I am working on a pre-existing Google Analytics set up and having to develop an understanding of how certain users of our website are interacting with the site.
An important component of this will require user-journey analysis to understand how, say, a premium user interacts with the site compared to a free user compared to someone who isn't logged in at all.
I understand that I can start using User-ID to start discriminating between logged in users and those who are not; however, I am unsure of how to handle the distinction between free and premium users.
Is there any way to add additional information to User-ID to include a "User Group"? Or is there an alternative recommended way to create these segments in Google Analytics?
While it is certainly possible to pass something along with the User-ID to identify the premium and the free users. Example: P-007 vs F-006. I'd recommend you to look into Custom Dimensions(CD) instead.
I'd set up a User Scoped CD and along with your sign-in event push the string "free" or "premium" along with it.
Reason for doing this is that when you set the User-ID, the user is identified by it across multiple devices. If a user starts with free, F-007 and then later converts to premium, P-007, then the user suddenly becomes a different user to GA. Using a CD will allow you to keep the ID the same while converting the user to "free" or "premium" without losing the client.
Related
I want to track how many users login/Sign up using one tap Sign up feature
Sorry, we don't provide any externally available metrics for this, you'd have to keep track of it using your own analytics systems. e.g. in Google Analytics, track when user signs in or up based on the results from your backend
I am setting up Google Analytics Accounts for a Product which have multiple builds as frontend for same user base.
So we have one Product called X and have:
Web Build
Mobile Web
Android App 1
iOS App 1
Android App 2
iOS App 2 6.
The main point is identical APIs and User base is used in all platforms and apps. So if we have a user John Doe he can login in any of the web or apps.
We want to extract following information from Google Analytics.
Under User ID feature want, sessions aggregations of that user around all build and apps, but identifiable. So I can know that user John login to web yesterday and used mobile app today.
Each user belong to a customer (company) in our system. So want to segregate all information based on companies.
I already have achieved point 2 by creating a custom dimension in Google Analytics and believe that's the best way to do it.
Now need suggestions from Gurus on how to acheive point 1 using Google Analytics.
Either use single account and single property for all builds and apps
If yes, then how to identify those apps and builds in sessions
If I use multiple properties/apps in GA account then how to aggregate user sessions among all?
Looking forward to hear how guys around hand or should have handled this scenario. Cheers!
This question is extremely broad, IMO any answer your going to get is going to be primarily opinion based. So here is my opinion and a little extra info to boot.
The first issue you are going to have is that there is a difference between Mobile google analytics accounts and web analytics accounts. The two do not mix. Mobile analytics accounts insert screen views with a screen name. While web accounts insert PageViews with a document location.
There is no way to analyze between two different Google analytics web properties. Unless you intend your android and ios apps to run as websites and send it like its a webpage its not going to work. You could potentially download the data into your own system or big query and analyze it there. Comparing your custom dimension to see what the users have done differently. I would wonder at the quality of the analysis you will get as there will be no real way for you to compare the data and match it up beyond using your custom dimensions user id and possibly date.
I am adding this because I am not sure what your saving in your custom dimension.
The second issue you are going to have is tracking. Google analytics TOS does not allow you to send any identifiable information to Google.
The Analytics terms of service, which all Analytics customers must adhere to, prohibits sending personally identifiable information (PII) to Analytics (such as names, social security numbers, email addresses, or any similar data), or data that permanently identifies a particular device (such as a mobile phone’s unique device identifier if such an identifier cannot be reset).
You could for example send your companies customer id for John as a user_id but user_id is an internal valuable used for internal processing this is not something you can extract out via the api.
The User ID enables the association of one or more sessions (and any
activity within those sessions) with a unique and persistent ID that
you send to Analytics.
To implement the User ID, you must be able to generate your own unique
IDs, consistently assign IDs to users, and include these IDs wherever
you send data to Analytics.
For example, you could send the unique IDs generated by your own
authentication system to Analytics as values for the User ID. Any
engagement, like link clicks and page or screen navigation, that
happen while a unique ID is assigned can be sent and connected in
Analytics via the User ID.
The best you could do would be to create a custom dimension and send that with every hit username=johnscustomerId. Which you appear to have already done. This is what I have done in the past and it works perfectly well.
I am trying to see if its possible to use Firebase to show the number of active users in real time on my shopify site. I also want to show the active users on a single product page if thats possible.
I see the Firebase example code for Presence but it looks like this only works for logged in users. How do I or is it even possible to show the real time user count ignoring whether someone is logged in or not...similar to the real time google analytics count?
The Firebase presence samples (one, two, three) all rely on the Firebase onDisconnect() handling. This method allows you to specify write/delete actions that should happen to your Firebase data on the server, once it detects that the connection to a client has been lost.
A system like this can work fine with using Firebase Authentication, but you need some way to uniquely identify each user. This can be any sufficiently random identifier, or for example the uid generate by Firebase's anonymous authentication. Both serve the same goal: authentication without identifications. That last approach is somewhat similar to how many analytics services work: they give you a unique ID when they first see you and then track you by that ID.
Can you set up alerts in Google Analytics to flag potential PII/NPI such as name, email address, billing address, billing details etc.? If so, how?
First I have do say I do not understand the downvote(s). For example I have seen applications with user logins where a full name was part of the page title - combined with time based dimensions that gave profile that say which user looked at what page at what time, and that would be clearly illegal. Even worse I have seen a case where security tokens were transmitted to GA that allowed access to secured resources. So clearly accidental transmission of PII to Google Analytics is a real thing.
Unfortunately there is not much you can do about it. You can either do a custom report with relevant dimensions and have it sent to you for a manual audit, or pull them via the API and have them programmatically examined via regular expressions that look for patterns like e-mail addresses etc. But by the time you can do that it is already to late, the data will already be permanently recorded in the GA property.
You have to stop this before the data is collected - if at all possible already in the website (via form validation etc), or use Google Tag Manager with custom javascript variables with validation rules, or filters in the analytics view (the latter being cumbersome and not very promising for this purpose).
The good news is that GA will not suddendly start to track PII on it's own. So you only need to check if your GA account tracks PII when you set up the account. Collect a few days data, validate that everything is okay, make changes as necessary and after all flaws are straightened out copy the view to start data collection from scratch and drop the old view if it contains PII.
The docs describe the clientId as:
This anonymously identifies a particular user, device, or browser instance.
https://developers.google.com/analytics/devguides/collection/protocol/v1/parameters#cid
It can be used to send server side hits to analytics while still tying them to a particular user.
There is also a feature in closed beta called userId, which you will be able to pass once a user has authenticated: https://developers.google.com/analytics/devguides/collection/analyticsjs/user-id
userId is fairly self-explanatory. However, UA also allows you to pass your own clientid if you choose to. For developing CRM type tools, can one just associate the clientid with a user in the same way that you would with a userid? The goal is primarily to be able to track offline interactions and connect them with visitors in Analytics.
maembe,
clientID is a random number generated by Google Analytics, and keep in mind it's always required and its value should always be a random UUID (version 4) (you could technically use your own, but I am not sure how practical and reliable this would be). Most importantly, you can easily access it with predefined get function (see documentation).
For your needs, this is exactly what you should do -- if someone sings ups, store ClientID in your CRM and then if there is any offline purchase, record the transactions with measurement protocol using the stored clientID. Google Analytics will then make the link (attribution) with that visitor and you will see this in your reports. Also, take advantage of newly available custom metrics and dimensions which can store pretty much anything you want (think of customer segmentation etc.). Beware of storing PII though.
Hope this helps :)
I am curious how UserID is going to work, it might change everything, but for now, I wouldn't rely on it as there is very little information available.
This Analytics support page now states the differences between Client ID and User ID - https://support.google.com/analytics/answer/6205850?hl=en#clientid-userid
Essentially client IDs represent unauthenticated users, and are automatically randomly generated.
User IDs represent authenticated users, and must be set manually.
It's worth noting that user IDs cannot be things like an email address, or other data that would allow Google to identify the user
You will not upload any data that allows Google to personally identify an individual (such as certain names, Social Security Numbers, email addresses, or any similar data), or data that permanently identifies a particular device (such as a unique device identifier if such an identifier cannot be reset).
If you upload any data that allows Google to personally identify an individual, your Google Analytics account can be terminated, and you may lose your Google Analytics data.
Taken from: https://developers.google.com/analytics/devguides/collection/protocol/policy
I'd imagine User ID is designed to differentiate the behavior of an authenticated user. here