I have a number of different product pages and i'm interested in seeing how many users view each product more than 5 times. I understand I can do this for one of them with a segment and sequence, but I have too many pages that i'm interested in tracking. Could I do this with a custom metric? Maybe a calculated metric in analytics or data studio?
there's no reasonable way to do that because Google Analytics metrics are reported in an aggregated way and there's no way to introduce some custom conditions like 'if metric X is greater than N for specific user' other than segments.
the only way is to implement custom tracking that would watch for the number of page views for a particular page/product and then send data to analytics when a specific number of page views is reached.
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I'm querying the Google Analytics API, and got a question about combining different dimension and metric scopes. Is it possible to combine a user-level dimension like "Device Category" with a hit-level metric, i.e. "Unique Pageviews"?
I know I can't combine hit-level dimensions like "Page" with session-level metrics like "Sessions". But I can't seem to find any documentation of other combinations.
My gut tells me it should be possible as user-level dimensions are stored in a cookie and then be associated with each hit. But I'd really like to get a second opinion on this.
You can identify valid combinations of dimensions and metrics with Dimensions & Metrics Explorer tool:
https://ga-dev-tools.appspot.com/dimensions-metrics-explorer/
Since not all dimensions and metrics can be queried together, with this tool you can select a dimension or metric checkbox to see all the other values that can be combined in the same query.
[EDIT]
If your request is which dimensions and metrics may be misleading when combining, the answer is... depends on the result you want to obtain and on knowing how to recognize the data. If you want to know which pages are most viewed when a user lands in a specific landing page, you can do this by querying landing pages dimension and page dimension. You will have repeated the landing page many times in the reports (many times how many pages have been viewed from sessions originating in that landing) but this does not mean that it is wrong. Sure depending on what you combine you can get a misleading result, but Google Analytics cannot know if it is misleading for you or if you wanted to do it.
I am trying to get the conversion rate for an individual page just like you get when running an A/B test. I want to find out how many times /page hits the goal of going to /thanks after a visitor is on it. I have tried a custom report but the only page that shows conversion rate stats is the actual thanks page. Any ideas?
You can create a custom segment of your users or sessions, who have visited a given page, or groups of pages. (Look for Conditions under Advanced group of New segment dialog.) You can filter your standard or custom reports for this segment only, and get the information, you are looking for.
I am working with Google Analytics data und during the analysis I saw that I have wierd distribution of visits. For instance, the minimum visits for a page is 89, wich also has the highes freq count in my dataset. Then I have 177 visits for a page with the second highest freq count. I find this pattern every month...
Does anyone know anything about that?
It sounds like you might have some combination of repeated trackers, heavy spam or over-impactful bot traffic.
Repeated trackers an be identified using Realtime reporting: if you click onto the Page Views tag, does each page load trigger only one page view?
Spam can often be identified using the Hostname. Run a custom report looking at Hostnames, and you can see if it's coming from freebuttons.xyz or some equally scummy location.
Finally, bot traffic can be filtered out using an option in the view settings: try setting up a duplicate View with this setting on, and see how different the volumes are.
Suppose I have 65 people that register on January 1, 2012.
I want to find out how many of those 65 people returned to the site that same week. (More generally, if n people signup on date A, I want to be able to find out how many of those n people return in a given date range.)
Is there a way to do this using Google Analytics? If so, how? I am currently getting the user's username for each page hit.
If you only need to track people who sign in then you don't need to get very fancy. You can copy the relevant user attributes, such as sign up date, from your DB to GA using events or session level custom variables.
But if you want to track everyone, including those who don't sign up, then you'll need to use visitor level custom variables (GA cookies).
I explain how to set this up in detail in this post so I'll just highlight the key points here:
First, decide how to layout the data in Google Analytic's custom variables based on your requirements. For example, are you storing retention dates for daily, weekly or monthly tracking? Do you also want to track cohort goals? Partition this data into the available custom variable slots.
Write the cohort data to these custom variables when visitors arrive or achieve goals using Google Analytic's _setCustomVar function. Setting the fourth parameter of that function to 1 indicates you want to do visitor-level (cookie) tracking.
For each cohort you wish to analyze, create an advanced segment in Google Analytics. Using a regex expression in the condition will give you the flexibility to segment for interesting cohorts. ex: "All users whose first visit was the week before Christmas".
Analyze the results with reports by specifying a date range and the corresponding cohort-sliced advanced segments. Another option is to extract the data using the Google Analytics Data Feed Query Explorer or their API.
Once you've put in the work your new visitors will be stamped by their first visit date and nicely fall into each daily or weekly retention bucket. This is what it might look like if you were tracking weekly retention, for example:
This is not a full solution, but here are some points on how I would approach this problem with the help of Google Analytics:
You have to make sure that you somehow store the registration date of each user, either in your database or in a cookie. Then have a look at Google Analytics Event Tracking. You could for example set up a new category based on the registration date. On every page load in your page, you then have to set up this event tracking call, for example like:
_trackEvent("returns", "2012-01-01", "UserId:123123123")
This way you will receive all page views for users that registered on that particular date. To add a date range in this, you have to make sure that these events only get fired for the number of dates after the signup (e.g. 7 days).
After your date range, you will be able to see how many page views and how many users returned - you even know which users came back.
I believe custom variables in Google Analytics can only be used to track the distribution of different values for that variable over time.
Suppose I have a forum and want to track the total number of posts made in that forum. Could I track them over time with Google Analytics, too? And how?
Custom Variables are a user-based dimension. So, traditionally, instead of measuring forum posts, they'd instead identify users who post on forums. That doesn't seem like what you're trying to measure.
Instead, you should consider looking at Event Tracking. Specifically, they allow for the tracking of 4 separate data points (per hit): 3 strings and a integer value.
So, you could use this to track when posts happen, or when comments happen on those posts, and then aggregate the values by whatever dimension you like using the API. You'd just need to bind the event to occur at the times you intend, with the data you want to track.
So, an example event call for you, tied to whenever someone posts a comment on a forum topic:
_gaq.push(['_trackEvent', 'Form Posts', 'Comment', topic_name, 1]);
You could then use the API to query particular views to tabulate whatever aspect of the event you want to aggregate. You can simulate those calls with the Google Analytics API Query Explorer. In this example, you could get number of Comments per day using Dimension set to ga:date, Metric set to ga:totalEvents, and then set the filter field to ga:eventAction==Comment