The three jobs a GEO tool actually does, what each tier honestly costs, and the free stack that covers most teams — from an operator who measures this for a living.
New to GEO? Start with the field guide to AI search optimization.
A "GEO tool" does one of three jobs: audit your pages, track your citations, or measure your AI traffic. Jobs one and three are free. For job two:
And the rule that saves you the most money: no tool earns citations. They measure. Content, structure, and distribution earn.
"GEO tool" gets used for three completely different products, and the buying mistake is paying for one job when you needed another. Before comparing brands, decide which job you're hiring for.
Score whether a page is structurally citable: answer-first sections, clean heading hierarchy, FAQ, tables, crawler access, Bing indexation. Point-in-time, page-level.
Run a panel of prompts against ChatGPT, Perplexity, Gemini, and Copilot on a schedule, and measure how often you're cited vs. competitors — your share of answers.
Attribute the sessions, signups, and revenue AI assistants actually send. Referral sources like chatgpt.com and perplexity.ai in your analytics.
Every paid platform below sells job two. If a vendor implies their dashboard will earn you citations, close the tab — measurement instruments don't write original data or earn third-party mentions. The levers that actually move citations are in the operator's playbook.
Honest tiering, not a top-ten listicle. Prices are published entry points as of June 2026 — verify before buying; this market reprices monthly.
| Tool | Job | Entry price | The honest take |
|---|---|---|---|
| Free Bing Webmaster Tools | Eligibility + citations | $0 | The most underrated GEO tool that exists. ChatGPT and Copilot read Bing's index, and the AI Performance report shows real Copilot citation counts — it's where my 135,700 citations were measured. Non-negotiable, before any paid tool. |
| Free Google Search Console | Eligibility + early signal | $0 | Watch for long conversational queries at deep positions — that's query fan-out probing your pages, the earliest sign AI retrieval has found you. |
| Free GEO Readiness Scanner (mine) | Audit | $0 | Scores any URL on 14 structural signals with ranked fixes. It's a page auditor, not a citation tracker — it tells you if a page can be cited, not whether it is. Run it here. |
| Entry Otterly.AI | Track citations | ~$29/mo | The cheapest serious tracker. Limited prompt volume at the entry tier, but enough to learn whether AI engines mention you at all. Right choice for early-stage teams and agencies running multiple small clients. |
| Entry–Mid LumenGEO (mine) | Track citations | Free scan; paid tracking | Built around one conviction: single-run checks are screenshots, not measurements. It samples the same prompts repeatedly and reports share of answers with stability data. If you only want "does ChatGPT mention me, reliably measured," this is the job it does. |
| Mid-market Peec AI | Track citations | ~€89/mo | The competitive-analysis pick: strong multi-engine and multi-language coverage, good benchmarking against named competitors. Best fit for mid-market B2B teams with a content engine already running. |
| Enterprise Profound | Track citations | ~$499/mo+, sales-led | The depth pick for large brands — enterprise integrations, big prompt panels, agent analytics. Overkill below roughly $10M revenue; most teams reading this page don't need it yet. |
| Suite add-on Ahrefs Brand Radar | Track mentions | Inside Ahrefs plans | If you already pay for Ahrefs, turn it on — AI Overview and chatbot mention tracking beside your existing SEO data. Less prompt control than dedicated trackers. |
| Suite add-on Semrush AI toolkit | Track mentions | Add-on pricing | Same logic as Brand Radar: convenient if you're already in the suite, not a reason to join it. Good for reporting AI visibility alongside classic rank tracking. |
Prices are published entry points as of June 2026 and change frequently; treat them as order-of-magnitude, not quotes.
The tier table tells you what each tool does. This tells you which ones to actually buy — and what not to touch yet.
| Situation | The stack | Monthly cost (order of magnitude) | Do NOT buy yet |
|---|---|---|---|
| Solo founder / pre-product Building, not yet shipping |
Free stack only: Bing WMT + GA4 AI segment + free page scanner. Add 30 min of manual prompt checks weekly — ask your 10 money questions across ChatGPT and Perplexity, each one twice. | $0 + ~2 hrs/month attention | Any paid tracker. You have nothing citable yet; a dashboard measuring zero is expensive theater. Come back when you have 5+ pages indexed in Bing and organic traffic you can trend. |
| Early-stage startup Content exists, citations unknown |
Free stack (non-negotiable) + Otterly.AI entry tier or LumenGEO once you've confirmed Bing has indexed your key pages. One prompt panel: 15 money prompts, not brand prompts. | ~$29–$50/mo | Peec AI, Profound, or any enterprise seat. You don't yet have the competitor baseline to make mid-market data actionable, and no one will act on weekly reports if the team is two people. |
| Agency running multiple clients Billing AI visibility as a service |
Entry tracker per client (Otterly-style). Run the per-client cost math before you sell: if a client pays $500/mo retainer and the tracker seat costs $29, the math works. At $150/seat for 6 clients it doesn't unless AI is a core deliverable with clear KPIs. | $29–$60/client/mo | Promising clients "AI rankings" — there is no such thing as an AI rank. Share of answers is a share, not a position. Agencies that over-promise this will lose clients when the number fluctuates. |
| Mid-market SaaS with a content team $2M–$20M ARR, dedicated content |
Free stack + Peec AI for multi-engine competitive benchmarking. At this stage you have named competitors worth measuring against and content velocity that makes weekly data actionable. Assign one person (even part-time) whose job includes acting on the citation trends monthly. | ~€89–$200/mo | Profound and enterprise contracts with annual minimums. The depth pick is real but the price is real too — wait until the data directly informs a six-figure content or distribution spend. |
| Enterprise brand $50M+ revenue, brand + category |
Profound (or equivalent enterprise suite) alongside the free stack. You need the prompt panel depth, the multi-language coverage, and the integrations that justify the contract. Also: a named owner — a dashboard no one acts on is the most expensive kind of free. | $499+/mo (sales-led) | Nothing — but make sure someone's job description actually includes "act on AI citation data." Enterprise tooling without an accountable operator is the most common way to waste this budget. |
Cost ranges are order-of-magnitude estimates as of June 2026. Verify current pricing directly — this market reprices frequently.
Every serious tracker offers a trial. This is the protocol that separates measurement tools from screenshot generators — run it before you enter a credit card.
Write the questions a buying customer actually types — not vanity brand prompts. Examples: "best [category] tool for [use case]," "how do I solve [specific problem]," "[your product] vs [competitor]." If a prompt only works when someone already knows your brand name, it's not a money prompt. Aim for coverage of buying intents: problem-aware, solution-aware, and comparison-stage questions. Cap at 25 — tracking volume beats tracking useful signals.
ChatGPT, Perplexity, and Google AI Mode / AI Overviews at minimum. Copilot is a bonus if the tool supports it. The point is a full week of data: AI answers have day-of-week variance, and a single day can be anomalous. You need a trend, not a snapshot.
Ask the vendor: how many times do you run each prompt per cycle? The correct answer is more than once — ideally 3–5 runs minimum. About one run in nine produces an answer that contradicts the others (per first-party LumenGEO sampling data). A tool reporting single-run results is giving you a screenshot, not a measurement. If they can't or won't answer this question, treat the output as directional at best.
Look for a trendline, not a single citation count. A tool that shows "you were cited 14 times this week" is less useful than one that shows your share of answers moving from 12% to 18% over 30 days. The latter tells you whether what you published last month moved the needle.
Find the citation detail view. Knowing "ChatGPT mentioned us" is table stakes. Knowing "ChatGPT cited the FAQ section of /pricing three times this week but never the homepage" is actionable. If the tool can't surface which page or passage earned (or lost) each citation, it can't close the loop between content work and citation outcomes.
Try to export or access the underlying prompt responses. Auditability matters: if a citation count moves sharply, you should be able to read the actual AI responses that drove the change. A tool that won't let you see the raw runs is asking you to trust their black box. That's fine for a weather app; it's not fine for a data source you're reporting upward or billing clients on.
A tool that passes all four checks earns a paid seat. A tool that fails checks 1 or 2 is a dashboard for comfort, not measurement. Don't pay comfort prices.
Before you subscribe to anything, know what you're agreeing to measure. Most tools default to metrics that are easy to produce, not metrics that are worth tracking.
| Worth tracking | Why it's actionable |
|---|---|
| Share of answers (over repeated runs, trended) | Relative, comparable across time, accounts for answer instability. A citation share moving from 8% to 21% in 60 days is a clear signal that specific content moves landed. |
| Citation count trend per engine (especially Bing WMT's AI Performance) | Bing Webmaster Tools breaks out Copilot citations for free — the same index ChatGPT reads. Trending this weekly is free and almost nobody does it. Directionally reliable. |
| AI-referral sessions + conversions (GA4 segment) | This is job three — the actual revenue question. GA4 referral traffic from chatgpt.com, perplexity.ai, gemini.google.com, and copilot.microsoft.com tells you whether citations translate to pipeline, not just brand impressions. |
| Which pages earn citations (concentration) | On GrantCompass, an average of ~58 pages were doing the citing work, not the entire site. Knowing your citing pages lets you double down on what's working and diagnose what's dormant. If you don't know this, you're optimizing the wrong content. |
| Vanity metric | Why it misleads |
|---|---|
| Single-run "do we appear" screenshots | One run tells you almost nothing about your typical share of answers. The same prompt run nine times will contradict itself at least once. A screenshot is a moment, not a measurement. |
| "AI rank" (position 1, 2, 3 in an AI answer) | AI answers aren't ranked lists. A synthesized response may cite you first in one sentence and third in another with no meaningful difference in influence. "AI rank" is a metric vendors invented because users understand ranking; it doesn't correspond to anything real in how AI citations work. |
| Citation totals without a competitor baseline | "We got 400 citations this month" means nothing without knowing whether your closest competitor got 40 or 4,000. Absolute counts are only useful once you establish a relative baseline. |
| Tool-invented composite "visibility scores" with no methodology | If a vendor shows you a single number — "AI Visibility Score: 67" — and can't tell you the exact formula, treat it as a marketing device, not a KPI. Composite scores obscure what's actually changing and make it impossible to attribute movement to specific content decisions. |
Three budget tiers, no hedging. The rule underneath all of them: cap tooling at a fraction of what you spend making content citable.
The rule from the top of this page bears repeating here: no tool earns citations. A $500/mo dashboard measuring a site with nothing citable earns you exactly $0 in citations. Spend the tooling budget last, not first. If you have $500/mo to allocate to GEO, spend $450 on content that answers buying questions directly and $50 on the tracker that tells you whether it worked.
This is what I'd set up before spending a dollar — it's the stack the paid tools are largely repackaging.
Verify your site, submit your sitemap, then watch the AI Performance report. It shows actual Copilot citation counts from the same Bing index ChatGPT reads. This is real citation data, free, and almost nobody looks at it.
Build one segment for chatgpt.com, perplexity.ai, gemini.google.com, copilot.microsoft.com, and claude.ai. That's your job-three dashboard: the sessions and conversions AI answers actually send you, trended over time.
Filter queries for full-sentence, conversational phrasing at positions 50+. Those are machine sub-queries from query fan-out, and they tell you which sub-questions engines think your pages might answer.
Run priority URLs through the free scanner, then ask the engines your money questions weekly. Ask each one several times — answers shift run to run, which is exactly why serious tracking samples repeatedly.
Pay when all three of these are true — not before.
And one buying filter that cuts through every demo: ask how many times they run each prompt. AI answers are unstable — about one run in nine contradicts the rest, per the 87-experiment dataset. A tool reporting single-run results is selling you screenshots.
What GEO is, the engines, GEO vs SEO, and a working glossary.
Start here →The nine moves that earn the citations these tools measure.
Read the playbook →The retrieval mechanic behind every engine in this comparison.
Learn the mechanic →Job one, free: score any URL on the 14 signals with ranked fixes.
Scan your page →Different unit (citation vs. rank), different stability, different levers — the full breakdown for practitioners who've used both.
Read the comparison →Run your most important URL through the free scanner first. If the page isn't structurally citable, no tracker on this page has anything to track yet.
Updated June 2026 · Prices verified at publish; this market reprices monthly.