Standing vs HubSpot AEO

• Distribution, decisively. It ships inside a CRM that a very large number of businesses already use, and it is bundled free into Marketing Hub Pro and Enterprise. Most buyers will meet it without looking for it.
• Price. $50/mo is half our entry tier, and zero for an existing customer on the right plan.
• A genuinely free, no-account grader, which is a real gift to somebody who just wants a first look.
• The data sits beside contact and deal records, so AI visibility can be joined to pipeline. We cannot do that and it is a legitimate reason to choose them.
• Their citations view breaks down which content types and domains get cited in a category, which is a useful cut we do not ship.

HubSpot AEO: $50/mo for 25 prompts across ChatGPT, Perplexity and Gemini, or $45/mo paid annually. Free for 28 days. Enterprise-grade AEO features are also included in Marketing Hub Pro and Enterprise, so an existing HubSpot customer on those tiers pays nothing extra. A separate one-time AI Search Grader is free with no account.

Prompts, capped per tier, in the same shape as the rest of the category. The difference is the bundle: for a business already on Marketing Hub Pro the marginal price is zero, which no pure-play can match.

Standing: a fixed basket built from your category, priced per domain rather than per prompt. It is the smallest basket in the category and the only fixed one, which is the trade: fewer questions, but the same questions every scan, so a change in the score is a change in the answers rather than a change in what we asked. It also means two customers in one category are directly comparable.

HubSpot AEO: Not published. Their documentation describes brand visibility as the percentage of tracked prompts where the brand appears, and the overall score as a weighted blend of five dimensions, but the number of runs behind either figure is not stated in their material or in the third-party reviews of it.

Standing: 5 runs per prompt per engine on paid scans, 3 on the free check, published. Roughly 300 responses per paid scan. This is the number that decides whether a score is a measurement or a single draw from a distribution.

HubSpot AEO: None published. No interval, no minimum detectable change, no significance test. Worth stating precisely because their score is a composite: sentiment, presence quality, brand recognition, share of voice and market competition, summed to 100. Every one of those is itself an estimate with its own variance, and adding five noisy estimates together produces a number that moves more than any of its parts, reported as a single figure.

Standing: a 95% confidence band on every score, shown in the product, with alerts gated on whether a move exceeds that domain's own historical drift. An engine that fails more than half its calls reports that it did not respond rather than a measured zero. Our own weakness, stated: the band covers within-scan sampling and does not cover platform drift between scans, which is why the model version is on the report.

• Five surfaces to their three: we add Claude and Google AI Overviews.
• Five runs per question per engine, published. Theirs is not published at any depth, so a customer cannot tell whether a score came from one draw or twenty.
• Every score carries a 95% interval, and an alert only fires when a move exceeds that domain's own historical drift.
• One fixed basket shared across a category, so two customers' numbers are directly comparable. A per-customer prompt list cannot be.
• A degraded engine is reported as degraded, never scored as a zero.

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