Start with the engines your buyers use, then compare capacity, price, data access, and what your team can do with the findings. If you need five-engine monitoring and documented prompt-level API access, SE Visible Basic is listed at $99 per month. If ChatGPT, Gemini, and Perplexity are sufficient, HubSpot AEO is listed at $50 per month with 25 tracked prompts. Semrush may fit an existing SEO workflow, while Scrunch Core remains relevant when its four-platform coverage and 125-prompt allowance match your requirements better.
This is a decision guide, not a claim that one visibility score is better than another. The comparison uses official documentation reviewed on October 11, 2026. Prices, trials, limits, engine coverage, and packaging can change, so confirm the quoted tier before buying.
The practical question is not only which tool monitors the most engines. It is whether the product gives your team usable observations, defined metrics, export or API access, and a controlled path to review and action.
The short answer: choose by coverage, cost, and what happens after monitoring
Use this order of operations: identify required engines, confirm prompt and project limits, calculate the price at your expected scale, verify exports or API access, and assign ownership for reviewing the results. Exclude any product that misses a required engine or data-access condition before comparing headline visibility scores.
- Scrunch Core: The official FAQ lists $250 per month, 125 prompts, one brand workspace, five user licenses, and four platforms: ChatGPT, Perplexity, Google AI Overviews, and Microsoft Copilot.
- HubSpot AEO: The product catalog lists a stand-alone beta product at $50 per month with 25 tracked prompts and daily runs across ChatGPT, Gemini, and Perplexity. Its product page also lists visibility, sentiment, citation analysis, prompt suggestions, and prioritized recommendations.
- SE Visible Basic: The product page lists $99 per month, 200 prompts, three projects, approximately 30,000 analyzed answers per month, and five engines: ChatGPT, Gemini, Google AI Mode, Perplexity, and Google AI Overviews.
- Semrush AI Visibility Toolkit: Semrush lists $99 per month when billed annually, with 25 tracked prompts and one domain for Brand Performance analysis. The base toolkit lists ChatGPT, Google AI, Gemini, and Perplexity. Broader Semrush materials describe additional coverage, so verify the exact package.
HubSpot currently advertises a free AEO trial, but official pages have presented different trial durations. Confirm duration and eligibility at signup. Scrunch states that Core has a seven-day trial. Semrush documentation says the AI Visibility Toolkit itself does not offer a free trial.
HubSpot AEO can be purchased without another HubSpot subscription. Marketing Hub Professional and Enterprise include AEO and add Smart CRM context. If CRM ownership, permissions, or downstream updates affect the decision, HubSpot systems consulting can help assess the operating fit.
A lower prompt price is not automatically lower total cost. A team that requires Google AI Overviews, Microsoft Copilot, five projects, raw answer access, or an API may spend more correcting a coverage or data-access mismatch than it would have spent choosing the right tier initially.
Compare like with like: engine coverage, limits, and data grain
Coverage describes what a plan observes: engines, prompts, projects, regions, languages, and refresh cadence. Execution describes what happens next: recommendations, content actions, exports, APIs, and routes for human review. A wide engine list does not prove that a product can update a CRM or CMS record.
Do not treat prompts, answers, checks, and projects as interchangeable units. SE Visible Basic lists 200 prompts and approximately 30,000 analyzed answers per month. HubSpot lists 25 tracked prompts. Semrush lists 25 prompts for one domain. SE Ranking separately defines one AI Search Add-on check as one prompt on one platform, so one prompt tracked across five engines consumes five checks. Ask every vendor whether capacity is counted per prompt, engine, project, location, run, answer, or reporting period.
Collection method matters as well. SE Visible’s FAQ says it collects answers through a browser interface. Profound documents prompt and topic exports in CSV or JSON, while its dashboard FAQ says dashboard exports are PDF and raw dashboard numbers require the API or a relevant Agent data node. These are product-specific access paths, not evidence of a universal integration pattern.
Metric definitions also differ. Profound defines visibility as responses containing a brand divided by responses containing at least one brand. That is Profound’s definition, not an industry-wide standard. Preserve each vendor’s denominator, sampling cadence, engine, region, and reporting period before comparing results.
Treat a prompt run as an observation, cited URLs and brand mentions as related records, and visibility or share of voice as an aggregate over a defined set and period.
Shortlist alternatives by the job your team needs done
Lower-cost monitoring with recommendations
Evaluate HubSpot AEO when ChatGPT, Gemini, and Perplexity cover the required use case. Its documented features include prompt suggestions, visibility, sentiment, citation analysis, competitor share of voice, and prioritized recommendations. Its currently documented stand-alone coverage does not list Google AI Overviews. The product can be used without a full HubSpot subscription, while Marketing Hub Professional and Enterprise add Smart CRM context.
Five-engine monitoring and prompt-level data
Evaluate SE Visible when five-engine coverage, multiple projects, browser-collected answers, and API access matter more than built-in content execution. Its API documentation describes prompt and prompt-result operations and returned fields including model text, mentioned brands and URLs, sentiment, and average position. Confirm authentication, quotas, credits, and account entitlements before treating the API as a production dependency.
SEO-stack consolidation
Evaluate Semrush when AI visibility should sit beside existing SEO data. The base AI Visibility Toolkit lists one domain for Brand Performance analysis and 25 tracked prompts at the reviewed price. Do not transfer engine coverage from broader Semrush AI-search materials into the base toolkit without checking the quoted package.
Analytics and factual-claim review
Evaluate Profound when its Answer Engine Insights definitions, prompt and topic exports, historical reporting, or FactCheck workflow match a defined requirement. FactCheck uses selected fact-based prompts and one connected Knowledge Base, with results typically taking seven days. Verify current plan-specific engine coverage, pricing, and limits directly with Profound.
Other market candidates
GetMint, AthenaHQ, ZipTie, AirOps, Peec AI, Ahrefs Brand Radar, Rankshift, and Otterly AI may merit a separate vendor review. The official documentation reviewed for this guide did not establish their current prices, limits, API entitlements, or engine coverage sufficiently for a verified comparison, so do not use the figures in the source article as procurement facts.
HubSpot’s AI Search Grader can provide a separate, free, one-time diagnostic across ChatGPT, Perplexity, and Gemini. It is useful as a baseline, not as continuous prompt monitoring.
Run a two-week comparison pilot before migrating
A parallel run is a proposed evaluation method, not a vendor-provided migration feature. Keep prompts, engines, regions, languages, competitors, and collection dates as consistent as possible. Record the prompt taxonomy version and each vendor’s native metric definitions before the first run.
Measure prompt and engine overlap, missing and duplicate observations, citation agreement, sentiment-label disagreement, export completeness, API reliability, and time from observation to analyst review. Keep raw observations and vendor definitions beside normalized internal fields.
Turn visibility data into reporting or action without overstating automation
Two documented data paths can support reporting: Profound prompt and topic CSV or JSON exports, and SE Visible prompt-result API access. The reviewed documentation does not establish a universal built-in CRM or CMS write-back workflow. Use an internal review record as the system of record until a named owner approves a destination update.
The following architecture is illustrative implementation design, not a vendor-published template. It separates one prompt run from citations, mentions, aggregates, and CRM or content events.
- Observation: one project, prompt, engine or model, region, language, run, and timestamp. Preserve returned answer text or an allowed raw-payload reference.
- Citation: one observation linked to one canonical URL and citation occurrence. Do not store multiple citations as an opaque field in an aggregate row.
- Brand mention: one observation linked to one brand and any available position or mention event.
- Aggregate: one project, brand, engine, region, language, metric definition, and reporting period. Do not treat it as another prompt run.
- Destination event: one approved proposed change to a CRM, CMS, task system, or report. Keep it separate from the contact or deal record it may reference.
For an illustrative SE Visible ingestion, the input is an authenticated API response containing project and prompt identifiers, engine information, an observation time where available, and returned answer data. Deterministic validation checks required identifiers, supported engines, timestamps, reporting windows, URL format, and duplicate observations. Unknown fields are quarantined for review rather than silently discarded.
Use vendor identifiers as record identity. A proposed observation key is tenant_id + project_id + prompt_id + engine_id + model_variant + region + language + observed_at + run_id. A citation key can be observation_id + canonical_url + citation_ordinal. If concurrent imports are possible, enforce uniqueness in the database and use a transactional upsert. A lookup followed by an insert is not race-safe.
AI can summarize returned text, group similar prompts, or draft an analyst explanation. It should not invent missing IDs, citations, sentiment, metrics, or destination permissions. Retry only documented transient failures, apply backoff for rate limits, log the request and response status, and preserve the raw payload reference, retrieval time, transformation version, reviewer decision, and destination response.
For Profound, exported prompt and topic fields can be mapped into a reporting store while the original file remains in controlled storage. Validate file schema, content type, JSON syntax where relevant, metric definitions, and date fields. Dashboard PDFs are not equivalent to raw structured data, so confirm whether the required numbers come from an export, API, or Agent data node.
For factual claims, Profound’s documented FactCheck process uses fact-based prompts and one connected Knowledge Base. Route legal, financial, safety, medical, or contractual claims to a qualified reviewer. A citation indicates source influence, but does not prove that every claim in an answer is supported by that source.
- Does the quoted plan include Google AI Overviews, Google AI Mode, or both as separate coverage items?
- Are prompts, projects, engines, users, locations, and refreshes counted in the same way your forecast assumes?
- Are raw answer text, prompt IDs, timestamps, and cited URLs exportable, and is API access included in the quoted tier?
- How are visibility, sentiment, share of voice, and average position defined, including empty answers?
- Who owns review and approval before a proposed CRM, CMS, customer-facing, or revenue-impacting change?
Choose the tool that fits the operating job
Choose required engine coverage first. Then compare capacity at expected scale, confirm the data-access path, and test the effort required to move from observation to review.
Scrunch Core may fit when ChatGPT, Perplexity, Google AI Overviews, and Microsoft Copilot coverage plus 125 prompts matter more than entry price. HubSpot AEO may fit a lower-cost three-engine monitoring need with recommendations. SE Visible may fit five-engine monitoring, multiple projects, and documented prompt-level API access. Semrush may fit teams consolidating AI visibility with existing SEO work, subject to its base limits. Profound may fit analytics, exports, metric-definition review, or FactCheck needs.
Let the pilot decide whether the data is complete enough, comparable enough for the intended decision, and practical enough for the team to use. A tool is ready for adoption when its documented coverage, access method, review ownership, and operating controls match the job, not merely when its headline score looks attractive.