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All of my models are 'data-driven' in that they are computed directly from the visit & event data. I don't currently have models that change based on the data, but I could easily add them if you're interested in helping me define how they work.

I find one of the big problems with GA is that it doesn't show you the actual people that are included in the final attributed credit per channel/campaign, does it? Without this, it's quite a leap of faith.

I'd love to chat with you about your current practices; I still think there's still tons of room for improvement past the current models. For example, I'm experimenting with a model that gives credit to pages in addition to traffic source to help justify the cost of content production / optimization of which content is working and which is not.



I'm using "data-driven" synonymously with "dynamic" in this case, which is indeed the changing model based on the data using machine learning.

I haven't played with it to this extent, but can't you get a GUID of some sort using the GA API[1] or custom dimensions? I haven't tried it personally and I know they restrict some of the data so this may not be possible.

I do like that you are factoring in content into this. The regular way of doing that is to create some custom channel groupings in GA (probably some other ways) but content really deserves a place in the funnel when looking at attribution. And you are right that content marketing is hardly free and has a high cost associated with it that is hard to prove ROI on.

Definitely would be open to chatting. I work in Mountain View if you're in the area and that would be easier.

[1] https://developers.google.com/analytics/devguides/reporting/...




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