New eBook Recommendation: Practical Google Analytics and Google Tag Manager for Developers

Each week recent purchases are placed on the new book displays inside the library, and eBooks are made immediately available to use. You can view and subscribe to the New Library Books list online. For instructions on how to borrow an eBook by downloading it; check out our eBook LibGuide. Some eBooks require logging in with your JCU username and password; additional software will need to be installed to download books to a digital bookshelf. Most eBooks can be read online without downloading extra software.

An eBook title of interest is:

Practical Google Analytics and Google Tag Manager for developers by Jonathan Weber and the team at LunaMetrics.

An extract from the publisher webpage states

There’s a reason that so many organizations use Google Analytics. Effective collection of data with Google Analytics can reduce customer acquisition costs, provide priceless feedback on new product initiatives, and offer insights that will grow a customer or client base. So where does Google Tag Manager fit in?

Google Tag Manager allows for unprecedented collaboration between marketing and technical teams, lightning fast updates to your site, and standardization of the most common tags for on-site tracking and marketing efforts. To achieve the rich data you’re really after to better serve your users’ needs, you’ll need the tools Google Tag Manager provides for a best-in-class implementation of Google Analytics measurement on your site.

This book offers foundational knowledge, a collection of practical Google Tag Manager recipes, well-tested best practices, and troubleshooting tips to get your implementation in tip-top condition. It covers topics including: Google Analytics implementation via Google Tag Manager How to customize Google Analytics for your unique situation Using Google Tag Manager to track and analyze interactions across multiple devices and touchpoints How to extract data from Google Analytics and use Google BigQuery to analyze Big Data question.

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