YouTube Analytics Using Google Data Studio

8 Pages Posted: 24 Aug 2020

Krishna Bhargava Anantharamaiah

Department of CSE, FET, JAIN (Deemed To Be University)

Date Written: July 19, 2020

In this paper we demonstrate the power of Big Data Analytics using Google Analytics as a platform. First the YouTube channel is opened, the start recording of the channel analytics is done here automatically by Google. This data is exported from YouTube in the form of Google sheets and then is fed to Google Analytics. After Google Analytics analyses this data, it is now integrated with Google data studio. Google data studio makes use of artificial intelligence insights techniques to generate artificial intelligence and prediction-based report graphs which can be analysed by the end user. This is the complete work flow of the project. In the future scope, not only YouTube, but any Google product or Google service data can be fed to Google Analytics and integrated in Google data studio for artificial intelligence based Big Data Analytics.

Keywords: Big Data Analytics, YouTube, Google Sheets, Google Analytics, Google Data Studio

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Krishna Bhargava Anantharamaiah (Contact Author)

Department of cse, fet, jain (deemed to be university) ( email ).

Bangalore, 572112 India +919480126779 (Phone)

HOME PAGE: http://set.jainuniversity.ac.in

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The Future of Analytics

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Learn about the top analytics capabilities businesses need to improve customer experiences and marketing outcomes.

As consumer behavior and expectations shift, marketers need new analytics tools to understand the customer journey and improve experiences across a variety of touchpoints like websites, apps, email marketing, ads, and more.

Improving the use of data and analytics is a top marketing priority in the next 12 months for businesses to meet evolving measurement needs and improve marketing outcomes 1 .

In new research from Forrester Consulting, commissioned by Google, marketers and digital analytics decision makers identify key challenges and opportunities for the next wave of analytics.

“The Future of Analytics: Firms Seek Advanced Tools to Improve Customer Experiences And Marketing Outcomes”, a commissioned study conducted by Forrester Consulting on behalf of Google, July 2020

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This document is deprecated! The information on this page refers to a Thesis version that is now obsolete. Please visit the Thesis Docs for current documentation.

Google Analytics is a popular, powerful reporting and metrics tool for site owners.

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If You Don’t Have a Google Account

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At this point, you either had an existing Google account and added Google Analytics to your existing products, or you have created a new Account entirely and added Google Analytics as part of the process.

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Note that if, for some reason, you have to use the “old” Google tracking code, which is not asynchronous, it’s recommended you add this code one section down in the “Stats Software / Scripts” rather than “Additional Scripts” — this will output the tracking code after the HTML content of your site.

Installing Google Analytics in Thesis — PHP Method

While the majority of users choose the ease of the interface, Google Analytics tracking code can also be added with a custom function.

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Note the UA- XXXXXXXX placeholder — replace this with your unique tracking code. Your Google Analytics code can also be pasted entirely in the “from <script> to </script>” section of the function; in most cases, only the UA- number would change.

However you added your GA code — via the interface or a custom function — when you visit your Google Analytics dashboard, you should now see indications that metrics processing and data collection have begun.

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Benchmarking Mobile vs Desktop Conversion Rates (Via Google Analytics)

google analytics thesis

Adam Lovallo

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Methodology

  • We pulled YTD Google Analytics data for 15 eCommerce and Lead Gen brands operated in the United States.
  • Each of those brands was doing at minimum $20m per year in top-line revenue annually and had a full Universal Google Analytics configuration (mind you UA is being replaced by GA4 soon-ish).
  • We pulled conversion rate data for all traffic and we pulled filtered data for Direct, Organic Search, and Paid Search. We recognize that Paid Social traffic grossly over-indexes mobile and so we wanted to look at those other traffic sources to see if the same conversion rate ratios held once that paid social/mobile effect was controlled for.

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On average, desktop conversion rates for all traffic were 1.9x that of mobile. Obviously, in the data above you can see a ton of variance from brand to brand. That said, intuitively 2x seems like a solid rule of thumb.

Below are the filtered results by Default Channel Group which more or less confirm the same ratios:

google analytics thesis

Organic Search

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Paid Search

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So there you have it! If you ever are pressed for the classic desktop vs mobile conversion rate comparison I think 2x is a solid and reasonable answer.

PS: As always feel free to message or email me at [email protected] to talk about growth via paid channels, SEO, CRO, etc!

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