Ranked!: A machine learning study of Google analytics metrics predicting content quality - Softcover

Inhaltsangabe

Ranked! exposes you to the Google Analytics metrics impacting the perception of quality content by Google: direct traffic, bounce rates, time on page, average session duration, pageviews, average pages per session, average page load time and more. The feel of the book is academic: a comprehensive research is being carried out on factors believed by SEO professionals to be important for ranking purposes, followed by a discussion of the methodology that will put these beliefs to the test. Learn how to incorporate state of art pre-built Google algorithms in your workflows and carry out your own studies and tests in the future, with no coding experience required! The study discusses the findings and implications of running a Google AutoML, an XGboost and a deep learning Keras model taking as input Google Analytics metrics perceived within the SEO community to impact website rankings.The study goes beyond testing long held SEO assumptions and debunks the myth of machine learning being accessible to only the few fortunate coders and programmers. In fact, the author is confident that after reading this book all non-technical marketers will be able to leverage the power of machine learning to run their own experiments and studies via state of art, point and click pre-built machine learning models in the cloud.By the same Author:DIGITAL MARKETING MADE SIMPLE - A Jargon Free Review of Theory, Tools & Leveraging Human Psychology to SELL MOREMIND THE BRAND GAP - A study of Competing Brand Identities, Human Biases and Why You MUST FIRE your HR teamHACKING DIGITAL GROWTH 2025: Exploiting Human Biases, Tools of the Trade & The Future of Digital Marketing

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