HOW THIS DIFFERS
Most tools report the score. This one reports the evidence.
No product is named on this page. What follows is a comparison of two approaches to the same problem — and a plain list of the things GeoVouch does not do, so you can rule it out quickly if it is the wrong shape for your team.
Two approaches, row by row
| Dimension | GeoVouch | The common approach |
|---|---|---|
| What you are given | Findings that each point at their source — the exact query, the article it was found in, the model response, the page snapshot. The number is the summary, not the product. | A composite visibility score. It moves, but the reason it moved is usually not recoverable. |
| What actually gets measured | The product entity is resolved first, along with its real official homepage; every step then measures that. The URL you typed is kept only as evidence of how the entity was identified. | Whatever URL was entered, treated as the subject. |
| Branded vs de-branded | Two of the seven steps never use your name at all. Category search and Share of Voice are written to resemble a stranger's question, because searching your own brand and finding yourself proves nothing. | Brand-name monitoring: how often the brand appears when the brand is what was searched. |
| Self-reported vs corroborated | Your own pages and independent sources are scored in separate steps and never merged. Blended into one ledger, “is this self-promotion or corroboration” stops being answerable. | One content or authority score covering both. |
| How a prompt result is treated | A prompt is sampled several times per model, and caching is deliberately disabled while sampling so the run shows how unstable the answer is. Variance is reported, not hidden. | One response per model, presented as the answer. |
| Citations | URLs a model cites are checked for reachability before being counted, because models cite pages that do not exist. | Cited URLs listed as returned. |
| When the measurement goes wrong | If a category's search results turn out to be from a different industry, the page says so in red above the ranking and marks the category, instead of presenting a plausible-looking competitor set from the wrong market. | No such check — a wrong-industry result set looks identical to a correct one. |
| When your own content is too thin | If your pages never establish a category, Share of Voice refuses to run and charges nothing, and tells you that is the finding. It will not borrow a category from web research about your brand name. | A category is inferred from somewhere and the run proceeds. |
| What you pay for | Credits, charged per step as it runs, priced on the button before you press it. A finished step is stored and costs nothing to revisit; a failed step returns its Credits. | Monthly subscription with seats, typically starting in the hundreds, independent of how much you run. |
“The common approach” describes the pattern this category has converged on, drawn from publicly documented product behaviour. It is not a claim about any particular tool's current feature set, which is exactly why none is named: that claim would be stale within a release.
What GeoVouch does not do
Published in the same place as the comparison above, because a comparison that lists only strengths is the kind of source we argue models should not trust.
- Continuous monitoring and alerts. Analyses run when you start them. There is no daily crawl, no scheduled re-run, and nothing that emails you when a number moves. If your job is to watch a dashboard every morning, this is not built for that.
- Long-run trend charts. Every result is a dated snapshot and past runs stay readable, but there is no multi-month trend view that stitches them into a line. Comparing two runs is something you currently do by reading both.
- Team accounts and seats. One account, one set of Credits. No shared workspaces, roles, or permissions.
- Integrations. No Slack app, no API for pulling results into your own stack, no CRM or analytics connectors. Results live in the product.
- Promises about outcomes. Nothing here claims to change what an assistant answers. Models change, the web changes, and the same question can come back different next week. What is on offer is a dated, checkable account of what today's answer is built on.
When something else is the better answer
- You need daily brand monitoring across assistants. A monitoring product is the right category of tool. This one answers why a result looks the way it does, not what changed overnight.
- Your site has no product or brand of its own. A blog, a marketplace, or a store that resells other brands has no entity for the analysis to be about — see what you point it at.
- You want a number for a slide. There is a score, but the work here is the evidence under it, and the evidence takes reading.