Turn repeated answers into a readable report.
See the structure of a monthly AI visibility dashboard. The ZIP includes an invented example, source data and a small builder you can run locally.
A simple record becomes a useful trend.
The dashboard is most helpful when you ask the same questions in later months and record the answers by hand. One point alone does not prove a trend.
Everything is inspectable and editable.
How to run the sample builder and where to put your own data.
A Python 3 script using the standard library to turn the files into HTML.
Invented client facts, questions, answer records, signals and the resulting dashboard.
python3 build_dashboard.py sample-clientMetrics with their context attached.
The share of recorded answers that include your business, for the sampled questions.
A table shows which assistant named you for each prompt, including gaps.
Incorrect details are recorded so the fix list can point to something specific.
Optional data from your Search Console, Bing, analytics and crawler logs can add context.
The template's business and every displayed number are invented. Its layout shows the reporting format, not a customer result.