I've set up a few experiments with Google Analytics using its experiment interface and everything seems to be working fine, but I haven't been able to find the answer to how Google Analytics attributes reached goal to the variations, is the attribution session-based or user-based?
Here's a scenario:
User visits one of the page variations included in the experiment during a session, does something else on the website and closes it.
The next day the user comes back, opens my website in the same browser and completes the goal (without visiting the experiment variation page)
The question is: will the reached goal still be attributed to the variation page the user saw during the previous session or will it be discarded and won't be attributed to any of the variations, since the user didn't see the variation in the same session he completed the goal.
The reached goal should still be attributed to the variation page:
A user is considered part of an experiment once he or she has seen the
experiment page. For example, if a user sees the experiment page, then
comes back the next day, the second visit is counted, even if the user
does not view the experiment page again.
https://support.google.com/analytics/answer/6112437#
Related
Due to the way GA tracks exits, it is actually not possible out of the box to get "time spent on page" metric from GA if the user does not navigate to the second page of the site.
I need a solution that meets the following requirements
Will work even if the user does not navigate to a second page (leave after visiting landing page)
Measure accurately time spent on page (taking into consideration of browser focus and idle)
Bonus - has an ability to not count towards bounce rate if the user stays for X seconds on page
You can try to send a virtual pageview on exit intent. In this way the landing page will not be the exit page.
For Example, We have two pages home page and contact page and both have their own variants in google optimize. So when visitor visit homepage and get the new variant from google optimize then it should not see a new variant of contact page when visitor redirects to contact page and vise Versa. Hope you get the point.
One approach is to track which variations users get into using cookies and target accordingly. So, let's say your user lands on the home page and is bucketed into the new variant. You use custom JS to drop a cookie along the lines of user_has_seen_new_variant=true, and in your second experiment you target based on whether or not people have that cookie.
Another approach would maybe be to combine your experiments into one, where you're targeting both pages. That way you would have control over what people are seeing on either page.
So,
I have a blog with a "demo button" with leads the user to a sign up page.
On sign up page, the user fill the general entries. Then he is brought to a payment page to enter his card details. and then from there he is taken to a confirmation page.
Now, I want to track every page. Basically, whether any user coming from a blog becomes a user or atleast how far he goes before closing the tab
Use Enhanced E-Commerce Tracking.
The EEC in Google Analytics lets you assign step numbers to the various steps in a checkout. It then creates a custom funnel report (remember that EEC must be enabled and configured not just in your code, but also in your view settings) that show how many users completed the checkout and how many dropped of at each step.
I am in the process of setting up enhanced Ecommerce for GA and have had a few requests of additional of what else the client would like to see in their reports. Once of which is;
"We no longer have paginated pages,instead, the pages automatically
load more products when a user gets to the bottom of the page. How can I track how many times the does this?"
Is there a way (using event tracking maybe?), that we can track every time a the page reloads new products as the URL is no longer changing. In order to compare with data from before this functionality change, it would be useful to see what the equivalent number of pages a user is seeing, ie, how many times the page adds new products to the page. Any code examples would be really helpful too.
Thanks,
Roxi
I would like to track where users originally came from when they make a purchase on my site so I know which keywords are more profitable and which websites are best for advertising.
an example is a user is on my site with my google analytics tracking code which has details of where they came from, and then decides to upgrade. they leave my domain to go to my biller (2checkout) complete the purchase and return to my thank you page.
I have transaction code and analytics code on my thank you page and the transactions are showing up with the correct product/amounts in GA however there is no other data and in my reports the referring url is always my biller or a credit card companies authorisation page.
i can manually connect which customer is which by saving their referring data when they first come to the site and then matching it up after they make a sale, but I would like it to show up in my google adwords / analytics account where it is easier to manipulate the data and see trends.
if anyone can help me with this annoying issue I would be vbery greatful, but I fear I may end up living off reports I create and then matching them up with adwords manually :/
One thing you can do is have a click event trigger a custom variable. When the user clicks on whatever link that takes them to your biller, have the custom variable trigger with the information you want to carry over (like the current page URL, some campaign name, whatever). Specify the custom variable's scope as Session or Visit so that it get associated with the thank you page.
http://code.google.com/apis/analytics/docs/tracking/gaTrackingCustomVariables.html
An alternative is to do campaign tracking:
http://www.google.com/support/analytics/bin/answer.py?hl=en&answer=55540
That is more or less the same principle as the first suggestion, but with using specified URL parameters. Depending on how your pages are actually coded, you may need to push a virtual page view with the campaign code(s):
http://www.google.com/support/analytics/bin/answer.py?hl=en&answer=55521