Visibility Audit Co. features explained
Visibility Audit Co. feature overview
Visibility Audit Co. focuses on AI search visibility audits for SaaS companies. The service looks at how products show up when people ask ChatGPT, Perplexity, and Google AI Overviews for recommendations in a category, then turns that into a ranked list of fixes. For a SaaS team, the practical question is not just whether the brand appears, but whether it is named correctly, cited alongside the right competitors, and supported by the kinds of pages and structured signals AI systems tend to use.
A core part of the service is prompt testing. Visibility Audit Co. runs buyer-intent prompts such as “best X for Y,” “X alternatives,” and “X vs Y” across multiple AI engines, and it runs them on two separate days because answers vary. The audit then records how often the brand is named, which competitors appear instead, and which sources each engine cites. That matters because AI answers are typically short and selective, so visibility depends on being present in the few results those systems choose to surface.
The audit also maps the cited sources behind the answers. Visibility Audit Co. identifies the review sites, comparison pages, and forums that the engines rely on, which helps show where a brand is missing from the wider information trail. Alongside that, it measures share of voice against three competitors chosen by the customer, so the report is not just a snapshot of one brand in isolation. It shows relative presence in the categories and prompts that matter most.
Another feature is the AI readiness scan. Visibility Audit Co. checks public signals such as crawler access, llms.txt, schema, sitemap, and crawlable text. The homepage specifically calls out crawler access for bots such as GPTBot and ClaudeBot, and it notes schema types like Organization and FAQPage. This piece matters because a brand can have useful content on its site and still be harder for AI systems to read if technical access or machine-readable structure is missing.
The output is not just diagnosis. Each finding becomes a fix ordered by likely impact and effort, written so an internal team or Visibility Audit Co. can act on it. That makes the audit more usable than a raw list of observations: it tells a team what to change first instead of leaving them to sort through the findings themselves.
For readers who want a lighter entry point, the $49 Snapshot is the smaller offer. It includes 10 buyer-intent prompts, a scan of AI readiness, and a PDF with top fixes delivered within 48 hours. The larger recommended audit expands that into 40 prompts across five engines, share of voice versus three competitors, a cited-source map, a full technical scan, ranked fixes, and a recorded walkthrough. The site also offers monthly tracking, which reruns prompts and reports on what changed over time.
What the service is designed to answer
At a practical level, Visibility Audit Co. is built to answer three questions for a SaaS team: whether AI answer engines name the product, which competitors they prefer instead, and what needs to change to improve visibility. The service stays on public data, so it is aimed at understanding and improving what AI systems can already see and cite from the open web.