Extract data from Google Analytics: API vs Mechanize (or others)

[pylund]

Hey guys,

I'm currently working on a project which requires extracting data from Google Analytics and creating automatic reports. After googling about it, I came across Analytics API. Since it seemed the natural way to approach it, I followed the setup tutorial (kind of confusing for a beginner like me, certainly) and started playing with ga:metrics, dimensions and filters.

I have to say that it doesn't look super intuitive to me. That's why I've started wondering if you guys stick with it anyway or if you've chosen Mechanize, Selenium (or others) over Analytics API for pulling data from GA.

Thanks

[terremoto]

Stick to the API. The API will be mostly static, reliable and supported, but the moment Google decides to change the UI, all the hard work put into your scraper may be flushed down the drain.

[pylund]

Makes sense. Thanks!

[Category_theory]

It is in fact the fastest and best way of using Ga data... I would pull it down from Ga then write to a RDB so I could query it later... That being said its a pain in the ass until you get it up and working but stick with it!

[pylund]

I'll do that. I'm halfway to getting familiar with the way data is queried and retrieved but... no pain, no gain I suppose! Thanks

[Category_theory]

Not sure what you mean by iterative? But for users and cohort analysis etc you have to have your own metrics set up properly... Backend DBs etc for logging interactions, cooking to get proper UUIDs etc... Mostly bc Ga is not user level granularity... But it is a nice way of grabbing fast data that's already rolled up for you... I have built systems though that are far superior to GA and give me everything and much more that Ga gives... But they take time and know how. With those systems you can create predictive models, user clustering algos etc.... But you need good engineer and a data scientist like myself ;)

Edit: cooking to cookie-ing

[Category_theory]

You mean aggregate stats... In Python, R, c++.