We report results the way an operator would.
No vanity metrics, no cherry-picked screenshots. Here's exactly how we define impact, and we only publish numbers that are real and approved.
How we define and report results.
Metric tree
We map your North Star down to the inputs that drive it, so every result ties to a number that matters.
Baseline
Before we touch anything, we record where you are. No baseline, no honest claim of impact.
Forecast
A 4-week rolling forecast sets the expectation. We report against it, including when we miss.
Attribution
We're explicit about what's correlation vs. cause, and what we can and can't attribute to our work.
We pointed this at our own projects first.
Before we sell it, we run it on ourselves. Here's what AI-visibility work did for two products we operate, measured in real AI citations, not vanity metrics.
AI citations in 3 months
157 pages cited on average across AI answers, from a near-zero base.
AI citations in 3 months
12 pages cited on average as AI engines started surfacing the site.
Source: Bing Webmaster Tools, AI Performance (Microsoft Copilot & partners), trailing 3 months.
These are first-party results on products we operate, not client case studies. We won't fabricate those. As founding clients hit milestones, their results, with baselines, forecasts, and attribution, will appear here too.
See it on your numbers.
The AI Visibility Audit shows where you stand in AI answers and gives you a forecast and a 90-day plan, before you commit to anything.