Are you using offline conversion imports? Are you enhancing your marketing data with user-provided information, or planning to? If so, Google's recent update will make your life easier: Conversions can now be matched using hashed email addresses in addition to GCLID.
Google Tag Manager (GTM) is crucial for marketers and web developers. It allows easy management of tracking codes on websites. But it’s not only about basic installation; it’s about optimizing GTM to collect valuable data and enable insightful analysis. Here, we’ll cover five essential GTM features that greatly improve data collection and analysis.
Google Analytics is a powerful tool, even without the price tag of the 360 version. If you are uncertain about going 360, use this breakdown of premium features listed in this article to see if going in this direction will be worth it to you.
With Google offering extended functionality options on most of their services, not all of them get the same level of needed understanding. Because if the Google Analytics 360 suite has more features and utilisation, is Search Ads 360 just a premium version of Google Ads?
“ Working with Optimics on the enhanced conversions project was a real pleasure, and we’re looking forward to using the new data and signals in future Google Ads campaigns.” — Andreas Berg, Chief Marketing Officer, Invia
Until recently, it was difficult to automate complicated data pipelines using Google Analytics 4. That has changed with Dataform, a component of the Google Cloud Platform that allows automating data pipelines.
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In today’s data-driven world, website owners, e-commerce businesses, and retailers rely on various tools and technologies to gather, utilize, and analyze data for targeted advertising, personalization, and enhancing customer experiences. However, with growing privacy concerns and evolving regulatory landscapes, it’s crucial to ensure users‘ consent and comply with data protection laws
In GA4, standard reports provide valuable insights into user behaviour and tracking efforts. For users transitioning from Universal Analytics, the flexible reporting interface in GA4 is a noticeable advantage.
Traditionally, obtaining user data for analysis was a complex and time-consuming task. However, Google has simplified this process with the introduction of User Data Export in BigQuery. This feature allows organizations to access valuable data, including audience insights, predictive metrics, and user activity timestamps.
Migrating from Google Analytics Universal to GA4 has likely put you in a position where you have to decide which date is more accurate for your web model. Add to that different numbers in the Google Ads interface as well as BigQuery, and you enter a philosophical discussion about what data really even means.
So let’s look at some key differences between these systems and how they track data.
Google Analytics 4 is a new, exciting, and evolving tool. Those of us who started working with it on its launch date have seen its improvements firsthand. Not only have we seen the tool evolve a lot in the past, but it will keep evolving well into the future.
If you want to keep track of the new features and utilities of the system, we’ve prepared a rundown of several recent updates to the system. As GA 4 is a growing system, more features will be introduced in the future. This article only mentions improvements until the end of July 2023.
BigQuery is a potent tool that can be used for many reasons. In this article, we will describe the main benefits of considering BigQuery as the heart of your data analytics platform.
While migrating from GA Universal to GA4, you might notice that result comparisons between the systems will not always lead to 1:1 results. This may not be the result of a faulty migration. GA4 has slightly different calculations for certain metrics. Here is a short list of major metric comparisons between the two analytic systems.
It’s been some time since Google announced a new version of Analytics. And starting in July 2023, Universal Analytics will stop recording new data. Unless you have a 360 subscription, you have one more year.
Although GA4 and UA are both web analytics tools used primarily for tracking website and app activity, BigQuery is mainly used for storing and analyzing large amounts of data.
Integrating Google Analytics 4 with a third-party experiment tool brings numerous benefits to online business owners. By leveraging advanced experimentation capabilities, enhanced targeting options, and deeper analytics integration, you can gain valuable insights into your audience and optimize your website for improved user engagement and conversion rates. As Google Optimize approaches its sunset, it becomes increasingly important to explore and integrate with third-party tools that align with your business goals. Stay ahead of the curve and unlock the full potential of GA4 by integrating it with a 3rd party tool
As a digital analyst or a business owner, understanding your audience and their behavior is crucial for optimizing your website and maximizing your business’s success. Google Analytics 4 (GA4) is a powerful tool that provides valuable insights into user activity, and by integrating it with a third-party experiment tool, you can further enhance your understanding of your audience.
In this article, we will explore the benefits of integrating GA4 with third-party experiment tools, along with an introduction to Google Optimize and the concept of third-party integration.
One of the benefits of Google Analytics 4 is that free accounts also can export data to BigQuery. Before you can export data to BigQuery you have to create a Google Cloud Platform (GCP) which is a set of cloud computing services. In this article, we will go through the process of creating a GCP project.
Platform unification in Google Tag Manager (GTM) refers to the ability to manage tags across multiple platforms, such as web, mobile, and AMP (Accelerated Mobile Pages), from a single container. It simplifies tracking user behavior and allows for more efficient tag management across multiple platforms with platform unification in GTM.
Google Analytics 4 is the latest version of Google’s web analytics platform. It provides new features and capabilities compared to the previous version, Universal Analytics.
There are several reasons why you might want to consider switching from Google Universal Analytics to Google Analytics 4:
It started out as a small project. A few lines of code here, a simple database there. Nothing too complicated, nothing that couldn’t be handled by a couple of enthusiastic developers with some spare time on their hands. But as the weeks went by, the project grew. New features were added, the user base expanded, and the data started pouring in.
Before long, the once-simple codebase had become a tangled mess of spaghetti code and poorly designed systems. It was slow, inefficient, and prone to crashes. The developers were overwhelmed, and the project was in danger of collapsing under its own weight.
That’s when the Cloud Architect stepped in. With a deep understanding of software architecture, a strong grasp of the latest technologies, and a laser focus on scalability and efficiency, the Architect quickly identified the problems with the existing system and set to work designing a solution that would meet the needs of the project.
It’s a great idea to integrate your GA4 data with data from other systems, achieving an overall picture that includes both online and offline behavior. With GA4, it’s easily possible, as BigQuery export is available even for the free GA4. Taking small steps can be easy, no need to run an enormous project.
If you understand the GA4 sessions correctly, you will find that they differ in many ways from Universal Analytics. I recommend reading this article for a better understanding.
Much has been written about the pros and cons of Google Analytics 4. However, in this article, we’ll take a look at one of the key features that only 360 accounts can enjoy in Google Analytics Universal. That feature is the export to BigQuery.