I'm tracking events on my websites and in those events I'm sending along an event value. The event value is how many times a person has done that particular event, so it could be a number from 1 to infinity.
I'd like to figure out where on a bell curve (or something like that) the event values are. I'd like to somehow find the distribution of the event values, but Google Analytics only gives me the average values.
How would you go about finding the distribution of event values in Google Analytics?
You could use metric-Filters in a segment to get the number of Events for each value.
If you use the API to extract the data you can write a loop to get every possible Value.
Still that is not the best solution. If you want to do this more than ones it would be better to add the value as Event-Label or Event-Action. GA saves this as a Dimension and you can easaly export and analyze this.
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I am setting up a report based on a calculated metric in Google Analytics. I would like to divide the total number of a specific event action with the number of users. Something similar to:
{{Total Events (MyEventCategory / MyEventAction)}} / {{Users}}
I have tried to find documentation on this feature. The autosuggestion when creating the calculated metric do not suggest the above is possible, but I would like to shout out and hear if anyone out there know whether or not this is possible.
We have a Google Analytics account set up to track downloads on certain files. When you create a report with, for example, Event Label (user) as the primary field, and Event Action (file name) as the secondary field, GA will say that the number of unique events is 168. When you add up the numbers in the unique events column, however, they add up to 322. Exporting the table as a CSV file and viewing it in Excel will also give you 322.
I should also add that there are 270 rows in the table, so for there to be 168 unique events, that would mean some user/file combinations would have 0 unique events, which doesn't make any sense.
Can anybody shed some light on why this is happening?
There is a lot of confusion with Unique Events metric. Instead of counting a number of times an event with unique combination of category/action/label happened, GA was counting unique combination of every dimension included in the report!
Finally that metric is deprecated now and renamed to Unique Events (legacy).
Instead we get a real Unique Events (new) metric which behave like expected.
More explanation in my blog post
http://www.internetrix.com.au/blog/google-analytics-unique-events-are-dead-long-live-unique-events/
In all Google Analytics custom reports, the Unique Events field actually reports the number of Visits (or sometimes a slightly higher number).
Built-in Google Analytics reports will show you the correct number of Unique Events.
It's a bug, plain and simple. I reported it to Google back in August, but it's still broken.
The number in the Google Analytics standard reports can be explained...but as Aaron pointed out, it sure looks broken. I wrote an article explaining it all:
http://www.analyticsedge.com/2014/09/misunderstood-metrics-unique-events/
So, my need is I submit user score to Flurry, in order to gain information about how much the average score that user can achieve.
I have setup logEventWithParameter
Event Name = "Game Result"
Parameters = {"USER_SCORE",""}
And then I look into my flurry dashboard, it doesn't count the average value of USER_SCORE parameter. I think I have mistaken about how Flurry work in this case.
Found the answer! at the Flurry`s FAQ written:
Are there limits to the number of Events and Parameters I can create? Yes, there is a limit of 300 Events for each application.
Each event can have up to 10 parameters, and each parameter can have
any number of values.
Note that we currently display only the top 500 parameter values for
any Event in the Flurry portal. If you want to track something like a
score, which can have an infinite number of values, we would recommend
creating a distribution for your parameter values.
Unfortunately, Flurry doesn't support this kind of use case. So I have to create score distribution group, something like SCORE_GROUP = {0-5000, 5001-10000, >10000}
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