How do I attribute results when the data has gaps?

You can assign credit to your channels, but the real path a customer takes touches many things, and half of it is not even recorded. So your conclusions come out muddy. That is not carelessness. It is the honest state of messy, incomplete data. Perfect attribution does not exist, and chasing it will only exhaust you. The useful question is not who deserves exact credit but which few things clearly matter and which clearly do not. Directional truth, held honestly, beats false precision every time. Name your biggest data gap out loud and stop pretending your model sees through it. Then make your call on what you do know, and say plainly where you are guessing. Honest uncertainty is worth more than a confident number built on air.