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Google Analytics Essential Training (2010)

Navigating data with site usage, goals, and e-commerce metrics


From:

Google Analytics Essential Training (2010)

with Corey Koberg

Video: Navigating data with site usage, goals, and e-commerce metrics

As we saw in the video on views, Google Analytics provides data broken down by columns of metrics, and those columns are grouped into tabs. As we see here in the All Traffic Sources report, we have several tabs available to us. The first is a Site Usage tab, and Site Usage is going to give us some information about how people are actually using the information on our site, sometimes called engagement metrics. We have visits, pages per visit, average time on site, percentage of those visits that were new visitors, bounce rate, etcetera. This information is broken down by this dimension of source/medium.
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  1. 6m 2s
    1. Welcome
      1m 13s
    2. How to get the most from this course
      3m 11s
    3. What's new in this update?
      1m 38s
  2. 5m 19s
    1. The pitfalls of hit counting and turning data into information
      3m 6s
    2. Web analytics: A tool and a process
      2m 13s
  3. 15m 30s
    1. Defining goals and conversions: Why do you have a web site?
      5m 40s
    2. Understanding data: Averages, segments, trends, and context
      1m 51s
    3. Introducing segments
      2m 38s
    4. Understanding trends and context
      5m 21s
  4. 11m 25s
    1. How does Google Analytics work?
      2m 18s
    2. Setting up an account
      2m 49s
    3. Installing tracking code on a site
      6m 18s
  5. 24m 20s
    1. Understanding accounts and profile administration
      6m 59s
    2. Navigating the reports and the Data Over Time chart
      4m 45s
    3. Selecting and comparing date ranges
      6m 50s
    4. Using annotations to make notes in data
      2m 30s
    5. Using the help tools
      3m 16s
  6. 24m 20s
    1. Viewing data in different formats (overview, tabular, pie, bar, compare to site)
      6m 10s
    2. Navigating data with site usage, goals, and e-commerce metrics
      9m 20s
    3. Sorting data with inline and advanced filters
      8m 50s
  7. 10m 26s
    1. Understanding the importance of segmentation in data analysis
      4m 40s
    2. Slicing data with dimensions
      5m 46s
  8. 7m 38s
    1. Why share data?
      1m 10s
    2. Managing user accounts and profiles
      4m 8s
    3. Emailing reports
      2m 20s
  9. 29m 12s
    1. Understanding who is visiting a site
      1m 20s
    2. Analyzing location data
      4m 52s
    3. Using language identification to segment users
      1m 35s
    4. Differentiating new users from returning users
      2m 1s
    5. Understanding visitor loyalty vs. recency
      4m 25s
    6. Comparing data according to visits, visitors, and page views
      2m 10s
    7. Sorting data by browser capabilities
      3m 56s
    8. Analyzing data from mobile browsers
      2m 34s
    9. Using flow visualization to see common paths
      6m 19s
  10. 23m 50s
    1. Linking an AdWords account to Google Analytics
      2m 46s
    2. Identifying campaigns and segmentation options
      5m 55s
    3. Using keyword reports
      1m 31s
    4. Fine-tuning your match type with the Matched Search Queries report
      3m 44s
    5. Optimizing traffic by time of day
      1m 37s
    6. Using the Destination URL report to identify landing pages
      1m 45s
    7. Identifying the best placement options for ads
      2m 0s
    8. Keyword positions
      4m 32s
  11. 40m 3s
    1. Understanding where site visitors come from
      2m 32s
    2. Analyzing the All Traffic Sources report
      2m 4s
    3. Identifying direct traffic
      2m 20s
    4. Identifying users who were referred to your site
      3m 9s
    5. Viewing search engine reports (overview, organic, and paid)
      4m 52s
    6. Introducing campaign tracking
      11m 17s
    7. Planning, creating, and logging a tracking strategy
      2m 58s
    8. Tracking offline campaigns
      7m 11s
    9. Finding data in a Campaign report
      3m 40s
  12. 36m 43s
    1. Analyzing top content by metrics and the navigation summary
      3m 29s
    2. Sorting top content according to page title
      3m 57s
    3. Understanding when to use content drilldown
      2m 25s
    4. Measuring the importance of top landing and top exit pages
      3m 41s
    5. Identifying slow-performing pages with the Site Speed report
      4m 6s
    6. Understanding the Site Search and Usage report
      3m 29s
    7. Analyzing the Search Terms and Search Term Refinement reports
      4m 12s
    8. Using the Site Search Pages report to understand how users search
      5m 19s
    9. Configuring Site Search
      6m 5s
  13. 33m 49s
    1. Understanding the Goal reports
      4m 24s
    2. Configuring goals
      9m 55s
    3. Understanding funnel visualization
      9m 48s
    4. Identifying value through E-commerce reports
      4m 35s
    5. Using goal flow to find detailed insights
      5m 7s
  14. 24m 25s
    1. Real-time data for time-sensitive analysis
      4m 21s
    2. Using intelligence alerts to flag important events
      8m 59s
    3. Creating custom intelligence alerts
      5m 48s
    4. Creating and customizing dashboards
      5m 17s
  15. 43s
    1. Goodbye
      43s

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Google Analytics Essential Training (2010)
4h 53m Beginner Oct 08, 2010 Updated Dec 20, 2011

Viewers: in countries Watching now:

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.

Topics include:
  • Setting up an account
  • Installing tracking code on a site
  • Reading the dashboard and understanding high-level metrics
  • Understanding how visitors use and navigate web site content
  • Analyzing visitor and traffic source reports
  • Tracking AdWords and other marketing campaigns
  • Planning and configuring goals
  • Utilizing segmentation for deeper analysis
  • Understanding the raw data and how it's collected
  • Selecting and comparing date ranges
  • Using flow visualization to see how visitors navigate through a site
  • Identifying slow-performing pages
  • Performing real-time analysis
  • Using annotations and other best practices
  • Configuring and analyzing internal site search
  • Determining the best report view to use
  • Navigating reports with tabs
  • Cleaning up data with inline filters
  • Sharing data and reports
Subjects:
Business Online Marketing Web Data Analysis Web Analytics SEO
Software:
Google Analytics
Author:
Corey Koberg

Navigating data with site usage, goals, and e-commerce metrics

As we saw in the video on views, Google Analytics provides data broken down by columns of metrics, and those columns are grouped into tabs. As we see here in the All Traffic Sources report, we have several tabs available to us. The first is a Site Usage tab, and Site Usage is going to give us some information about how people are actually using the information on our site, sometimes called engagement metrics. We have visits, pages per visit, average time on site, percentage of those visits that were new visitors, bounce rate, etcetera. This information is broken down by this dimension of source/medium.

So we can see, for each of these different sources, how those metrics are doing. In other words, when people come from google.com, how long are they staying on the site versus someone who comes over from YouTube.com. But we may also want to view those by how those particular visits are achieving our goals. So if we click over to the Goal Set 1, we're going to get a different set of columns. Here, we can see how google.com, and YouTube, and the other sources are doing as far as the number of visits they bring, but also completing our orders, viewing software downloads, hitting our Contact Us page; these are all goals that I have defined as things that I want people to do on my site, and this is going to evaluate each of these different traffic sources on how well they achieve those goals.

We can also see the overall goal conversion rate, as well as some information about the per visit goal value. Now, in my Goal Set 2, I've defined some engagement metrics. These particular goals I've defined as, I want to see people who browsed my site over five minutes, I also have a goal of people visiting more than four pages, I have a very ambitious goal of people visiting over 10 pages, and then I can see the goal conversion rate for this particular set of goals. Again, all of these are based back on the dimension that I have; in this case source and medium. The last tab that I have here is the Ecommerce tab.

If you have an e-commerce site, and you have Ecommerce enabled, this can be a really, really critical tab. This is going to give us the dollars and cents, exactly how much each of these visits are worth; how much each of these traffic sources are bringing in. In this case, we can see those same sources: google.com, blogger.com, youtube.com, etcetera, and how much revenue each of those visits resulted in, how many transactions, the average value of those transactions, this e-commerce conversion rate; these can be really, really valuable columns for us to see, because we can start to put a value on each of these things these visits are doing.

If you are involved in the AdSense program, you also may seen an additional tab here, as well as some information about the ads that your site is displaying. One useful thing to do here is use the Compare to past feature in the date range. If I click on the Date Range selector up here, and click on Compare to past; in this case, let's compare June versus July. What I see is the same report, except I have an additional row here, where I'm going to see what the percent has changed from the July visits, versus the visits in June.

In this case, I can see that there was a 23% drop in visits from google.com. What's really interesting is, if I scroll on down here, I can see that on the Gmail blog over at blogspot.com, there is a 92% drop in visits from the month of June to the month of July. The other thing I can notice is there is a corresponding drop in revenue. As you notice this column here of Revenue, we see a 97% drop; going from $6,800 down to just $145 in the month of July.

This is some pretty insightful data. This is something we can definitely want to see in terms of the value that those visits are bringing. However, we can see a pretty tight correlation between a drop in visits, and a drop in revenue, which would be expected. In just a minute, we'll see that this isn't always the case. The Ecommerce tab is useful in lots of places. Let's take a look at the Keywords report. If I click on Keywords -- now it may be interesting to see how much e-commerce revenue we're deriving from each of these keywords. In other words, we know how valuable each of these keywords were from visits, but how much money were each of these ones? Is there a particular keyword that's driving value? In this case, I want to click back on my Ecommerce tab.

Here on the Ecommerce tab, if we scroll down, we can see the different keywords which brought folks to our shop, and we also can see the number of visits they brought. By default, we're going to be sorted by visits, but I am interested in which keywords were the most valuable, so I'm going to go ahead and sort by revenue. I do that by clicking on the Revenue column, which is going to sort, in descending order, the amount of revenue. And one thing I notice in the second one here is that the term google t-shirts: in the month of July, 97 people searched on this term; in the month of June, 95, so you would expect the revenue to be approximately the same.

However, what we see is that in the month of July, there is a 426% increase from the month of June, even though the amount of visits only went up by 2. So we can see there is not always a correlation from there. By having this extra column, and actually understanding what the value is, we can see exactly what that is; we don't need to rely on visits to give us some inference that may or may not hold true about what the value of that keyword is. Let's take a look at a few more examples. The Visits tab is great, because it gives us context, and insight, and visits are, of course, one of the most important things on our site.

But not moving beyond the Visits tab, and staying on the Visits tab all the time is highly dangerous, especially if we have goals and e-commerce set up. Let's take the case of this actual client. Now, in this case, we were originally working on some pay-per-click analysis, and the client wasn't particularly interested in it, pointing out that, in this case, the number three medium, cost-per-click -- which is our pay-per-click -- was, as he put it, a drop in the bucket. If you look at the referral traffic: 953,000 visits. The claim was, this is where my real traffic comes from. I don't know why we're wasting our time down here with this pay-perclick stuff; it doesn't amount to anything.

Now, the problem was, at this time, visits were all we had. There was no revenue set up, because there was no e-commerce tracking enabled. Now, it stands to reason that he was right. More visitors does equal more business, but when it comes to data- driven analysis, we're going to need more than a gut feel. When we've got the performance data to show how the quality of these visits stacked up, we see a completely different story. In this case, although there were almost a million visits coming through on the referrals, it only amounted to $15,000. Although there were only 58,000 visits coming from the pay-per-click -- the so-called drop in the bucket -- this amounted to $11,000.

At this point, once we see the actual value of these, we can see that not all visits are created the same, and you certainly can't claim that it's a drop in the bucket any more. The vast majority of Google Analytics users don't have goals defined, or e-commerce configured. Now, for those of you sitting at home, are you flying blind? Are you looking at this, and thinking it's a drop in the bucket? Later on, we'll show you how to configure goals of your own, so you don't have to rely on the Visits tab as your sole performance indicator, which you definitely shouldn't do. But picking the proper metric isn't easy. Let's take the following case, where we're asked to select the best campaigns.

So, the goal here is to pick out the best campaign, and we are going to highlight some different ways that we might evaluate this, based on these metrics. Now, we'll start out with a bang: ROI. This is really what we're after, right? Return on investment is the name of the game, and although a 273% return on investment is pretty good, there is no question that 1000% is better. In this case, it might be over. We pick the bottom one, and move on with it, and no one would blame us for doing so, but just for fun, we take a little look further. Now, per visit value, we get reinforcement of the same thing. $1.41 on top, versus $3.22 below.

So if we are doing pay-per-click, again, the bottom one is the way to go. But what about Revenue? We haven't brought any context here. Well, on top brings 14,000 plus, and the bottom only $7500 in revenue. ROI is an easily manipulated value, because it doesn't necessarily depend on the number of visits, or any absolute numbers. So even though you have an ROI of a thousand, if you're looking for revenue, you may be more interested in a 273% ROI that brings you $14,000. But we haven't really talked about the cost. If you're doing advertising, to bring in that revenue, you may have had to pay for it.

In this case, we get $9,000 versus $1500. So in looking at all these different metrics, how do we figure out which one is the best? The bottom line we're really looking for is net profit. How much did I get, versus how much did I have to pay for it? And these two are almost exactly the same. Even though every metric was wildly different, and showed one was vastly better than the other, the bottom line at the end of the day: they're about the same. Let's look at another case. How about these two? One campaign brought 10,000 visits, and one brought 6000 visits. Now, given that, by and large, most of the folks that come in don't have goals configured, don't have e-commerce, don't have anything else to judge the value of the campaign other than visits, it's pretty clear that the top one's the winner.

But what about when we start looking a little deeper; when we start looking at things like impressions, and clicks? If you're paying for each one of those clicks, it gets a little bit more tricky, because now money is going out the door, so to get those visits, how much did I have to pay? In this case, even though 10,000 is definitely better than 6000, if I had to pay $9,000, versus just $774, that might change the game considerably. We also haven't looked at what the value of that was. Remember, visits aren't revenue. When we look at the revenue one -- look at this 14,7 versus 38. When we get back to that all important net profit, the top campaign brought $5,700, while the bottom one brought $38,000.

With each of these metrics I've picked, it seems like the opposite one won. After all, if you torture that data long enough, it will confess to anything, and agencies love to take advantage of this to make you think that they're loser campaigns are huge winners. And if you don't understand these metrics, it's probable that you believe them. Understanding which tab to use, which metrics to use, and which ones are important in which situations, could keep you from choosing the campaign with twice the visits that would lose you $32,000.

Find answers to the most frequently asked questions about Google Analytics Essential Training (2010).


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Q: The course was updated on 12/19/11. Can you tell me what's changed?
A: Many movies were updated to reflect the changes in the Google Analytics user interface and new movies were added to the course as well, with topics including using flow visualization to see common paths, identifying slow-performing pages with the Site Speed Report, using goal flow to find detailed insights on funnels and conversion paths, analyzing real-time data for time-sensitive analysis, and fine-tuning match types with the Matched Search Queries report.
Q: Where can I learn more about internet marketing?
A: Discover more on this topic by visiting internet marketing on lynda.com.
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