5 Tools to Use Google Analytics Like a Data Scientist

diagnostics, predictive analysis, segmentation

September 22, 2017 by

Editor's Note: Josh R Jackson is a contributing editor at BestMarketingDegrees.org. To complement the brand new Google Analytics' classes in our updated catalog, he joins us to discuss five ways to approach the ubiquitous platform like a data scientist.


Google Analytics is simultaneously the most widely used and under-used analytics platform on the Internet.

How can it be both at the same time?

There's a simple reason: the freemium web service boasts more subscribers than any analytics platform in the world - but few users ever harness the sprawling interface to its full potential.

If you think of site development as building an office from the ground up, Google Analytics is a toolbox full of everything you need to build that office, complete with floors, desks and even a breakroom. But if you only know how to use a hammer and nails, that office will not just take a long time to build; it will be missing key components you can’t assemble without using the rest of the tools in the box.

Google Analytics has the potential to flip a website from a rundown office into a booming business that will attract the attention of thousands (if not millions) of people, especially if you know how to use its features like a data scientist.

With that being said, here are 5 ways you can start to use Google Analytics like a data scientist.

1. Use Funnel Analysis

Funnel analysis allows GA users to chart the path their customers will take through various pages of a website. This tool is particularly useful at pinning down exactly where (and maybe why) a customer abandons their journey through a site, whether it be a blog post that has no internal link structure, or a shopping cart that has a confusing layout.

As the go-to tool for tracking progress on a set list of conversions, funnel analysis is ideal for visualizing exactly how customers engage with calls to action across their entire online presence, especially because it can process data spanning multiple platforms.

2. Use Segmentation

Segmentation is perfect for marketers who want to know more about their audience. The tool allows Google Analytics users to organize and isolate various audiences according to the geographic, demographic, and conversion rate data of individual site visitors.

Segmentation also provides its users with the ability to import behavior information, e-commerce data, marketing data and other external data to complement what it collects on your audience. This way, segmentation users can plug in data collected by multiple tools - including AdWords - to generate marketing and advertising campaigns designed specifically for certain segments of their audience.

3. Use Real-Time Reporting

Real-Time Reporting is a fast way to peek beneath the hood of your website and get an idea of how recent changes may be affecting site traffic.

Real-Time Reporting is ideal for monitoring new content and small promotions that are designed to boost the number of your visitors and conversions. Real-Time Reporting is an excellent tool for monitoring the response an audience has to new information that is deemed particularly relevant or important to your audience prior to publishing.

4. Use Diagnostics Tools

One of the most important tasks of any data scientist is separating anomalies from important trends. Google Analytics’ Diagnostics Tool automatically does this by notifying users when a variety of events or metrics are outside an expected range of values for your site. In other words, it tells you when something extraordinary is occurring.

Google Analytics also provides users with Analytics Assistant, which uses machine learning to learn your preferences and work as an automated data scientist, helping you uncover trends and insights according to the metrics that interest you and your business most.

5. Use Predictive Analytics

Like its name suggests, Predictive Analytics helps users predict things like user behavior. That includes which users are most likely to convert.

Because it isolates audiences that are most likely to convert, Predictive Analytics is especially useful for devising remarketing campaigns in AdWords. If you’re just starting a site and aren’t yet able to measure conversions, then try harvesting data by using Predictive Analytics features like Smart Lists or Smart Goals.

Are you using Google Analytics like a data scientist? Take our newest classes on Google Analytics to start scraping and processing data that will help your website reach its maximum potential.

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