Firebase provides a default event type for posting game scores. It includes parameters for the game level, character and score that was posted. However, viewing this event in the Firebase analytics console I can't see the level/character/score data anywhere, though I can see the total number of "post score" events.
How can I analyze e.g. the distribution of scores, or the average level achieved per game, etc?
Not all predefined event params are reflected in reports. You have a couple of options for further analysis: you can create audiences with filters based on the param values you're interested in, or you can use BigQuery for more in-depth analysis of your data.
EDIT: You can now set up custom parameter reporting.
Related
Experiencing problems with Funnel Explorations while user_id is implemented. (see screenshots, for the difference in user counts.)
I was told by Google support that the funnel exploration will not show any events where a user_id is assigned, due to the reports using "TVF" + "Gaia" events, whereas the funnel exploration does not include Gaia (user_id assigned) data. I could not find any documentation online related to this.
I am trying to find clarity on:
Is this really the correct functionality for funnel exploration, to exclude data associated with a user_id?
Does this affect all explorations or only certain types?
We want to continue to run our GA4 property with user_id implemented, but how can I do funnel exploration and generate visuals to share with my team?
view from engagement>events report
view from exploration>funnel
I verified the correct data is flowing into the GA4 property, I can see the correct number of purchase events and users in the Engagement>Events report, but when viewing in funnel exploration I am only shown a tiny fraction of users for the same date range.
We use Firebase A/B test product for our mobile apps. We need to reach the parameters of our events and make a deeper analyze. We have worked with BigQuery before for this, but it requires a lot of effort.
Let me tell you briefly about our problem:
Let's say we have an event called add_to_cart. We want to look at the number of times the add_to_cart is triggered from a specific screen in the A/B test results. For example, those whose firebase screen class is category_page. This data can be accessed by writing a query over BigQuery, but create extra effort for different needs.
Is there a short way or tool about doing analysis by event parameters?
As we find Firebase's reporting and analysis insufficient, we will decide to use a different tool. If anyone encounters such a problem, it is possible to make a deep analysis through BigQuery.
Another way you can use Audience as a hacky way.
1. Go to Custom Definitions section and create a custom definition.
Your scope should be "User". Select firebase_exp_<N> as the User property. Because Firebase defines a property for each user it adds to the experience. You can find the <N> number from the link on your A/B test page.
E.g. your A/B test link is like: https://console.firebase.google.com/u/0/project/your-project/config/experiment/results/20. The <N> number is 20 and user property is firebase_exp_20.
2. Create Audience for each control group
Create a new audience according to this created dimension value. A value of 0 corresponds to Baseline. Each control group after that continues with consecutive numbers. (1,2,3..)
3. Go to Analytics
Go to Analytics and do your analysis for each control group with these Audiences.
I hope it helps.
We would like to build indicators that provide more useful information than "averages", e.g. instead of having to rely on "average time on page", we would like to create an indicator like "unique users that spent more than [threshold] time on page".
In order to do this, we need to know, whether Google Analytics is storing information on "user session" in connection with "time on page" in its raw data? And if it does, whether this raw data is accessible and can be filtered?
Another situation where the mentioned storing and filtering might come in handy, is the following: if different activities (e.g. post comment, click like, ...) are all tracked with regard to user session, we could build an indicator like: "unique users that performed any of the following: comment, like, ...".
Any reply, remark or comment is highly appreciated.
Raw data is not accessible in Google Analytics.
The closest you will get, if you have a GA360 account, is the BigQuery export, but even that is not "raw" in any meaningful sense (although it is more detailed). You could create a custom sendHitTask to send raw data to your own database.
But raw data would be not useful to you, since GA does not send session data with the raw data. Since 2012/the introduction of Universal Analytics, sessions are entirely calculated on the Google servers - the aforementioned BigQuery export would actually be more useful, since data there is already sessionized, but this requires the paid-for version of GA.
Usually there are workaround for most use cases - i.e. "more than time x" can be viewed as categorical data instead of as metric, so if you send a timestamp in seconds (starting with 0 for the first page view) with each hit to a session scoped custom dimension GA will only retain the last value per session. Then you can filter by all users where that dimension is bigger a given value (you need to use a regex, since you cannot compare dimensions as numbers, and I recommend to create "buckets" instead of having too many discrete values).
But to answer the explicit question, there is no access to raw data (unless you store it yourself) and it would not contain session data in any case.
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}
Tools like Mixpanel, KISSmetrics and others support cohort analysis out of the box but I've heard that you can do this with a bit of effort in Google Analytics as well. How do you set this up if you want to track, say, the daily and weekly retention of your visitors?
Google Analytics can do a lot but retention analysis is one of it's weak points. Since it tends to focus on visits (as opposed to visitors) you'll need to configure the cookie tracking yourself using Google Analytic's custom variables. Having said that, it's not too hard to get a simple solution running quickly.
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. If you need more detail there's a full walk through on my blog:
How to do Cohort Analysis in Google Analytics.
This really interested me so I did a little research and basically you have to customize the GA javascript in the pages to upload custom variables into google.
Once you have done that you need to go to "Advance Segments in Google Analytics" and select your custom variables. Here is a detailed description on how to accomplish this:
Hacking a Cohort Analysis with Google Analytics