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Google Analytics Essential Training (2010)

Slicing data with dimensions


From:

Google Analytics Essential Training (2010)

with Corey Koberg

Video: Slicing data with dimensions

Dimensions are built-in segments, and that's one of the primary ways that we will segment data in Google Analytics. Let's talk about organic search engine traffic for a second. Naturally, keywords are always a part of that conversation, and in fact Google Analytics makes it the default dimension for the organic search report. But for now, let's look at this report using a different dimension. At the top of the table we can see a few other popular dimensions for this report, such as Source and Landing pages, and also a dropdown here where we can take and choose any dimension that we like. Let's talk about Landing pages.
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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

Slicing data with dimensions

Dimensions are built-in segments, and that's one of the primary ways that we will segment data in Google Analytics. Let's talk about organic search engine traffic for a second. Naturally, keywords are always a part of that conversation, and in fact Google Analytics makes it the default dimension for the organic search report. But for now, let's look at this report using a different dimension. At the top of the table we can see a few other popular dimensions for this report, such as Source and Landing pages, and also a dropdown here where we can take and choose any dimension that we like. Let's talk about Landing pages.

The interesting thing about organic search is that we don't get to choose where in our site that traffic gets sent to. The search engine does that by ranking different pages that they feel are the most relevant to the search term. And maybe that's the homepage, maybe it's a blog post, maybe it's an old page that I didn't even realize was still accessible on my site. This is information we want to know. So whatever page on our site ranks for those keywords is going to be the landing page. So we can change the Dimension from Keywords to Landing page. This way we can see which of those are the most popular. In this case, the home page is our most popular organic landing page, followed by the blog, and who we are page listing all of the partners and employees.

But does this really answer the question we're looking for? This just shows us the most popular landing pages from Google's organic searches, but in the aggregate. We're really trying to figure out the most popular keyword and landing-page combinations, and we've lost that connection by switching from one dimension to another entirely. For this, we can use secondary dimensions to show the most popular combinations of the two dimensions we really need to know-- search term and the corresponding landing page. To do that, we change our primary dimension here back to keywords and we select our secondary dimension to be the landing page.

Now we can see a list of the different keywords that people searched on, as well as the landing page that they landed on our site from that keyword. Let's take a look at our non-branded keywords. So we'll apply an advanced filter to exclude the keywords that matches our branded searches. In this case, we're going to click on advanced filter, Exclude > Keyword. In this case we're going to use a regular expression so that we can put multiple keywords in a single box. In our case we're going to put cardinal, and then that vertical pipe is going to mean and/or, and path. That should take care of most of our brand of keywords.

For the most part, it looks like Google has done a pretty good job of matching keywords to the relevant page, although I am a little intrigued when I see this one here, loss aversion, that goes to our homepage. This might be something I need to take action on. I need to do some work on my SEO to make sure Google, Bing, and the rest aren't confused about what my pages are really about. Let's take a look at another real-life example. Perhaps I am in the process of deciding which cities to hold our next Seminar for Success Google Analytics Live Trainings, and I want to see where there is the most interest. One thing I could do is find keywords that match that topic.

I am going to set a secondary dimension of city, and I am going to use inline filters to restrict the keyword set to just the things that have to do with training. So keeping primary and this is the keyword. I am going to change my secondary dimension here based on Visitors to City. I am going to change my advanced filter to restrict the keywords set by including keywords that are just related to seminars. So in this case we'll obviously have words like seminar, but I also want to capture some other words around training, so I am going to again use a regular expression with that vertical pipe bar to include more than one word inside the box. Click Apply and we'll update our report.

What we see here is quite interesting. Keywords that have to do with training are centered around these cities, and so we see Vancouver, Rockville, Franksville all have a significant amount of visits of people looking for that type of training. These might be potential candidates for us to hold future seminars. And we've looked how to isolate traffic, modify our dimensions, and add secondary dimensions, but we can go even further. Pivot tables allow us to take slicing and dicing to the extreme. Let's say I want to look at which keywords are being searched on via the search engines and see if there are any differences in countries. I want to evaluate the quality of traffic as well as the quantity, to see if perhaps traffic from other parts of the world are more or perhaps less likely to stay on our site.

So we're going to choose Bounce Rate as our secondary metric. Let's go ahead and do that. First thing I need to do is clear my advanced filter and select Pivot from the View dropdown. Okay, now I see a list of keywords for my site. I am going to set the Secondary dimension here to be Country. Now remember, I wanted to see Visits, but I also want to see performance, so I am going to set the secondary here to be Bounce Rate. And lastly, I already have Keywords as my primary dimension, so I am going to pivot by source. So what this shows me is people who searched on these keywords in these countries from these sources have these results.

From visits in the US who searched for cardinal path, I see 1,600 visits in total, with an average of Bounce Rate of 35%. When I break it down by individual sources here, I can see Google sent a vast majority of the visits and had a 35% bounce rate. Bing sent less visits but had a better Bounce Rate, et cetera. I can see that for one of these different keywords, broken down by each individual source and country. If I want to break this down even further, I can come back to my advanced filter and I can remove those branded keywords. And I am going to Exclude > Keywords > Matching Regular Expression, and I am going to put in my branded keywords.

In other words, these are words where it's going to indicate that someone is already familiar with my brand, products, services. As you can see, we've got an incredible amount of data and we've sliced and diced that down to get very granular information. One thing I want to point out: when you start slicing and dicing data down this finely, you do need a fair amount of data to actually populate this report and create segments with meaningful data. So while it may be interesting to look at the number of users who converted on a goal that came in on a specific organic keyword on an iPhone from Minneapolis in the last two days, you're going to need to have visitors who actually fall into that segment in order for it to be meaningful.

Combining segmentation and dimensioning allows us to quickly and deeply segment our data to get answers to even the most difficult analysis questions.

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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