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In Google Analytics Essential Training, Corey Koberg shows how to use the Google web analytics platform to generate and evaluate information about the visitors to a web site, including data on site traffic, user behavior, and marketing effectiveness. This course covers the out-of-the-box functionality, from account creation to reporting fundamentals, and explains how to glean insights from the vast array of data available.
Modern business intelligence and Web analytics tools give us the ability to collect a staggering amount of data. In fact, the problem now is not that we can't get the data; it's that we have so many tools and sources of data, we can't possibly process at all, and as a result, we're being buried by it. The goal of today's analytics is not just to collect the data and store it away in meaningless charts and graphs, or worse yet, just store it to rot in the digital vaults, but rather we want to take that raw data, organize it into something that we can use, something actionable, something that has importance to us, and meaning to us as people.
From a business perspective, we need to be able to answer all the questions that are fundamental to effectively marketing and growing our business, and while these questions can get very specific and complex, they don't have to be. Some of the most important questions to ask ourselves, especially in the beginning, can be simple, fundamental questions such as, how is the Web site doing? This desire to analyze our Web site isn't necessarily new. Not long after the Web was created, site owners were looking for ways to understand what was happening on sites they built.
You may even remember when every site seemed to have something like this. I'll admit I thought these were fascinating when the technology first appeared. I put them on all of my sites, and refreshed each day to see how many hits had piled up, but the truth is, they tell us almost nothing that we can take action on to improve our site. The limitations were obvious, so then we got a little more sophisticated with our first-generation log analyzer analytics tools, but the truth is, it's just that hit counter over time. It's still not too actionable. Even the most sophisticated of these, that had bandwidth and server utilization stats, really don't get to the fundamental question of, how is the Web site doing? They tell us how the Web server is performing, but that's just a commodity these days.
What we really care about is the performance of the content, and how the visitors are interacting with the site. None of these tell us that. So how does modern Web analytics answer those fundamental questions? Let's take an example. This a result of an e-mail blast that was sent directing traffic to the site. We are split testing two versions of the e-mail to see which one was more effective at generating sales. Each line here represents one of the versions, which are aptly named Version1 and Version2. We can see that these e-mails brought in roughly the same amount of visitors -- about 10,000 -- and nearly the same per visit revenue value of $0.15 and $0.13.
Now, you'd be forgiven for assuming that there wasn't much action to see here; they're so similar. But as Web analysts, we need to consider all the data, or we risk missing valuable, but perhaps varied in sites. With two blasts a day, this brings us to approximately 20,000 visitors per day. At those values per visit, that $0.02 difference adds up to $12,000 per month. In other words, the entire salary of a well paid analyst, and then some. This is why it's so important to get away from counting hits, and into understanding user behavior, and evaluating quality sources of traffic, and the performance of all the elements of our site.
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