Liam
Forum Replies Created
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Unfortunately, GA4 data that’s exported to Google BigQuery does not currently include the conversion path data you’re looking for. This is because the Google Analytics interface and the raw data exported to BigQuery are not one and the same. Google Analytics uses raw data in its underlying data sets to generate the reports you see in the interface, adding attributes such as conversion paths. However, when GA4 data is exported to BigQuery, it includes only the raw events data, without the additional attributes. This is why you aren’t able to see the conversion paths in your BigQuery project.
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The error you’re encountering is typical when TypeScript cannot find declaration files for the imported JavaScript module. The ‘ga-gtag’ module you’re using is likely pure JavaScript and doesn’t contain type definitions that TypeScript understands. TypeScript tries to infer types from JavaScript files but in this case, it implicitly assigned ‘any’ type because it couldn’t determine the types.
Here’s a couple of ways you could resolve this:
– Create or add a ‘ga-gtag’ declaration file (ga-gtag.d.ts) to your project: In your “typings” or “types” directory, which should be in your root directory, create this file and add something like declare module ‘ga-gtag’;.
– Install the type definitions for ‘ga-gtag’ if they exist: If there are type definitions available for ‘ga-gtag’, they can be installed via npm using something like npm install –save @types/ga-gtag. But from what I can see, ‘ga-gtag’ doesn’t have type definitions hence you’d have to create a custom declaration file as explained in the first solution.
– Use any as a type for gtag, just for quick workaround :
import gtag from 'ga-gtag' as any;.Remember, it’s better to have type definitions for better assistance from TypeScript’s IntelliSense system. You should only use the last workaround if you’re sure about the types being used in the ‘ga-gtag’.
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While Google Analytics offers great insight into your website’s performance, it’s important to note that you can’t directly embed Google Analytics dashboards onto your own custom website. However, there is a workaround. By using the Google Analytics Embedded API, you can obtain the data you need from your Google Analytics account, but you’ll have to design the requests to mirror your Google Analytics reports. Also, this only works with Universal Analytics (UA), not Google Analytics 4 (GA4). Alternatively, you can use the Google Analytics API to fetch the data and leverage Google Charts to display it in user-friendly graphs on your website. Remember, these solutions require custom coding and some technical expertise. There isn’t a simple plug-and-play solution for this as of now. Rest assured, the result can be quite impressive with a polished, personalized data display.
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There might be an issue with the way the iFrame behaves within the context of the parent page. Even though you’re correctly setting up google analytics as recommended, iframes can create their individual browsing context, which might be causing an unexpected user and session tracking. Possible issues might include the iframe is hosted on a different domain (cross-origin issues), the tagging isn’t properly set up, or you might be blocking third-party cookies. You could try cross-checking all these factors. If it’s a cross-origin issue, you might want to look into implementing a PostMessage mechanism to send data between the parent page and the iframe, or consider other alternatives like server-side tracking.
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Sure, let me explain this in a simpler way. If you want to check if a particular user came back to your website, you’d probably have to export your Google Analytics data to BigQuery. That way, you can analyze your data thoroughly and detect returning users more easily.
In case you didn’t know, Universal Analytics (which I assume you’re using) allows you to create custom reports. This could be a convenient tool for you, especially because it lets you use the “Client Id” dimension. However, just a friendly heads-up, the Client Id dimension in Universal Analytics can be a bit tricky to work with. I’ve noticed that it doesn’t always work perfectly when filtering or searching. So don’t worry if it feels a little clunky, you’re not alone!
I hope that helps make things a bit clearer! If you have any more questions, feel free to ask.
