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Google Analytics Essential Training (2010)

Understanding trends and context


From:

Google Analytics Essential Training (2010)

with Corey Koberg

Video: Understanding trends and context

As we saw in the segmentation intro, we can use that segmentation functionality to evaluate performance. Say, for example, which traffic source is converting better? This is very important to know, after all, if you have one source converting at 94%, and one at just 28%, obviously one is more valuable to you than the other. Or is it? Just like averages and aggregates lie, we'll need to make sure we don't consider metrics in isolation. We'll consider the full context of the numbers we are seeing to truly understand what's going on. Now clearly, in this case, if I have to choose one over the other, I'll take the 28% any day over the 94%, because 28% of 80,000 is a lot, and 94% of 17 is very little.
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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

Understanding trends and context

As we saw in the segmentation intro, we can use that segmentation functionality to evaluate performance. Say, for example, which traffic source is converting better? This is very important to know, after all, if you have one source converting at 94%, and one at just 28%, obviously one is more valuable to you than the other. Or is it? Just like averages and aggregates lie, we'll need to make sure we don't consider metrics in isolation. We'll consider the full context of the numbers we are seeing to truly understand what's going on. Now clearly, in this case, if I have to choose one over the other, I'll take the 28% any day over the 94%, because 28% of 80,000 is a lot, and 94% of 17 is very little.

But context is about much more than just Web metrics. We tend to get so focused on them that we forget the other aspects of our business that are interrelated. For example, we have a lot of travel related clients, some here in the Caribbean, and I can tell you that their Web site will convert a lot differently on a day like this, than on a day like this. So we wouldn't want to conclude the changes we made to the site were a disaster, and we should revert them right away, without realizing those numbers in the context of this external weather event. And more than merely understanding why our performance is that way, if we are savvy about our analytics, we can actually use that to our advantage.

For example, when Hurricane Ivan was blowing over one of our clients resorts, we saw a huge spike in traffic. Now digging into our analytics, we found it was almost all due to hurricane related searches. Initially there was some concern that this was effectively bad press that would do damage to the brand, but some creativity allowed us to react and take advantage. In Caribbean resorts it's common to offer a hurricane guarantee. In this case, the guarantee offers the chance to come back during better weather with all kinds of upgrades and freebies. So by changing the homepage from the picture of the sunny paradise to a huge flash page all about the hurricane guarantee, they were able to salvage that traffic, generate new stories in the press, and get many folks to associate in their mind the guarantee with their brand, not just the scenes of horrific hurricanes, all because they knew how to use analytics to their advantage.

Taking metrics into context is important in lots of ways. I'm reminded of the CEO of the auto company who was ecstatic showing off this chart trending down, and showing how much money they were losing every day. So why was he happy? Because he wasn't losing as much as they were expected to lose, and not as much as their competitors were losing. Keeping the data in relative context is always important. And you can imagine the plight of the Web marketing manager for this hotel next to the Eiffel Tower. Bidding on keywords and ranking in the search engines just got a whole lot tougher for the Hilton in Paris a few years back when searches on Paris Hilton suddenly got way more popular.

And the point here is that it had nothing to do with their Web site, their campaigns, their analytics, or really even their business, but it had a huge effect on the online keyword searches. And we hear this all the time; oh, they're not really my competitor, they just have the same name, or we just share the same keywords. Well, then you are competition online. We call this accidental competition, and it's important to realize that your competitors offline often have little to do with your competitors online. In this next graph, I'll point out two aspects of analysis that are critical to making correct decisions about our site.

I'll give you a second to guess what industry this is. It's actually travel as well. Now, in my house, booking travel usually involves my wife and I doing some research when we get a chance, but then not actually booking until we can both get a free minute to sit down, confer, look at the calendar, etcetera. This always seems to work out to a Sunday night when there is no big plans, and we actually have a few minutes. But just because that's how it works in my house, I can't make the mistake of thinking my personal bias is the same as all my clients. In fact, it looks like, based on this convergence graph, that's not the case at all.

This graph tells me most people roll into work Monday morning and say, I can't handle this, I need a vacation, and jump online. So the key here is that, besides not letting our personal bias cloud the data, we also need to recognize the prevailing trends in our industry, such as days of the week. We certainly don't want to compare how a campaign did that ran on a Sunday and one that ran on a Monday, because unless it was massively different, Monday will win every time, and we will conclude the wrong thing. Most trends are more than just days of the week, but seasonal as well. For example, if one of your keyword was fireworks, and you saw a huge spike here around the beginning of July, do you assume that your new AdWord's campaign must be the reason? Of course not.

The searches go up for everyone around that time, because of the 4th of July. Now, that's reasonably obvious to us. But what if we saw an even bigger spike earlier, like in November. Could it be from Halloween? Well, we know the first step in our analysis is segmentation, and we immediately see that all the traffic is coming from India, and centered around Diwali festival keywords, which, like our 4th of July, causes a spike in firework searches. Now, this trend wasn't initially obvious to us, but by using the tools available, we can understand whether we can claim success due to our marketing campaign, or was it simply a rising tide that floats all boats, and had essentially nothing to do with our actual site or marketing.

Now the key here is that understanding these trends will allow us to compare apples to apples by controlling for those external factors, and keeping our data in context.

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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