Start learning with our library of video tutorials taught by experts. Get started

Google Analytics Essential Training (2010)

Using intelligence alerts to flag important events


From:

Google Analytics Essential Training (2010)

with Corey Koberg

Video: Using intelligence alerts to flag important events

The real point of web analytics is not just to collect data; it's to get insights. And through a feature called Intelligence, Google Analytics is going to help make analysis of our site for easier and help us draw accurate conclusions faster. To get to the intelligence reports, we navigate by clicking over here on the Home tab, click INTELLIGENCE EVENTS, and we have the option of the Overview, Daily Events, Weekly Events, or Month Events. For now let's just look into Daily Events. There are two different ways that I use this tool. The first I'll call forensic and the second we'll call insights.
Expand all | Collapse all
  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

Watch this entire course now—plus get access to every course in the library. Each course includes high-quality videos taught by expert instructors.

Become a member
Please wait...
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

Using intelligence alerts to flag important events

The real point of web analytics is not just to collect data; it's to get insights. And through a feature called Intelligence, Google Analytics is going to help make analysis of our site for easier and help us draw accurate conclusions faster. To get to the intelligence reports, we navigate by clicking over here on the Home tab, click INTELLIGENCE EVENTS, and we have the option of the Overview, Daily Events, Weekly Events, or Month Events. For now let's just look into Daily Events. There are two different ways that I use this tool. The first I'll call forensic and the second we'll call insights.

In forensic mode here what I am really looking for are things that are jumping out for me but I can't necessarily explain it. As I look at this graph right here of visits, certainly this day jumps out. There is a large jump in visits here and I want to figure out what that is. That's not necessarily a particularly easy thing to do. Often what we are trying to do here in analysis is not things that couldn't ever possibly be figured out another way, but ways that we can do things faster, easier, quicker. We only have a certain amount of time in our day for analysis; we need to be as efficient as possible, so I need to figure out quickly what's going on here.

As I put my mouse over this date, I can see the number of visits have gone up, and down below you will see this green bar. This green bar indicates the number of intelligence alerts that have been detected on that particular day. In our case we have three alerts. If I click on this green bar, the bottom of the screen is going to update to show what those alerts that Google Analytics found for us. So there are three things of interest here. First is that page views have gone up, visits have gone up, and visits particularly from the source of reddit have gone up. If I look over here I will see this idea of Importance.

Importance is also known as significance, and the idea here is this is going to tell us how different this is from what was expected. In our case, there was a large increase in the number of pages views and visits. Normally we would expect to get between 0 and 275 visits from Reddit. In this case we had 2500 visits on that day-- over 500% increase. If I click on the little icon right here, I will actually isolate the graph above to show just that. In this case it becomes very obvious, yes, this is a major event that happened on that date.

When we look at just the visits here from reddit.com, we can see that this was something way out of the ordinary. If I click back to our original screen, we see that that bump in 2500 visits is a large contributor to our overall visits here. It's a quick way for us to understand what's happening when we see something out of the ordinary. But I think the real value of this tool isn't so much in explaining what's already obvious to us, but in uncovering insights that we may never have seen before. If we are diligent analysts, we might log in every single day, we might go through our list of hundreds of different reports, and we might analyze every single type of medium, every single type of source, every keyword, every campaign that we are running, all the different traffic from different areas of the world, different cities, different states, different countries, and we might look for all these little anomalies and differences.

When we clicked on reddit.com, it became apparent that there was something strange that had happened there, but we wouldn't necessarily know to go click on visits from reddit.com that day or click every other source that brought us traffic that day. This isn't something that we as human analysts are perfectly good at is going through report after report after report. However, this is the perfect job for a computer, to churn through all of these reports every day, looking for something out of the ordinary and then alerting us when that happens. The problem is, if we are writing the computer program to do that, how are we going to tell the computer to sift through all this data and alert us? We could do it by quantity and we could say when a certain change in quantity happens to alert us.

The problem there is if we are thinking it's something like page views, right down here we see there are 20,000 page views on one, other pages on our site may only get a couple hundred or even a couple of dozen pages. So if we set a page-view limit of let's say an increase of a hundred pages, we probably are going to alert every single day for certain pages that get thousands of page views. Or we may never get an alert for a page that only gets a couple of dozen but it goes up to a hundred and that would be significant for that particular page. The other option is we could look at things via percentage.

The problem there is things that have a low quantity are going to have high percentages. For example, if we are used to getting one conversion and all of a sudden that goes to three conversions, percentage- wise that's going to be a very large jump. But in reality I don't necessarily want to get alerted when three things sell instead of one thing. That's not going to be significant to me in the overall case of my business where I'm selling thousands of items per day. So percentages can be problematic as well. What we are really trying to say, in English, is I want to be noted when something significant happens. So what we are really looking at is something that's different from the expected.

The way Google Analytics is going to look at this is through essentially standard deviations. It's going to look and see what was expected, and then it's going to look at what was actually happening, and it's going to look at how different those things were. That's what we have over here in the gray bar of Importance. When things are significantly different from what was expected, it's going to be more important. So this algorithm isn't based purely on quantity and it's not purely based on percentage either. It's closer to what you might think of a standard deviation. The key to this is that it's going to stop us from getting false positive predictions, because as analysts if day after day we get false positive predictions of things that are supposed to be important or supposed to be significant but actually aren't, we are going to start ignoring those.

In fact, we have the ability to control how much of those we get or don't get by the slider up here where we can say we want the alert importance to be low or high. If I select over here to low then I'm going to see more alerts here that don't necessarily meet a high threshold of importance. If I say, listen, I am very busy today, I only want to see the high level alerts, then I can move this over to high. I'm going to get far fewer alerts, but the alerts that I do get will be of very high importance. In this case, we can see things that were predicted to be in a certain range but their actual was very far away from that.

So in this case we expected to have 11% to 12%; instead I got a 24. In this case 3.7 to 4.7; instead I got a 26%. These things have a high level of importance and therefore probably something that we're going to want to be alerted to. So let's go ahead and put this to use. Let's scroll up here. Let's set my alerts somewhere here in the middle and back to our overall graph, and we can see our visits here and some medium alerts that have come across. One of the things that I think is critically important for this is when I talk about insights, we are really looking for that needle in a haystack, except I don't even necessarily know that the needle exists.

What I mean by that is if I were to see this large spike here, even without the Intelligence reports, I would probably figure out what that was. I would do some searching. I would go through my reports and I would see that something happened there of significance and I would go and figure that out myself. The real benefit of the Intelligence reports is for uncovering insights that I probably never would have found, because I had no reason to believe that anything out of the ordinary was happening. As I look across my visits graph, there are a couple of days that kind of jump out of me as large spikes. But as I look down here across my alerts I have a few days where there aren't necessarily anything in the visits graph that would make me go and look at that if I didn't otherwise have a reason to do so.

For example, let's take a look here at one of these. On November 15, up here in this graph the normal visits top line data over time graph doesn't give me any reason to believe this is a day out of the ordinary. In fact, it looks to be a little bit of a low-performing day. If I scroll down here what I see is something out of the ordinary I probably never would have found. The prediction algorithm expected between 0 and 140. In other words this is not a page that gets a lot of traffic. But in this particular day instead of 0 through 140 as it was expected, there are over 1100 visits to the Go Gopher Figurine page.

Similarly, if I come over here and take a look on November 28, I see that this was again not necessarily out of the ordinary day by any stretch, a little higher than the ones around it, but nothing on the course of the months that would be anything of interest. But as I scroll down here, I see that there were some high-importance events. In this case in terms of orders being completed, it was expected to be somewhere in the low $200 range, and was up over 950. Revenue was expected to be between $1000 and $2600; instead it was $22,000--over 500% revenue boost there.

I think this is really one of the major values of this. If I click on this particular report, I see that there is a significant event on that day, but I may have never known to find this needle in the haystack if I wasn't particularly looking for this, which frankly I wouldn't be. What we are doing here is utilizing the power of Google servers to search through and find these things that I may not otherwise find and to surface those up so that we as analysts can spend our time looking at things that are interesting and different rather than searching through numbers, which is what the computers can do. Intelligence can be used in many ways, such as to find these insights that were buried beyond our view or as we saw on the first example, a bit more forensic, to explain something that we saw but couldn't necessarily explain.

So the best way to find out what type of intelligence Google has found on your site is to simply open these reports and start digging.

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


Expand all | Collapse all
Please wait...
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.
Share a link to this course
Please wait... Please wait...
Upgrade to get access to exercise files.

Exercise files video

How to use exercise files.

Learn by watching, listening, and doing, Exercise files are the same files the author uses in the course, so you can download them and follow along Premium memberships include access to all exercise files in the library.
Upgrade now


Exercise files

Exercise files video

How to use exercise files.

For additional information on downloading and using exercise files, watch our instructional video or read the instructions in the FAQ.

This course includes free exercise files, so you can practice while you watch the course. To access all the exercise files in our library, become a Premium Member.

Upgrade now

Are you sure you want to mark all the videos in this course as unwatched?

This will not affect your course history, your reports, or your certificates of completion for this course.


Mark all as unwatched Cancel

Congratulations

You have completed Google Analytics Essential Training (2010).

Return to your organization's learning portal to continue training, or close this page.


OK

Course retiring soon

Google Analytics Essential Training (2010) will be retired from the lynda.com library on May 14, 2014. Training videos will no longer be available, but the course will still appear in your course history and certificates of completion. For updated training, check out the all new Google Analytics Essential Training coming soon to the lynda.com Online Training Library.


Become a member to add this course to a playlist

Join today and get unlimited access to the entire library of video courses—and create as many playlists as you like.

Get started

Already a member?

Become a member to like this course.

Join today and get unlimited access to the entire library of video courses.

Get started

Already a member?

Exercise files

Learn by watching, listening, and doing! Exercise files are the same files the author uses in the course, so you can download them and follow along. Exercise files are available with all Premium memberships. Learn more

Get started

Already a Premium member?

Exercise files video

How to use exercise files.

Ask a question

Thanks for contacting us.
You’ll hear from our Customer Service team within 24 hours.

Please enter the text shown below:

The classic layout automatically defaults to the latest Flash Player.

To choose a different player, hold the cursor over your name at the top right of any lynda.com page and choose Site preferencesfrom the dropdown menu.

Continue to classic layout Stay on new layout
Welcome to the redesigned course page.

We’ve moved some things around, and now you can



Exercise files

Access exercise files from a button right under the course name.

Mark videos as unwatched

Remove icons showing you already watched videos if you want to start over.

Control your viewing experience

Make the video wide, narrow, full-screen, or pop the player out of the page into its own window.

Interactive transcripts

Click on text in the transcript to jump to that spot in the video. As the video plays, the relevant spot in the transcript will be highlighted.

Thanks for signing up.

We’ll send you a confirmation email shortly.


Sign up and receive emails about lynda.com and our online training library:

Here’s our privacy policy with more details about how we handle your information.

Keep up with news, tips, and latest courses with emails from lynda.com.

Sign up and receive emails about lynda.com and our online training library:

Here’s our privacy policy with more details about how we handle your information.

   
submit Lightbox submit clicked