{"id":259,"date":"2016-08-26T12:16:00","date_gmt":"2016-08-26T11:16:00","guid":{"rendered":""},"modified":"2020-12-04T19:10:54","modified_gmt":"2020-12-04T18:10:54","slug":"new-course-google-analytics-for-beginners","status":"publish","type":"post","link":"https:\/\/www.thediar.com\/en\/blog\/new-course-google-analytics-for-beginners\/","title":{"rendered":"New course: Google Analytics for beginners."},"content":{"rendered":"

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<\/i>The essence of training is to allow error without consequence. Orson Scott Card.<\/i><\/div>\n
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At Ducks|in|a|row we are excited. We are about to offer our very first course<\/b>: Google Analytics 101<\/a>. This course is intended to cover the first contact <\/b>with the tool: how the interface works, which are the most common reports, how to read them, and, most importantly, why do we measure.<\/div>\n
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In any case, we should not forget that Google Analytics is just a tool. It is not an end by itself, but an instrument<\/b> allowing us to reach such end. The end itself is Digital Analytics<\/b>. The definition I like the most is the following:<\/div>\n
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“Digital Analytics is the analysis of qualitative and quantitative data from your business and the competition to drive a continual improvement of the online experience that your customers and potential customers have which translates to your desired outcomes, bot online and offline.<\/i>“<\/div>\n
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Google Analytics mainly helps driving insights from quantitative<\/b> data. Google Analytics measures users’ behavior in terms of a relation between dimensions<\/b> and metrics <\/b>in a temporal<\/b>\u00a0context. Data for qualitative analysis must be gathered from other sources: panel groups, surveys, chat, customer care data, etc.<\/div>\n
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The ultimate goal of both, qualitative and quantitative analysis, is to learn<\/b> and to derive action<\/b>: understand what works, what does not, and what worths a try. However, too much data (and less analysis) leads to data paralysis<\/b>. Digital Analytics is about analyzing and organizing data so that actions can be actually derived and properly measured. We already talked about this in an older post<\/a>.<\/div>\n
When implementing the actions, we should not be afraid of failing<\/b>. Just be afraid if you don’t learn from such mistakes, and make sure you react fast. Failure is tolerated<\/b>. Idleness is not.<\/div>\n
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One last thought before explaining the contents of the course: data can tell you whatever you want if you torture it enough. This means that the analysis that will come out of Google Analytics’ data will still go through the QA process, as well as the conclusions reached out of it. Whatever interpretation you extract can be as well biased or even wrong. Again, implement, measure, and react fast. Very fast<\/b>.<\/div>\n
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The course itself is an introduction to Digital Analytics. Google Analytics is a way of touching that data and techniques. We will cover basic Digital Analytics terminology, such as KPI, metric, dimension filter, and segment, and how they are obtained in Google Analytics. We will learn about traffic sources, content consumed, and goal measurement. However, the most important topic acts as an umbrella for these topics: why do we measure<\/b>? What do we want to accomplish by tagging a site or an App?<\/div>\n
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Register quick<\/b> as places are limited. You will get more information here<\/a>.<\/div>\n
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Good measuring!<\/div>\n

<\/p>","protected":false},"excerpt":{"rendered":"

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