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Google Analytics Essential Training (2010)

Viewing data in different formats (overview, tabular, pie, bar, compare to site)


From:

Google Analytics Essential Training (2010)

with Corey Koberg

Video: Viewing data in different formats (overview, tabular, pie, bar, compare to site)

Google Analytics not only records the data for each visit, it gives us tremendous power and flexibility in how we can view and analyze the data that's already been recorded. This section will show us a few of the most common and useful ways we can view and visualize the data. For example, let's say we navigate here to the Traffic Sources report, and click on the All Traffic sources. Now, this is one of my favorite reports. In fact, this is the first one I'm going to go to if I get a new client, because it provides so much information about the current state of the site. When we first log in, we are going to see a table format here with source and medium on the left-hand side. It's going to be source and medium, and then it's going to be a column with data about each one of these different rows.
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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

Viewing data in different formats (overview, tabular, pie, bar, compare to site)

Google Analytics not only records the data for each visit, it gives us tremendous power and flexibility in how we can view and analyze the data that's already been recorded. This section will show us a few of the most common and useful ways we can view and visualize the data. For example, let's say we navigate here to the Traffic Sources report, and click on the All Traffic sources. Now, this is one of my favorite reports. In fact, this is the first one I'm going to go to if I get a new client, because it provides so much information about the current state of the site. When we first log in, we are going to see a table format here with source and medium on the left-hand side. It's going to be source and medium, and then it's going to be a column with data about each one of these different rows.

So the visits, the pages per visit, the average time on site, the percentage of new Visits, the bounce rate, for each one of these source medium combinations. So each one of these rows that talks about how people arrived at the site from the source and the medium is known as a dimension. In Google Analytics', our columns are known as metrics. These metrics provide information and data about each of these individual rows, and these rows are known as dimensions. Now, this tabular format presents a lot of data, but for us humans, it's not particularly easy to understand information when it's just a bunch of numbers in a big table. So Google Analytics gives us some idea of how to visualize this information that's going to help us gain some insights.

The first option is to take these numbers, and turn it into a pie chart. We will click this second button here, and we are going to select the percentage with the pie chart. So when I look down these numbers here on the left-side in Visits, I can see 55, 52, 50; all kind of very close to each other. Then I have a step down here to 33, and another step down to 15, and then large grouping down here into single digits, down all the way down to 1600. We can see this easily represented on the pie chart over here, where I see the big three, I see the step down to 33, I see the other ones here, as well as all of the long tail that's going to be clustered together in the aggregate here in the grays.

Or if you prefer bar charts, we can do that too. If we go down here in this button, and click on the Performance tab, what we are going to see is that same information represented here in bar charts. So we can see our big three, then we can see the drop down to 33, as well as the drop to 15, and all of the also-rans as well. Now this is useful, but it's not as useful as it could be, because what we essentially have is a single metric that's repeated here in two different ways. What if we switch to another metric, such as bounce rate? Now, we have shown before that a good bounce rate can be correlated directly to our revenue and other performance indicators.

Performance is a good word to focus on, because that's what we really want here. Volume on the left, and performance on the right. The question is, as I look at these different bounce rates, I don't really know if these are good bounce rates, or bad bounce rates, or how they stack up. Fortunately, we have an easy way to see that. We can see if these are performing above average or below average by switching over to the next option, which is the Comparison. What we are going to see here is these dimensions compared to the site average. I was looking at bounce rate, so I'm going to go down and select Bounce Rate. From here, I can see the two things that I need to know to evaluate this bounce rate.

First is, how is it performing to the site average? Each of these bars is relative to the site average, which is right down the middle. So if you are on the right-hand side, you are performing worse than the site average. If you are on the left-hand side, on the green, you are performing better than the site average. Now keep in mind, this is bounce rate, where lower is good, so a negative 30 is actually a good thing. So here I can see that my number one referral, google.com, is performing right about average. It's average performing traffic, but the next one down here, Direct, is slightly worse than average, and the next one down here, blogger.com, with 50,000 visits, is performing significantly worse than the average.

However, from here, the 33,000 coming from google organic is performing 33% above the site average, and as we go down, we see even better performing traffic until we get down here to the gmail blog over blogspot, which has a 53% better bounce rate than the site average. So in these two columns, we have the two critical things we need to know. We need to know how it's performing, but also the number of visits to let us know what this is in the context of volume. After all, if something has a great bounce rate, but only brings one or two visits, it isn't necessary that important to me as a site owner. I need to understand how it's performing, but also what percentage of volume is this traffic that's coming from there, or how big of an impact that high performance is going to have on my site.

With this view, you can look and evaluate individual traffic sources by the number of visits from those sources, and then evaluate their performance based on bounce rate, for example, and I'll always keep that number of visits in view, so I have that context. But if you want to get into some really detailed analysis, such as looking at trends by segmenting out different cities, we can utilize the Pivot view to look at all of that together by city. To do that, we simply click on the Pivot view here. In terms of metrics, we set this up as we did before, with Visits, and Bounce Rate. In this case, I am going to pivot by city.

What we see here are source/medium combinations, just like we had before down the left-hand side. In each of these, we can see the visits, and the bounce rate. We can see the total here, which is the same column we had before, but now I have also got it broken down by individual City. So I can see here that people from London brought 1200 visits, and had a 69% bounce rate, compared to Sao Paulo at 124 visits, and a 73% bounce rate. If I want to get really specific, I can break this down to a secondary dimension, and all kinds of other analysis, which we won't get too far into for now. But the point here is to show you, you can get really, really specific, and understand lots of different ways of viewing the same data, all within the same table.

Now, there is one more data view available for us, and that's the Term Cloud view. This view is often used for keywords, so let's try in this in the Organic Search report. If we apply the Term Cloud view here, and increase the number of rows to 50, we can see the top 50 keywords that brought traffic to our site. The clear winners are in the bigger font, and the darker color. So far, we see Google Store, Google Shop; things we would expect. This is based on visits, and it gets even better if we switch our metric away from visits to something more interesting, like average order value. To do that, I am going to switch to the Ecommerce tab, and select Average Order Value.

I am also going to increase my rows back to 50. Here we get some very interesting data. We can start to see the terms that are bringing in the highest average order values, not just the highest number of visits. And some words definitely jump out at us. This is actionable data. Term clouds tend to be real crowd pleasers if we include them in presentations, and they are great conversation starters for content and media teams. As we get deeper into our analysis, we will find that we can uncover far more actionable data if we know how and when to take advantage of each of these view options.

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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