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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.
In the previous few reports we've introduced the idea of tracking whether users are coming back to the site and how engaged they are during that visit. Now we'll look to segment that data into histogram-styled buckets to try and gain more insight into what's actually happening when those visitors come to our site. The first report here is called the Frequency & Recency report, which gives us an idea of how many times users are coming back to the site, using the Count of Visits metric, as you can see on here on the horizontal bar. And we previously talked about New vs. Returning, but this attempts to shed a little more light on not just if they're returning, but how many times.
As we saw in the New vs. Returning report, only 10% in total are returning visitors. What we see here is that half of them, 5%, have been to the site one or more times. That quickly drops off and as we see for this site, folks don't tend to come back multiple times. So what this tell us is that we better make sure we do everything we can to keep them on the site once we get them here. This also gives us info about our sales cycle. While people rarely buy a car on impulse, they may research for weeks. This graph tells us that for this site we need to make the sale now because the odds are, they aren't coming back.
Now, because this all depends on the nature of your business, this report will vary widely, and yours may not look like that. We can see a slightly different report here if we switch to another site that's going to look a little bit different. Let's do that. We still see the majority of visits coming in the first and second row, but we also see a bump down here, a little bit more than the halfway through. It's important to note that this is not necessarily that more the visitors are coming back around this time; it's that this is the part of the histogram where it starts to group larger and larger quantities of time together. We've got 5 here, 10 here. We get down here, visits 100 through 200 are all grouped into one row.
Now if you see large numbers clustered down here all the way at the bottom, be sure to check in if you're counting internal traffic. In other words, people within your own organizations, they may be skewing your stats by hitting the site on a daily basis. This is especially true if you have an organization where the homepage of the browser is set to load the company homepage. A similar but slightly different metric that gives us a window into our sales cycle is to examine days since last visit. So we move from Count of Visits over here to Days Since Last Visit, which shows us how long ago the previous visit was. So instead of the number of returned visitors, we're looking at the time of those visits and how close or far apart they were.
As we see the bump in traffic halfway down where the bucket start to grow into larger numbers, also keep in mind for Google Analytics to track this accurately means the cookies must be intact. The chance that a person deletes their cookies within a day or two is relatively low. But as we start to approach a year or even longer, the chances that they haven't changed computers, location, or cleared their cookies in any other way is substantially less. The next report section down here is the Engagement reports, and the Visitor Duration metric is a highly illuminating report because it exposes just how misleading these averages could be.
It's well known within user experience circles that most people spend less than 10 seconds on a page, which is backed up by this data. We can see that by far the biggest bucket of visitors spend very little time on the site, and they're probably contributing towards the bounce rate. But if you recall from the overview reports, which we'll glance at back here, the average time on site down here was a minute and 51 seconds, because there are just a few people that spend a great deal of time on the site, so this average is misleading. However, with their analytics we're really trying to tell a story about our users through the data.
So going back to the Engagement report, we see it would be very misleading to believe that the majority of people actually do spend a minute and 51 seconds on the site due to that average. And we can see here that the majority are in the less-than-10-second bucket. Worse yet, those folks that spend a great deal of time on their site and distort the average, oftentimes they're internal to the organization, or they're folks looking from home, or other noncustomer, non-external visitors, and we generally aren't focused on them in our web analytics analysis. The Page Depth metric also in this engagement report is similar and that examines the engagement of the visits, but rather than focus on time, it focuses on the number of page views.
Again, this highlights the problem with averages. If we look up at the Google store profile, in the Overview section we can see the average number of page views for this site as a whole was over 3 pages per visit. However, if we look at the engagement report, we see here that three-quarters of the visitors see two pages or less, the majority of those just one. So assuming that most people see over three pages per visit because that's what the average is would be a major mistake in our analysis. Visitor behavior reports can shed a great deal of insight into how visitors are using our site, both over the course of time and within a specific session.
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