-of-answer ops | 16 | Contact for pricing |
| BrandRank | Sentiment and mention context | 16 | No public pricing |
| Conductor | SEO + AEO + content in one enterprise suite | 16 | Enterprise (sales-gated) |
| Otterly | Cheapest serious citation auditing | 15 | $29/mo (Lite) |
| Ahrefs Brand Radar | AI mentions bolted onto an SEO stack | 14 | ~$828/mo all-in (add-on) |
| Semrush AI Visibility | AI tracking inside Semrush | 14 | $99/user/mo |
If you only buy one and you are a mid-market B2B SaaS team running a real program, start with Peec. It does not top the raw capability score (its pricing is opaque and that costs it a column), but the competitor view and prompt taxonomy are what we open every morning. If you need URL-level citation attribution above all else, Evertune or Profound. If budget is the binding constraint, Rankscale at $20 or Otterly at $29.
The 10 AEO tools worth knowing in 2026
1. Peec: capability 16/20
What it does: tracks brand mentions, citations, and share-of-answer across ChatGPT, Perplexity, Gemini, AI Mode, and Copilot, with Claude and newer models on the Enterprise tier. Daily scans. Tag taxonomy for slicing prompts by funnel stage, service area, and vertical.
How we use it at LoudFace: 75 active prompts. 9 tags (TOFU / MOFU / BOFU plus Webflow / SEO / AEO / CRO plus SaaS / Fintech). Daily competitor scan. Weekly review of which prompts moved.
Where it wins:
- Largest connected prompt library among tools we have tested
- Cleanest competitor-tracking view in the category
- Filter prompts by tag and you get strategic insight rather than raw data
Where it doesn't fit:
- Pricing is contact-only, which makes it hard to budget before a sales call
- Under 20 tracked prompts the value is hard to justify
- The action layer is thin. You still need a content team to act on the data
Pricing: contact for pricing, tiers Starter through Enterprise (peec.ai). Best for: B2B SaaS marketing teams running a real program with 30+ tracked prompts. Not for: solo founders tracking under 10 prompts who would do fine with manual checks.
2. Profound: capability 20/20
What it does: enterprise AEO platform with deep URL-level citation attribution, multi-brand dashboards, and CFO-readable reporting. Tracks ChatGPT, Perplexity, Gemini, AI Overviews, and 10+ surfaces.
How we use it: not currently. We evaluated it and chose Peec for our stage. We refer enterprise prospects who ask about agency-grade tooling here.
Where it wins:
- The most complete URL-level attribution in the category, which is why ChatGPT itself tends to name it first
- Multi-brand is genuinely useful for agencies managing 5+ accounts
- Reporting layer is the most CFO-readable we have seen
Where it doesn't fit:
- Pricing is sales-gated and opaque, which makes budgeting hard before a call
- Overkill for a single brand under 100 prompts
Pricing: sales-gated. Third-party reports cite self-serve tiers from around $99/mo up to custom enterprise contracts (tryprofound.com). Best for: agencies running 5+ client programs and enterprise marketing teams. Not for: anyone with one brand and a small prompt set.
3. AthenaHQ: capability 17/20
What it does: prompt-portfolio management across ChatGPT, Perplexity, Gemini, AI Mode, Claude, Copilot, and Grok. Build a library of buyer prompts and track them over time.
How we use it: pilot. We have it under evaluation alongside Peec.
Where it wins:
- Prompt-management UX is genuinely well thought through
- Nine-engine coverage is among the broadest at this price
- Pricing is public and credit-based ($95/mo annual gets ~3,600 credits, one credit per AI response)
Where it doesn't fit:
- Newer entrant. Feature depth lags Profound on attribution
- Credit-based pricing makes monthly cost harder to predict than per-prompt models
Pricing: $95/mo annual, $295/mo monthly, Enterprise custom (athenahq.ai). Best for: teams that obsess over prompt-portfolio structure. Not for: anyone who needs everything in one tool today.
4. Evertune: capability 20/20
What it does: AI visibility and source-influence platform. Beyond tracking whether you are mentioned, it identifies the influential third-party URLs shaping the model's answer: Strength URLs (sources that already mention you) and Opportunity URLs (influential sources that do not yet). Runs 10+ engines including ChatGPT, Claude, Gemini, Perplexity, AI Mode, Copilot, Meta AI, and DeepSeek.
Where it wins:
- Real URL-level attribution, which most tools only approximate
- Source-influence analysis tells you which pages to go earn a mention on, beyond your own score
- Broadest engine coverage on this list, unlimited competitor tracking
Where it doesn't fit:
- Enterprise-only, no self-serve, no free trial
- Aggregated brand-score framing over granular prompt-by-prompt ranking
Pricing: enterprise-only, roughly $3,000/mo entry on annual terms (evertune.ai). Best for: enterprise brands that want to influence the sources behind the answer rather than only measure it. Not for: anyone needing a self-serve entry point.
5. Otterly: capability 15/20
What it does: citation auditing. Shows which pages from your domain get cited in LLM answers, and for which prompts, across ChatGPT, AI Overviews, Perplexity, and Copilot.
How we use it: spot checks after publishing. Tells us within 24 hours whether a new page is showing up in answers.
Where it wins:
- Cheapest serious entry point in the category
- The which-page-got-cited view is more granular than what Peec exposes
- Transparent, published tiers
Where it doesn't fit:
- Competitor tracking is thinner than Peec
- 15 prompts on Lite is tight for a real program; most teams move up within a quarter
Pricing: Lite $29/mo (15 prompts), Standard $189/mo, Premium $489/mo (400 prompts); annual is cheaper. Gemini and AI Mode are paid add-ons from $9/mo depending on tier (otterly.ai). Best for: content teams validating published pages weekly. Not for: programs that need competitor share-of-voice as the primary KPI.
6. Ahrefs Brand Radar: capability 14/20
What it does: tracks brand mentions and share-of-voice across AI Overviews, AI Mode, ChatGPT, Perplexity, Gemini, and Copilot, drawing on a large database of real search-backed prompts. Also covers YouTube, TikTok, and Reddit mentions.
Where it wins:
- If you already live in Ahrefs, AI-mention tracking sits next to your existing SEO data
- Competitor benchmarking by topic is solid
- Prompt volumes are pulled from real searches rather than synthetic lists
Where it doesn't fit:
- No URL-level citation attribution. It tells you mention frequency, without surfacing which page won the cite, and that is the dimension that drives content decisions
- No Claude coverage
- Cost only makes sense once you are paying for a higher Ahrefs plan plus the add-on
Pricing: paid add-on on top of an Ahrefs plan. $199/mo per single AI index, or $699/mo for all platforms; real all-in entry lands near $828/mo once the base plan is counted (ahrefs.com). Best for: SEO teams already standardized on Ahrefs. Not for: teams that need to know the exact cited URL.
7. Semrush AI Visibility Toolkit: capability 14/20
What it does: monitors brand appearance, perception, and competitive share across ChatGPT, Google AI Overviews, AI Mode, and Gemini, inside the Semrush ecosystem.
Where it wins:
- Natural add-on if your team already runs Semrush
- Sentiment and brand-perception views are well built
- Competitor share tracking is included
Where it doesn't fit:
- Engine list is narrower than dedicated AEO tools, with no Perplexity or Claude in the core toolkit
- Per-seat pricing scales fast across a team
Pricing: $99 per user per month as a standalone toolkit; three seats land near $297/mo. 7-day trial (semrush.com). Best for: teams standardized on Semrush. Not for: teams that need Perplexity and Claude coverage.
8. Conductor: capability 16/20
What it does: enterprise platform that bundles AI Search performance tracking, an AI Topic Map, content opportunities, an on-brand writing assistant, and AI-crawler monitoring. Queries the engines through official APIs rather than scraping, across ChatGPT, AI Overviews, Copilot, Perplexity, Gemini, and Claude.
Where it wins:
- One suite for SEO, AEO, and content generation, which large teams value
- Ties AI visibility to traffic, conversions, and revenue
- API-based data collection is more stable than scraping
Where it doesn't fit:
- Enterprise pricing and commitment. Pricing is opaque
- Competitor share-of-voice is not a clearly first-class view
Pricing: no public pricing, demo-gated. Third-party reports put mid-market tiers in the hundreds per month and enterprise contracts well into five and six figures per year (conductor.com). Best for: large enterprises that want SEO and AEO in one place. Not for: lean teams that need a clear monthly price.
9. Rankscale: capability 17/20
What it does: content-gap analysis from LLM citation patterns across 10 engines including ChatGPT, Perplexity, AI Mode, AI Overviews, Gemini, Claude, Grok, and Copilot. Identifies topic clusters where you are losing citations.
How we use it: monthly review. Generates the next-5-things-to-write shortlist that feeds our content calendar.
Where it wins:
- Lowest real entry price in the category and the broadest engine list at that price
- Content-gap framing is more actionable than raw citation data
- Topic clustering is solid
Where it doesn't fit:
- The $20 Essentials tier is a taster. Most teams land on Pro or Growth
- Output is a starting point. The clustering is statistical; you still need a strategist to pick which gaps are worth attacking
Pricing: Essentials from $20/mo, Pro $99/mo (~1,200 credits), Growth $385/mo, Enterprise $780/mo (12,000 credits) (rankscale.ai). Best for: content teams that need a defensible what-to-write-next pipeline. Not for: teams without the bandwidth to act on monthly recommendations.
10. BrandRank: capability 16/20
What it does: sentiment and mention attribution across ChatGPT, Gemini, Claude, Perplexity, Grok, Meta AI, and DeepSeek. Tracks how every citation lands, positive, negative, or neutral, and a Category Answer Share view for competitive context.
How we use it: occasional checks when something feels off. If a competitor starts being cited more on our priority prompts, we want to know whether they are being recommended or warned against.
Where it wins:
- Sentiment-aware citation tracking is rare
- Surfaces the cited-as-a-cautionary-tale failure mode
- Used by 60+ enterprise brands, so multi-brand is mature
Where it doesn't fit:
- Sentiment is a noisy signal at the LLM level. Treat it with appropriate skepticism
- URL-level attribution is unclear
- No public pricing
Pricing: no public pricing, demo only (brandrank.ai). Best for: brands defending category position that need mention context rather than raw frequency. Not for: programs still in citation-acquisition mode, where any mention is a win.
Honorable mentions
Two newer tools worth a look, both genuine products rather than blogs, and both cited often in AI answers about this category:
- ziptie.dev tracks visibility across Google AI Overviews, ChatGPT, and Perplexity with content optimization and AI success scores. Public pricing from $69/mo (Basic, 500 checks) to $159/mo (Pro). Narrow on engines (no Gemini or Claude) but cheap and self-serve (ziptie.dev).
- xSeek analyzes how ChatGPT, Perplexity, Gemini, and Claude perceive your company and hands back an action plan, with a free diagnostic and developer utilities for llms.txt and robots.txt. Tiered Starter through Scale, prices not published on the main page (xseek.io).
How to actually pick
You do not need most of this list. The category is over-tooled and getting more so. The stack for a typical B2B SaaS team is two tools, maybe three:
- One tracker. Peec, AthenaHQ, or Rankscale. Pick by which prompt-management model matches how your team thinks and what you can afford.
- One auditor. Otterly if you publish weekly and want the cheapest serious which-page-got-cited view. Evertune or Profound if URL-level attribution is the whole point and you have the budget.
- Optional: content-gap input. Rankscale if you have a content team that can act on a monthly shortlist.
If you are an enterprise with multiple brands, the shortlist collapses to Profound, Evertune, or Conductor, and the decision is about reporting depth and how much of your SEO stack you want to consolidate.
Anything beyond two or three tools is over-tooling. We see teams drown in dashboards more often than we see them under-instrumented.
If your AEO program is brand new and you do not yet have a tracked prompt list, the right move is to build the prompt portfolio first. Ninety minutes of work, manually, in a spreadsheet. Then buy a tool to automate the daily check. Buying tools before you have a prompt strategy is buying answers to questions you have not asked.
How we use AEO tools at LoudFace
Honest daily practice:
- Morning: open Peec, check share-of-voice trend for our top 20 prompts. Flag any prompt where we lost a position overnight.
- Weekly: review which new pages got cited (Otterly) and which prompts moved tags (Peec). Surface 2 to 3 content updates.
- Monthly: Rankscale gap analysis feeds the next month's content calendar.
- Quarterly: review the tool stack itself. Drop anything that did not surface insight we acted on in the prior 90 days.
The tools earn their keep when the data drives decisions. The Peec dashboard is how we knew Toku had become the AI's go-to answer for stablecoin payroll, and which adjacent prompts to attack next to compound that position.
We use Peec to drive our Notion content roadmap directly. The tools and the writing are tightly coupled. AEO tooling without a content team to act on the data is a dashboard hobby. And remember that none of these tools watch the fan-out sub-queries by default, so the prompts you load matter as much as the tool you pick.
Stop measuring the wrong layer
The tool matters less than the prompts you load into it and the content team that acts on the output. Pick one tracker, one auditor, point them at the fan-out queries your buyers actually ask, and review the data weekly. The teams that win AI citations are not the ones with the most dashboards. They are the ones who shipped the page that answered the sub-query everyone else skipped.
If you want to see where you stand, we run a free AI visibility audit: in a couple of minutes it shows how ChatGPT, Claude, Gemini, and Perplexity describe your brand and where the gaps are. See our public pricing first if that helps.
Frequently Asked Questions
Which AEO tool should I start with in 2026?
For a mid-market B2B SaaS team running a real program, Peec, for its competitor view and prompt taxonomy. If pricing transparency matters before a sales call, start with Rankscale at $20/mo or Otterly at $29/mo for citation auditing and add a fuller tracker later. If URL-level attribution is the priority and budget is not the constraint, Evertune or Profound.
What's the difference between AEO tools and SEO tools?
AEO tools track citations in LLM answers across ChatGPT, Claude, Perplexity, and Gemini. SEO tools track positions in search engines like Google and Bing. The data sources differ, the metrics differ, and the optimization moves differ. Some vendors bundle both, like Ahrefs Brand Radar and the Semrush AI Visibility Toolkit, but treat the AEO module as the secondary product unless attribution is first-class.
Do I need an AEO tool if I already use Ahrefs or Semrush?
Their AI modules (Ahrefs Brand Radar, Semrush AI Visibility Toolkit) are a reasonable starting point if you already pay for the platform, and they keep AI mentions next to your SEO data. The catch is attribution: Ahrefs Brand Radar tracks mention frequency but not which URL was cited, and that is the data that drives content. If you are serious about AEO, a dedicated tool earns its place.
What's the cheapest AEO tool for a startup?
Rankscale Essentials at $20/mo is the lowest real entry, followed by Otterly Lite at $29/mo and ziptie at $69/mo. All three are self-serve with published pricing. Below a tracked prompt list, though, even free is too expensive: do the manual 90-minute audit first.
Which AEO tools track ChatGPT vs Perplexity vs Gemini?
Most serious tools cover ChatGPT, Perplexity, and Gemini. The breadth leaders are Rankscale, AthenaHQ, Evertune, and Conductor, which add Claude, Copilot, Grok, and others. Watch the gaps: the Semrush AI Visibility Toolkit omits Perplexity and Claude in its core, and Ahrefs Brand Radar omits Claude. Match the engine list to where your buyers actually ask.
How much should a B2B SaaS company spend on AEO tools in 2026?
Most B2B SaaS teams should expect $300 to $800 per month on AEO tooling once the program is running, which buys a tracker plus an auditor. Below that you are under-tooled. Above that, outside genuine enterprise needs, you are probably over-tooled relative to the content team that has to act on the data.
How accurate are AEO tools at tracking LLM citations?
Accurate enough to make decisions. It is not literal. LLM responses vary across sessions, regions, and model updates. A tool that says you are cited 12% of the time on a prompt means roughly 12% in its sample rather than exactly 12% of all queries globally. Treat trends as more reliable than point estimates, and read your own server logs as the ground truth for what bots actually fetched.
Will these tools still matter in 2027?
The category will consolidate. It is young and over-tooled, and 2026 is already seeing the SEO incumbents (Ahrefs, Semrush, Conductor) bundle AEO into their suites while pure-plays raise prices. Expect mergers and pricing pressure through 2027. Buy on quarterly contracts where you can. Long annual lock-ins in a moving category are a bad trade.
