2022 is the year of Google Analytics 4. Now or never you should migrate to the new version of Google Analytics. This is not just an update. It's a new analytics system. This show takes you through the history, the changes, the migration process, the benefits and the alternatives of Google Analytics 4. And we do this, by telling you about it. There are plenty of video trainings out there already. But we want to give some spoken words which you can easily consume while driving, working out, do ...
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We are talking to founders and thought leaders in the analytics space in this podcast. We learn about the motivations behind the products they offer. We discuss new topics that shape the analytics space. These are exciting times where the data space is exploding, and so are ways to collect and analyze data. Some years ago, it was pretty easy for most companies to decide on an analytics tool. Either you go for an all-purpose solution like Google Analytics. Or you need something special for yo ...
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How data teams can provide value, with Stefan Dörfelt from Kausa
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In this episode we have a discussion about the value of a data team in a company, which, naturally, is a huge topic. We talked about how new categories of analytics tools, like Kausa, are changing the role of data teams. Instead of just receiving requests to investigate issues, data teams can now proactively reach out to other teams with interestin…
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Building an analytics product with a clear & honest customer focus - with Maciej Zawadziński from Piwik Pro
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Our major goal is to focus on our customers. I guess this kind of sentence you will find in any presentation of digital product vendors, maybe even beyond. So people always claim that they take the customers first, that they do everything for their customers. And yes, to some degree they do. In the end, they bring the revenue, and so they might lis…
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Product analytics is best placed in the hands of the developers - with James Hawkins from Posthog
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There is a specific kind of person or a particular kind of role, which is usually ignored in data projects and especially in tracking projects. And these are developers. It's pretty shocking - I know. They rarely play an important role in these initial data projects. Even when they finally have an essential role. They ensure that the correct data g…
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Why tracking implementation is still hard work and how to improve - with Alexander Kirtzel from Elbwalker
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Alexander from Elbwalker and I are talking about why tracking implementation is so hard and creates so much frustration on the way, why pure auto-tracking is not the solution, and why context is pure analytics magic. New tracking setups have a lot of really cool high-energy moments just because it's something new. And often we do a new tracking set…
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How to provide every team with the right data access - with Oliver Laslett from Lightdash
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Would you start a new product when the category is pretty crowded already What if you start a new product where the category is pretty crowded already? And most of the people that you talk to tell you: maybe not a good idea. But Oliver and Hamzah decided to do it. A new BI tool based on modern data principles and tools. It’s built on top of the met…
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How to start with data and save your resources - with Jonas Thordal from Weld
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Listen to my conversation with Jonas from Weld to learn more about deciding on a data stack, the benefits of an integrated platform, and how to start with data in your company. It’s so much fun to build your data stack bundle by combining 2, then 5, then ten different tools. The significant promise of best-of-breed is that you shop for the best sol…
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Use analytics to improve your business and customer experience - with Adam Greco & John Cutler from Amplitude
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There is one trap in analytics - putting tools into categories And I am guilty here too. So we have tools for marketing analytics (mostly GA). And we have tools for product analytics. And we have tools for app analytics. And surely some niche ones for content analytics, sales analytics,... I think you get the problem. We are complaining about silos…
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How to make your decision based on high-quality data - with Stefania Olafsdottir from Avo
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Great data persons are also great storytellers. And if they can present a narrative of how problems with data quality can lead to wrong product decisions and can slow down everything, you can be sure to listen carefully. Stefania from Avo is a perfect interview partner - she had built the data team at QuizUp. She was making the journey through all …
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Behavioral data should be free and transparent - with Yali Sassoon from Snowplow Analytics
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What if you had created a product 10 years ago that perfectly fits into today’s world because it has all the ingredients we are looking for in data collection: - privacy first - data ownership & transparency - open source But let’s correct one thing. We are not simply talking about data collection. We speak about generating high-quality behavioral …
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02 - The new data model of Google Analytics 4 and why it's quite a good idea
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Data models are just something for real data nerds? Not this time. For Google Analytics 4 understanding the data model is important for everyone. Why? Because moving from Google Analytics Universal to Google Analytics 4 is basically moving to a new analytics service. It’s not an incremental update but a completely new setup. The major change is the…
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01 - The history of Google Analytics 4 or basically the history of Google Analytics
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Really, Google Analytics is 16 years old. Yes, it is. With 16 in most cultures you can already do a lot of things. Driving a car, vote, drink alcohol (often not a great idea), starting a job. So, you can start to call yourself mature (at least a little bit). Google Analytics is a mature software. But why is this software doing such a huge remodelli…
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00 - Introduction - Why we have ignored Google Analytics 4 so far
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Google Analytics 4 is not new - when count in the "Web + App property" which basically was a v0.8 - it's out for years. But rollout was weird, a long time essential features were missing. Which is ok, if your product is in beta. But Google pushed the 4 version early as the recommended version and basically confused everyone. So we started to ignore…
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