Proof
What proof does Awesome.Digital use?
Awesome.Digital is being tested on owned sites first, so the product has to produce recommendations that can be shipped, rerun, and measured.
Quick answer
The proof model is simple: scan an owned or client site, identify the real blockers, ship fixes from the diagnosis, and rerun the audit. A recommendation only matters if it changes what gets fixed.
Current proof posture
Owned sites
Dogfood first
QNTx Labs, Awesome Digital Marketing, Jeff Hopp properties, and this site are used as test surfaces before broader positioning.
Fix cycles
Diagnosis to shipped work
The scan is valuable only when it changes the fix order. Recommendations are reviewed for whether they matter, make sense, and are missing anything.
Measurement
Rerun after fixes
Before-and-after audits show whether structural fixes improved content depth, answer readiness, trust signals, or discoverability.
What we can say now
The tool has already found useful gaps on owned and partner surfaces: thin public content, missing answer-first structure, weak freshness signals, incomplete llms.txt coverage, and proof layers that were obvious to humans but not exposed to crawlers.
The next proof layer will be more public: before-and-after pages, example snapshots, and short case notes showing the blocker, the fix, and the audit delta.
What proof is still missing?
- Public example reports with sensitive data removed.
- Before-and-after audit deltas for owned-property fixes.
- Named customer stories when the work is approved for publication.
- A deeper methodology note for how operator diagnosis differs from generic audit templates.
Start with the live scan.
Run the free preview, save the private growth snapshot, and use the evidence to decide whether a review or diagnostic sprint is worth doing.