I'm tracking several events on my website using Google Analytics 4.
Some of those events are more important and I'm considering them as conversions. However, they happen at different steps of the user journey, so each of them would have a different cost and return, so I'd like to consider them as different conversions, in the same way they correspond to different events.
The problem is, when I want to report on them (e.g. on Data Studio, or Google Ads UI, or even on Google Analytics funnels), you can only see the aggregated sum of conversions, rater than being able to select a specific conversion.
Is there a way to make GA4 (an Data Studio) either:
Split reports by specific conversions (rather than the total number of conversions)?
Split reports by events rather than conversions?
I feel like GA4 has been a step back in terms of report customisation and data analysis.
Thanks!
Related
I have a google analytics report in datastudio. One of the pages in the report is attempting to report on events. In GA when looking at the event in the e-commerce explorer tab I will see data for revenue, ecommerce conversion rate, per session value, but in my data studio report all values show as zero.
This is a straight google analytics data source (i.e. there is no data blending).
Screen shots below of the datastudio result and the analytics report for the data I am trying to match.
Every resource I can find says this should be possible and the fact that Google Analytics has the exact same data showing again makes me think this is possible.
Is there an issue with what I am doing or the metrics / dimensions I am calling? If not why isn't this working?
I have struggled with something like this too. I would guess that the problem is with the decimal places, which I couldn't get to work in GDS - zeroes all over the place, just like you are getting. When I multiplied the defined event value by 100, it all worked. Worth a try, I think.
I am trying to automate the weekly report. Currently, I am using Google Analytics website to get the data for my report. Sampling level is higher precision.
I tried to get the same data by Google analytics API set samplingLevel as HIGHER_PRECISION. However, I am still getting the sampled data.
For FASTER, Precision Level is roughly 25% whereas for DEFAULT and HIGHER_PRECISION sampling level is roughly 50%.
On Google Analytics website, it says 'This report is based on 100% of sessions'. Can I get the same level of accuracy with Google API? I am using Google Apps script.Response for HIGHER_PRECISION is not matching.
Sumit, the API and the Google Analytics UI are certainly different and similarly the sampling's effect on things is a different beast which must be handled properly to get anything useful out of it.
As was mentioned in the comment, you can achieve high precision unsampled reports by (typically) shortening your date range that you're querying for and then "walking" the data.
To walk the data, you are essentially just gradually incrementing that small date range as you move through the desired data.
The "unsampled reports API" is... well, not the best. Considering that's what they are avoiding giving the end user in the first place, the offering available is not a very good long term or large project friendly solution. I would recommend small date ranges and then doing a data walk.
Happy Coding
There are several solutions to avoid sampling issue in Google Analytics by automating the process of data export for short date ranges.
I prefer this tool, it's pretty simple to use: MadStats.io
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.
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.
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