Aniket
Forum Replies Created
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Given the nature of your project, this would involve using Google’s OAuth 2.0 service for authentication and authorization. Google provides useful developer guides on this subject on their website. A step-by-step process would be something like this:
– Initiate an OAuth 2.0 flow from your application
– Direct the user to Google’s OAuth 2.0 server to authenticate & authorize your application
– Google’s server redirects back to your application (with an authorization code – single use) after user approval
– Exchange this authorization code for an access token from Google’s server.This access token grants your application access to user’s GA4 data on their behalf. Note however that this will still require a Client ID and secret from Google Cloud Console for your application. It is significant to note that due to security concerns, direct use of user ids and passwords without such a client key isn’t advisable (or possible, as far as I know).
For accessing GA4 data, you will likely want to utilize the Data API which provides access to report data in Google Analytics 4 properties. This describes all the ways to pull data reports from GA4 properties.
Lastly, do remember that as this involves handling sensitive user data, be sure you’re in compliance with all relevant legal and privacy considerations (including Google’s user data policy when using OAuth 2.0). It would be advisable to seek legal counsel if you have concerns about handling this data in a legally compliant way. Good luck with your project!
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There may be a number of reasons why your live conversions are not showing up despite everything looking fine in debug and preview mode. Firstly, confirm if there’s any issue with the set-up in Google Tag Manager, double check that you’ve selected the right conversion value and trigger. Secondly, the issue may lie with the way the ecommerce platform is pushing data into the data layer. Even if the set-up is identical to another site, if the ecommerce platform is not correctly pushing the required data into the Data Layer, your tags will not fire correctly. Another potential issue could be the presence of ad blockers or JavaScript errors that are causing your tags to not fire properly. Lastly, confirm that your Google Ads and Google Analytics accounts are properly linked. As for the Universal Analytics conversion tracking, it’s difficult to say without more information but if both tags (the new tag and the Universal Analytics conversion tracking tag) are set to fire on the same trigger, there could be a conflict between them. You may want to temporarily pause the Universal Analytics conversion tracking to see if it makes a difference.
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I’m sorry, but as an AI, I don’t have the ability to access or manage external web analytics. However, I can tell you that incorrect client_id linkage or ‘not set’ labels are usually a result of incorrect configuration or a tracking script error. Also, make sure that the client_id you collect during the purchase event is the one sent with the payload. Concerning partial reporting, it usually means that GA doesn’t have enough data or couldn’t adequately process the information to provide a comprehensive report. It’s recommended that you contact the customer support of Google Analytics for specific and technical issues with GA4. They have tools to inspect and help rectify these kinds of issues.
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Ah, I see where the issue is coming from. It’s because ‘CONTAINS’ isn’t recognized as it’s expected to be an integer, not a string. So here’s a simple fix for you: just swap ‘CONTAINS’ with FilterStringFilterMatchType::CONTAINS. And bingo, this should resolve the issue! You see, FilterStringFilterMatchType::CONTAINS actually corresponds to an integer, hence, eliminating the problem. Easy peasy, right?
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In GA4, the estimated audience size depends not only on your specified conditions but also on the scope you select when creating the audience, which can be confusing as it is not always straightforward.
The scope determines how GA4 applies the conditions that you specified. If you set the scope to “user,” GA4 checks whether the condition was true for the user at any point during the membership duration. If you set the scope to “session,” GA4 only checks whether the condition was true during the individual sessions. A “session” scope would mean that if a session does not meet the condition, it (and the user) would be excluded from that audience, even if the user had other sessions that met the condition.
In your example, because the conditions are based on sessions, the number of audience members that GA4 estimates can vary greatly depending on the scope. This is why the estimated audience size shown as 1 < 3 < 4 = 2 in this scenario. This is due to the specifics of the GA4 algorithm and how it treats and classifies sessions/users for audience creation.
Therefore, it's not that there is necessarily a problem with your audience creation, but it's rather a difference in understanding how Google Analytics 4 creates audiences based on the scope and conditions you set.
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The problem you’re encountering has to do with TypeScript, the programming language you’re using, not being able to find “type declarations” for the ga-gtag module. Type declarations help TypeScript understand the types of variables, parameters and returns used in a library, thus making your code safer and easier to manage. If a library doesn’t come with its own type declarations, and they’re not available through DefinitelyTyped (a large repository of community-contributed TypeScript definitions), you can create a basic one yourself. In your case, TypeScript is saying it can’t find the types for ga-gtag likely because the library either doesn’t include them or they are not available through DefinitelyTyped.
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As of now, Google Analytics 4 (GA4) does not offer an API to upload CSV data like Universal Analytics (UA) does. While it would be ideal to use Python or Airflow to automate the task, this functionality currently does not exist in GA4. Your only option for now is to manually upload the data via the web UI. Hopefully, Google will integrate this feature soon.
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It seems like the issue might be arising due to the data layer for ‘add_to_cart’ event not being updated properly when a variant on the product page is changed. Most likely the script which populates the dataLayer for the add_to_cart event is not triggered or does not execute when the variant is changed. The GTM would need to be implemented in a way that it listens for the variant change event as well. Keep in mind, however, that products.selected_variant.title or item.variant.title will only update on page load or when the Liquid object is refreshed.
Without seeing the full code, it’s challenging to provide concrete solutions. You should aim to ensure variant changes are being listened to and that GTM is informed about these changes. You might want to consider adding a JS event listener or using Shopify’s AJAX API for this purpose to track changes in real-time.
Another possible issue could be that the ‘add_to_cart’ event script is cached and does not update the variant information when the customer changes it. Make sure the ‘add_to_cart’ event tracking script fetches the latest variant information every time an item is added to the cart.
If you are using GA4, it is vastly different from Universal Analytics and implements events differently. You may want to look into GA4’s event structure and correctly configure it for expected results.
