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Bot Filtering could have more of an effect on reporting for certain types of websites.
Apparently, however, traffic inflation by bots has been reported as serious problem on certain websites, particularly those selling ad space based on pageviews: the more impressions that the advertiser and publisher report, the more they can charge the advertiser.
For other types of sites, this issue may have only minimal impact. How can you find out for your own site?
1. Copy a view.
2. In the settings for the view copy, select the Bot Filtering checkbox.
3. After a period of time, compare sessions and pageviews between the original view and the bot-filtered view.
In the test that I ran, there was a difference of only five sessions and six pageviews over the course several weeks, but you can very easily set up your own test as described above and determine if the impacts are greater for your own website.
For additional perspective on the bot issue, see this article on TechCrunch.
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The Google Tag Assistant panel indicates the presence of Google Analytics on a Web page.
The Google Tag Assistant extension for Chrome allows you to check for the presence of several different types of Google code snippets, or “tags”, on a Web page.
After the free and easy install, you can click the tag icon in the Chrome extension bar to display information about the Google Analytics code on the page, including the UA number, which identifies the Google Analytics property to which all raw website data is sent. It also offers suggestions, such as placing the Google Analytics tracking code within the
tags (which is recommended but not completely necessary for Google Analytics to execute correctly).
Interestingly, Google Tag Assistant also displays the container ID of Google Tag Manager container if this code is also present and indicates the UA number of any Google Analytics tags that you have deployed to the page through Google Tag Manager. (Remember not to confuse Google Tag Assistant with Google Tag Manager.)
One issue that Google Tag Assistant sometimes calls out is the occurrence of multiple Google Analytics UA numbers on a single Web page. It may be perfectly valid to have two different tracking codes with two UA numbers on a single page (for rollup reporting), but multiple tracking codes sometimes indicate a need for tighter management of the Google Analytics deployment.
Keep in mind that you do not need to be logged into Google Analytics or Google Tag Manager to use Google Tag Assistant, and that you can activate it to display Google tag information for any page on any website, not just your own.
Optimization is not only about analytics. While quantitative data is indispensable for website optimization, the qualitative feedback from usability testing can quickly provide insights that would take much longer to garner from Web Analytics data.
For example, it would be nearly impossible for Web analytics data on its own to indicate that you need a guarantee on your purchase page. A single usability test could quickly flag this potential issue. If one or two more testers voice the same concern, you might really need that guarantee.
You can run your first usability test for free at trymyui.com. (You’ll need to provide a credit card to sign up – just make sure to select one credit only, unless you want to purchase additional credits.)
Other types of qualitative feedback include surveys, as well as direct conversations with end users, colleagues, and clients who may have never had the opportunity to critique Web processes.
Of course, even with seemingly decisive qualitative feedback, we can’t assume that any change will increase conversion, so monitor key metrics after you make any change. Better yet, run a split test in Google Analytics Content Experiments or another testing tool to measure performance of the page variations.
In any case, don’t limit your optimization efforts to quantitative analysis. Incorporate qualitative channels for faster insights.
In Google Analytics, goals, custom reports, and dashboards are created at the view level. If you want to use that same asset in another view, property, or account – or if you want to share with other Google Analytics users – you can forward a link from the Share Assets screen, accessed from the view admin.
Segments are somewhat different in that they’re accessible in all views within the same Google Analytics account, so you’d share a segment with a different GA user, or potentially with yourself if you happen to maintain GA accounts under different logins.
When you share any asset in this way, you’re not sharing any data, but rather a link that another Google Analytics user can click and then apply to their own views. For example, the link below shares a simple custom report for sessions and bounce rate by referrer, but not any of your actual referral data.
This same sharing mechanism allows you to import predefined bundles of segments, dashboards, and custom reports, which you can access by clicking Import from Gallery in the Share Assets screen.
If you or your team have already created additional views for your Google Analytics property (or properties), congratulations. You’re already doing at least one thing the way you’re supposed to.
Why is it considered best-practice to have multiple views per property? For one thing, you should be filtering out your internal traffic and your development server activity, and there are also a range of other view settings and filter that can help you to clean, consolidate, and segment your view data.
However, you should not apply any settings or filters to your single All Web Site Data view. At a minimum, you should create a test view and a backup view.
As a note, the previous name for view was profile. In Google Analytics, the terms are synonymous. View is a more descriptive name, since the purpose of a view is to provide a particular view on your raw Website or app data.
You can create up to 50 views per standard Google Analytics account, but you do need Edit access at the property or account level.
Still have only that one view? Create test and backup views today, and try out a filter or setting in your test view. In any case, don’t be afraid to create additional views: backup and test to begin with, and whenever you need a more specialized representation of your data.
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The Converters segment includes users who have completed an Ecommerce transaction or a goal.
Google Analytics now provides the Converters advanced segment, which you can apply to your reports to view the pageviews, events, sources, and other characteristics that constitute successful visits.
More accurately, the Converters segment is defined with Users as scope, so it segments based on users who have converted or transacted during any session. If you instead want to segment only for the same sessions during which the conversion or transaction actually took place, you can copy the Converters segment and change the scope from Users to Sessions.
Similarly, if you want to focus only on Ecommerce transactions or the completion of a specific goal, you can define an advanced segment for users or sessions with goal 2 completions greater than 0, as an example.
In any case, segmentation in general is essential for gaining actionable insights from your reports. The Converters segment, or a similar segment that you create yourself, can specifically help you identify your success factors so you can adjust your Website navigation and marketing initiatives to generate more Ecommerce transactions and goal completions.
If you’ve applied any special report settings that you want to easily access again, you can save a shortcut. In this way, shortcuts are somewhat akin to custom reports, in that they preserve specific report settings.
Shortcuts save the report as configured with any of the following features:
• advanced segments
• secondary dimension
• table filters, default and advanced
• table sorting by column
• Comparison, Percentage, and other display types
One point to note is that shortcuts are not available under Share Assets in the view admin. Although it certainly would be useful to share shortcuts, advanced segments are created on a user-by-user basis, so the other GA users with whom you’d want to share the shortcut would not necessarily have all the necessary dependencies to recreate the shortcut configuration on their end.
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This custom report drills down from Device Category to Browser Version
Before rolling out a responsive or adaptive Website update to your users, it’s important to test the design changes on the same devices and browsers that your visitors are already using.
You can click the following link to import a basic device/browser custom report into one of your Google Analytics views:
If you are unable to source physical devices to test on, a fallback option is the device emulator built into Chrome or other available device emulators.
Note that in addition to the Users and Sessions metric, the custom report also includes Bounce Rate, just to demonstrate how current users are (and aren’t) interacting with your site across different devices and browsers.
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Unique pageviews represent the number of sessions during which the page was viewed at least once.
In Google Analytics, unique events and unique pageviews almost mean the opposite of what they sound like.
The unique events metric doesn’t indicate the number of unique times that an event occurred, but instead the the number of sessions during which this event occurred at least one time. Same thing for unique pageviews: the number of sessions during which the page was viewed at least one time.
It seems like the idea behind these metrics is that sometimes the fact that someone saw a page or completed an event at least once during a visit/session is more important than the number of times that this happened.
For instance, a page gets page value or counts towards a goal funnel the same way whether it was viewed one time or ten times prior to a goal or transaction. Similarly, if you set up an advanced segment based on page or event, the number of times that the page was viewed or event was completed during a session (or across all sessions if you set you advanced segment to User scope) doesn’t matter, as long as this happened at least once.
When you see unique as part of a metric name, think in terms of sessions.
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With Full Referrer as a secondary dimension, the Landing Pages report can identify cross-domain issues.
In a recent post, we identified missing tracking code and incorrect cross-domain setup as the two primary causes of self-referrals manifesting in the Referrals report within Google Analytics.
We can take advantage of the Landing Pages report to isolate both of these issues. Specifically, if we apply Full Referral as a secondary dimension, and also apply the built-in Referral Traffic advanced segment just to temporarily hide other traffic mediums, you can see specifically where the breakdown is occurring.
• If the landing page and full referrer are on the same domain, the referring page is probably missing the Google Analytics tracking code. Easy fix: include the tracking code.
• If the landing page and full referrer are on different domains (main site and checkout site, as an example), you have probably not configured cross-domain tracking correctly. We’ll examine cross-domain setup in an upcoming post.