AI Visibility Tracking Tools Compared: Features, Pricing and Data Sources

Compare AI visibility tracking tools by the decisions you need to make: which questions and search surfaces they measure, whether a score means a mention or a citation, what evidence you can inspect, and how the result becomes a content or technical task. Then compare the cost of that specific scope, including prompts, engines, locations, seats and add-ons.

This comparison is published by Vercatus. Vendor descriptions below were checked against the linked public pages on 28 September 2026. They describe documented capabilities and plan structures; we have not run a controlled performance benchmark of these products. Confirm the current quote and measurement method before purchasing.

Compare the scope before comparing a headline price

Tool	Documented scope worth evaluating	Pricing and allowance questions	Primary reference
Vercatus	Answer Share on your topics with its range; Why (memory, sources, searches); plays with drafts and acceptance checks; verdicts against topics left alone	Plans are set by topics and sites; every engine is in every plan	Plans and measurement method
Profound	Answer Engine Insights, Agent Analytics and AI Marketer workflows	The current page offers a limited trial and custom Enterprise packages; clarify prompt coverage, credits and data access in the quote	Profound pricing
Peec AI	Brand visibility and source analytics, with daily tracking on its standard plans	Starter lists 50 prompts and three selected models; compare projects, country coverage and access requirements by tier	Peec AI pricing
OtterlyAI	Search-prompt tracking, link-citation analysis and GEO audits	Plans list prompt allowances; Claude, Google AI Mode and Gemini are listed as add-ons. Check the billing period and selected engines	OtterlyAI pricing
Semrush AI Visibility Toolkit	AI research reports, Brand Performance, custom Prompt Tracking and AI Search Site Audit checks	Distinguish report-query limits from the included 25 custom tracked prompts; verify extra domains, locations, users and prompt add-ons	Semrush toolkit documentation

A listed capability may depend on a plan, location or configuration. An omission from this table is not a claim that a vendor lacks it. The linked plan pages provide the full scope.

Profound illustrates why dated verification matters: the current public page describes a trial with 50 prompts run daily for seven days across ChatGPT, Gemini and Google AI Overviews, followed by custom Enterprise packages. Do not carry an older Starter price from another comparison into a procurement decision without checking the current offer.

1. Ask which data produces the score

A visibility platform may combine several evidence types. Request a description and example of each one you intend to use:

• Your selected prompt panel: answers collected for questions you chose, under a defined schedule and context.
• A vendor research dataset: broader observations used to discover topics, brands or competitors. Check its coverage and update period.
• Crawler or server logs: requests made to your website. A bot visit does not establish an answer citation.
• Referral analytics: visits arriving from an assistant or search surface. These are traffic observations, with their own attribution limits.
• A content audit or simulation: whether your pages can answer a question. This is an input assessment rather than an observed answer-engine outcome.

These measurements can complement one another. They should remain identifiable in the report. If a dashboard’s score changes, you need to know which dataset, question cohort and denominator changed with it.

For Vercatus, the methodology explains how Answer Share is measured and how verdicts are read. The citation tracking guide gives definitions you can use to evaluate any tool’s metrics.

2. Verify the exact engine and surface

An engine name alone is not enough. Ask whether an observation comes from a consumer experience, a search-enabled official interface, or a live search-results surface. Record the web-search setting, locale, language and model where disclosed.

Google AI Overviews and Google AI Mode are separate surfaces. Bing Copilot Search and the Copilot application also need precise labels. A plan listing an engine does not establish that every account can observe every country, language or interface.

Use the same engine and context for a comparison. If two tools return different answers under different conditions, you have not yet established which collection is more representative of your audience.

3. Normalize pricing to your workload

Write the workload before requesting a quote. For example, an illustrative team might need a fixed set of customer questions in two countries, daily observations on selected engines, several editors and evidence exports for a monthly report.

Then document these cost inputs:

Input	What to clarify
Prompt allowance	Distinct questions, saved prompts, or completed checks?
Engine coverage	Included engines, selected models and paid add-ons
Frequency	Daily, weekly, on-demand, and how each consumes budget
Markets	Whether each country or language creates another billable unit
Projects and sites	Brand, domain, subdomain or workspace limits
People	Included editors, viewers and additional licenses
Data access	Export history, API availability and retention
Content workflows	Credits or quotas for audits, recommendations and generation
Billing	Currency, tax, annual commitment and cancellation terms

A subscription with a small prompt panel and one surface serves a different workload from one including site audits, multiple domains and implementation review. Neither can be priced fairly by dividing the subscription by a headline “engine count.”

Vercatus lists its prices on the pricing page and its topics, sites and poll frequency per plan in the plan reference. Use the equivalent definitions from each shortlisted vendor to build your comparison.

4. Test evidence quality with one real question

Choose a customer question you already understand, then request a sample report or run an authorized trial. Inspect the answer and sources, rather than accepting the score alone.

Can you see the exact wording and observation date? Are citations separated from mentions? Does a source link resolve to the cited page, and is a third-party page about your brand distinguished from your own website? Are failed requests and searches with no AI answer shown accounted for?

Next, inspect a changed observation. You should be able to identify whether your page entered the sources, the answer changed wording, a competitor appeared or the search surface stopped showing an AI answer. Export enough evidence to reproduce the report’s headline counts.

5. Check what your team can do with the result

Have an editor or engineer take one finding through the proposed workflow. Assign a canonical target page, identify the missing contribution, create a scoped task and record the implementation date. Establish how you will check the same question afterwards.

For agencies, also verify authorization per client site, workspace boundaries, report exports and access when a client leaves. For larger teams, review roles, sign-on requirements and contractual controls using the vendor’s current documentation and quote.

Avoid assuming that generating a new draft resolves a coverage gap. Your team still needs to verify product facts, citations and the existing page that should own the answer. Our guide to useful source content explains that editorial process.

A practical shortlist decision

Prioritize the tool whose documented scope and sample evidence support your immediate workflow. A team building a first repeatable citation panel should focus on question management, context labels and source exports. A team diagnosing missing visibility should also evaluate crawler access and readable-content checks. A team already using a broad search suite should verify whether its included AI features cover the required markets and prompts before adding another system.

Vercatus connects Answer Share, Why, plays and verdicts. Evaluate that workflow on your own topics using the same criteria you apply to the other products.

The evidence behind the questions

• Ask what a number counts. Engines distinguish sources they retrieved from sources a passage is attributed to, so a tool that counts “citations” should say which (grounding and attribution, grade A).
• Ask what the engine itself reports. Bing publishes an AI Performance report with citations and sampled grounding queries; a third-party number can be checked against it for Copilot (Bing AI Performance, grade A).

Keep the selected workload, quote date, source references and decision in one evaluation record. Recheck them when you renew or expand. The useful comparison is the one your team can repeat when products and plans change.