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.
Related
I’m wondering if anyone can help me. I’m currently working on a project which involves trying to understand customers who have abandoned one of the stages within a checkout but then returned to the site at a later stage and converted. I would then break this down to the number of days before they returned. I’ve tried creating segments however the data doesn’t seem to be making sense. Has anyone any idea how I’d go about this? Is this even possible in GA or is this something I can only accomplish in BigQuery if at all?
Your help will be very much appreciated.
Google Analytics(GA hereafter) is counting a visitor as a new or returning user by persisting cookie values in client side(in the browser). So once a user is visited, It stores an id which is specific to that user (actually this user means the browser which had been used to visit the website). So when a user visits the site for the first time, GA will store a specific id in a GA related cookie in the client side. If the user visits the website again later in another session, then GA check if there is a client.id for that user stored in the client side. If it found then that user is count as a returning user or New user otherwise.
In Google Analytics, goto Audience -> User Explorer. In there you can see an aggregated view of each user(client.id) interacted with your website and clicking on one client.id will show each user's activities with the website(differentiated by sessions) and will show all the sessions related to that user with the information like time, URL and some other dimension values.
Also if you want to separate out New users or Returning users from each other, you can create a new segment with a condition checking for the User Type dimension against the values "New Visitor" or "Returning Visitor".
To measure returning customers after an abandonment and converted, you can create a segment as follows,
It seems that it's not possible in GA.
There are no metric like "Days between abandoned funnel and conversion" (only "Days before transaction" - between acquisition day and transaction day). So you need a date for abandoned funnel and a date for conversion separately: i.e. you need two reports.
I know solution, but Excel or smth like this is needed if you want to calculate days before conversion.
At first you need to have Client ID as a custom dimension.
Then create custom report contains dimensions Client ID and Date and metric [Your Goal] Abandoned Funnel (Goal with Funnel needs to be set).
And the second report - Client ID, Date and [Your Goal] Complection.
And to merge these tables using Client ID parameter.
I'm looking to download hit data from a Google Analytics view for a small period of time that includes unique ID for a session and URL that was viewed. I believe I could do this going forward by setting something in Google Tag Manager to a Custom Dimension, but I was looking to avoid that (we have a good number of custom dimensions) and because I wouldn't be able to go backward.
Is it possible in the free version of GA to do something like? I picture the output being the URLs in my x-axis and my users in the y-axix with counts.
I'll be looking to take this data and do a cluster analysis to determine user behavior types.
Nope. Google Analytics does not expose a user specific id via the API or via data exports in a standard account (in GA360 you could use BigQuery to extract the client id).
You either have to set up a custom dimension (as you said this does not work for historic data), or try and use calcuated fields in Google Data Studio in the hope that if you aggregate enough different dimensions into one field you will end up with something specific per user.
I'm trying to get all unique visitors for a selected time period, but I want to filter them by date on the server. However, the sum of unique visitors for each day isn't the number of unique visitors for the time period.
For example:
Monday: 2 unique visitors
Tuesday: 3 unique visitors
The unique visitors for the two days period isn't necessarily 5.
Is there a way to get the results I want using the Google Analytics API (v3)?
You're right that Users aren't additive, so you can't simply add them day by day. There are several ways around this.
The fist and most obvious is that if you've implemented the User-ID you should be able to straight up pull and interrogate the data about which users saw your site on which days.
Another way I've implemented before is to dynamically pull the number of Users from the Google Analytics API whenever you need it. Obviously this only works if you're populating a live web dashboard or similar, but since it's just the one figure you're asking for, it wouldn't slow down the load time by much. Eg. if you're using a dashboarding tool such as Klipfolio, you may be able to define a dynamic data source, and query Google whenever you needthe figure (https://support.klipfolio.com/hc/en-us/articles/216183237-BETA-Working-with-dynamic-data-sources)
You could also limit the number of ways that the data can be interrogated, and calculate all of them. For example, if you only allow users to look at data month-by-month or day-by-day, then you only need those figures.
Finally, you can estimate the figure with reasonable accuracy by splitting it into two parts. New Users are equal to New Sessions (you're only new on your first Session), which is additive, so that figure can be separated out and combined as required.
Then, you could take a rough ratio of new to returning Users (% New Users) from, say, 1 year of data, and use that with the New Users figure to generate an average on any level.
Is it possible to export a list of all page views, with timestamps, out of google analytics?
Currently I can see page views per day, but not specific times for each view. I do see real-time data as it comes in, so I assume the time for each view is being stored.
If not, how might I go about sending that data when I report the page view in a way that will make it accessible in the dashboard?
[[UPDATE]] The Google Analytics v4 API now includes a "dateHourMinute" dimension.
Inside Google Analytics, I think the problem you will run into is that a "timestamp" includes Date, Hour, Minute, Second (and maybe millisec) and you can only drill into one secondary dimension at a time (ie: just date). An alternative method is to use the query explorer or just use the Google Analytics API.
Ad Hoc Report with query explorer
You can use the Google Analytics API Explorer: https://ga-dev-tools.appspot.com/query-explorer/
It will allow you to select:
A date range
Metrics: (like Users, pageviews, etc)
Dimensions: pagePath, Date, Hour, Minute (can't go to second or further, as in a timestamp, though)
Use filters to get rid of some data.
If your website gets a decent amount of traffic (> 50,000 pageviews per month), you might want to grab it 1 month (or less) at a time to avoid hitting limits/sampling effects.
#doctaj solution works. Please just note that if you are using the query-explorer for example, "dateHourMinute" dimension is considered 3 dimensions and will burn 3 spots from your available 7 or 10 dimensions that you can query. So if you need more dimensions, you need to decide which is more important to you. For example, you may want to query for the date and hour dimensions separately to drop the minutes in favour of something else.
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