Liam
Forum Replies Created
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Page speed metrics from Universal Analytics (GA3) are not directly transferred into Google Analytics 4 (GA4) because there are substantial changes in how GA4 measures user behavior. However, Google suggests using Google’s PageSpeed Insights tool or Chrome User Experience Report for similar functionality. In addition, engagement and retention metrics in GA4 provide insights into how site speed and performance might be affecting the user experience. So if you want to measure site speed in GA4, you can use these suggested tools and also check out the new GA4 metrics.
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In simple terms, your website is set-up in a way where different sections are essentially considered as separate sites, each for a different language. These are seen as different sites by Google Analytics 4 (GA4), the tool you are using to collect data about who’s visiting your pages. Because of this, GA4 is gathering data for all these different ‘sites’ and compiling it together, which is why you are seeing data from all the different language versions in one place.
When you go into Google Data Studio, you’re seeing a representation of this combined data. The strings ‘in’, ‘uk’, and so on represent the different languages. So, ‘in’ likely represents the Indian version of the site, ‘uk’ the British version, and so on.
The confusion, it seems, comes from accessing the data through the ready-made dashboards in Google Analytics. They pull in all the data together, making it hard to differentiate. But good news: you’ve discovered a solution. By looking at the ‘hostname’ and ‘page path’ metrics, you can get specific data for each language version of the site. These two metrics together effectively tell you which specific site (or language version) a page view happened on. So, you can use them to separate out the data for different languages.
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The ‘select_item’ event typically relates to choosing an item from a list, like a product list on an online store. So, when you click on an item, but not necessarily add it to cart or view its details, that would be a ‘select_item’ event. It’s like marking it without getting into its specifics. The exact outcomes can vary from website to website depending on how they set up their user events.
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As of now, Google Analytics 4 (GA4) does not support roll-up properties, which is a feature available in Universal Analytics. Therefore, since GA4 does not have roll-up properties, you can’t directly connect a roll-up property to Google BigQuery. However, you can link individual GA4 properties to Google BigQuery and export data separately. Google might consider adding the roll-up properties functionality to GA4 in the future based on user feedback and demand.
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Given that you’ve clarified the issue doesn’t involve hitting the 1 million line data export limit, there could be multiple other reasons for why certain days are missing from your GA4 daily export.
One possibility could be a delay in data processing. Sometimes it can take up to 72 hours before certain kinds of data appear in your reports. If the missing day is within this window, you might just need to wait a bit longer for the data to appear.
Another potential issue could be related to the set date range. Ensure the dates you’re trying to examine are correctly included in your report’s date range.
Last but not least, you might be dealing with a known issue with GA4 where certain kinds of data don’t always appear accurately. The Google Analytics software updates often, so ensure yours is up to date.
If none of these suggestions solve your problem, you may want to consider contacting Google Analytics Support for further assistance.
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Greg is experiencing a technical issue with his Python script. When he attempts to run the script on his local machine, he’s bumping into errors related to the Secure Sockets Layer (SSL), a protocol for securing and authenticating data on the Internet. The script is failing to verify the SSL certificate, which is required to establish a secure connection, for a certain IP address. Even though Greg has installed the necessary certificates locally, the problem persists, and he’s receiving warnings that the connection isn’t private. He’s curious if anyone else has ever come across these issues and is asking for any advice or suggestions.
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Absolutely, happy to break it down more informally for you.
So, you’ve got your JavaScript callback that’s listening for the event. You’d like to be able to track when that event gets triggered in your Google Analytics (GA4). What you can do to make this happen is simply add in a new line in your callback. This will push a new event to the “dataLayer”. Here’s how you could do it:
`js
window.dataLayer = dataLayer || [];
dataLayer.push({event: “your-cool-event-name”});
`
Make sure to give your event a meaningful name to keep things organized.Alright, once your callback is pushing the event to the dataLayer, you need to create a new trigger in Google Tag Manager (GTM) that’ll listen for when that event gets fired. The trigger’s setup will end up looking like the one I’ve linked here: (insert image link)
Once that’s set up, you’re good to go! Every time the callback in your JS gets hit, it’ll push the event to the dataLayer, and your specially set-up trigger in GTM will hear it and record the info over in GA4.
If you want to get a bit more advanced, you can actually add even more info onto the object you’re pushing to the dataLayer. Any fields you add there will also be available for you later on when you’re checking out the data in GA4.
If you’re looking for some extra reading, Google’s got a great article about how the dataLayer works. You can find it here: (insert link).
Hope that helps!
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There could be a couple of reasons why this is happening. It could be that there’s a delay with the data appearing on the GA4 dashboard, as it can sometimes take a while for all the details to process. Also, it’s worth double-checking that you’ve set everything up correctly with your Branch and GA4 integration. Make sure the specific events you’re tracking are properly configured in both platforms.
