Most sites I look at aren't broken. They're just carrying a decade of decisions nobody
revisited — orphaned pages from an old launch, three URLs competing for the same term,
a migration that quietly dropped canonical tags, thin category pages absorbing crawl
budget that should be going to the ten pages that actually convert.
A traditional audit finds all of that and then hands you a spreadsheet with
800 rows sorted by error type. That's a data dump, not a decision. The
hard part isn't finding issues — modern tooling finds them in minutes. The hard part is
knowing which twelve to fix first, what each one is worth, and who on your team can
actually ship it.
That's the part I do. My background is revenue operations, so I read a site the way I
read a pipeline: where is the leak, what does it cost, and what's the cheapest
intervention that closes it. The AI layer handles the volume. The prioritization is
mine.