The fastest way to waste money in influencer marketing is to approve creators too quickly. I know because the first versions of my creator review process were basically vibes plus screenshots. The account looked polished. The follower count looked big enough. The average views looked decent. Then the campaign underdelivered and everyone acted surprised. That is what finally pushed me into building a more structured audience quality audit. Not a giant enterprise platform. Not some fake-AI fraud detector that claims absolute certainty. Just a workflow that helps answer a practical question before money goes out: does this audience look believable enough, engaged enough, and useful enough to justify the spend? This post is how I would build that audit today, what signals I trust most, and how I would wire it together in JavaScript and Python using public social data. The Goal Is Not Perfect Fraud Detection This is the first thing worth getting straight. You are not trying to prove every follower is real.…