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Google Analytics

What is happening, where, and how much? Practitioner-written articles on Google Analytics and Google Tag Managers.

Data blending

Over the last years, Google Data Studio has evolved from an appealing but clunky application to a tool that we recommend to any digital marketer.

Data Studio allows you to communicate data simply and in a repeatable format, and their expanded integrations, customizations, and editability have made Data Studio dashboards extremely powerful.

A relatively new feature, data blending, came out last year. This underused function can do a lot of cool things; it also has some limitations. Once you’ve got your head around the basics, the possibilities are endless.

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Google analytics funnel

Analyzing the customer journey is pivotal to conversion optimization. But how do you track user journeys in a way that is digestible, visual, and useful?

With funnels, of course! Funnel tracking in Google Analytics is one of the best ways to identify—in detail—where you’re going wrong.

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A Complete Guide to YouTube Analytics

With more than 2 billion monthly active users and more than a billion hours of content consumed every day, the right Youtube strategy can increase brand awareness, engagement, and conversions. 

But, cutting through the noise can be a challenge. 

Strategically leveraging YouTube’s robust analytics can help you make data-backed decisions and improve performance.

In this post, we’ll tell you how to use YouTube analytics to grow your brand and generate more video content views.

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How to Setup Google Analytics and Segment Your Data

When you hear “data segmentation”, it’s tempting to feel overwhelmed. Why? Segmentation can seem daunting (or boring) to those unfamiliar with it.

It’s an unfortunate because segmentation is perhaps one of the most effective tools at our disposal. The ability to slice and dice your Google Analytics data is the difference between mediocre, surface-level insights and meaningful, useful analysis.

In this article we’ll show you how to setup your Google Analytics to unlock actionable insights.

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Google Ads Hub

Not long ago, it was common for marketers and web analysts to spend the bulk of their day staring at Excel spreadsheets, manually collecting and organizing ad spend data across dozens of sources.

You had to go to each advertising account and export statistics on advertising campaigns, such as ad impressions, clicks, and costs, then export data from the web analytics system, and, finally, combine all the data manually.

Not an optimal use of time. 

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Raw Data & Google Analytics: A Game Changer

For a long time, I considered standard Google Analytics reports to be the best way to get useful insights. From time to time, I struggled with sampling, limitations, and weird results, but I didn’t see a way around it—until I discovered Google Analytics 360 and raw data exports into Google BigQuery.

After a few hours playing around with SQL, I was already able to deliver insights I never could have with aggregated Google Analytics reports. Since that day, I’ve been exploring how raw data can be a web analyst’s best friend.

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Data Discrepancies in Google Analytics: What Can Go Wrong, Why, & How to Fix It

Google Analytics shows 104 conversions. Your CRM shows 123 new leads. Heap reports 97. And so on.

It’s easy to get frustrated by data discrepancies. Which source do you trust? How much variance is okay? (Dan McGaw, founder and CEO of McGaw.io, suggests 5%.)

For most companies, Google Analytics is a—often the—primary source of analytics data. Getting its numbers aligned with other tools in your martech stack keeps results credible and blood pressure manageable. 

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