The Analytics and Site Intelligence Blog @ MoreVisibility

What is Bounce Rate in Google Analytics?

Melanie Wahl — Wed, 23 May 2012 13:21:55 +0000

THE DEFINITION

Bounce Rate, specifically the Bounce Rate Metric in Google Analytics, is the percentage of single-page visits to total visits of a certain Dimension. For example, say you are looking at your Organic Traffic and sort by search engine. You follow the row across and see that Bing is delivering a 75% Bounce Rate. This means that 75% of the visitors coming from Bing to your website during the date range you have selected are visiting one page and leaving your site. Depending how your Google Analytics account is set up, this may include closing the browser, directly typing in a different site’s URL into their browser’s navigation bar, or clicking on a link to one of your social media sites or off-site blog. This third case is important to note, because unless Google Analytics has been set-up to track these off-site channels as part of the account, a visitor will be considered a Bounce even though they are still interacting with channels your brand controls.

IS A HIGH BOUNCE RATE BAD?
A high Bounce Rate typically indicates that a visitor did not find the page they landed on relevant to their interests or it did not fulfill their drive to click-through on the referring link. This is not always the case. If your blog is being tracked by Google Analytics and a visitor lands on one of your blog posts and the information they seek is clearly available, they may have no further interest in diving deeper into your website. A low Bounce Rate, on the other hand, does not necessarily mean your users are happily engaged with your site. If you pair a low Bounce Rate with a high number of Pageviews and low conversions, your visitors may be frustrated and unable to find what they are looking for even after searching and are leaving your site unfulfilled.

If you are looking for ways to improve your bounce rate, read our blog post: Down about your Bounce Rate? Do these five things to improve it today!

KISSmetrics has an interesting infographic about Bounce Rate that includes an equation, Bounce Rate metrics by industry average, and a number of tips to improve your Bounce Rate.

BOUNCE RATE vs. EXIT RATE (% EXIT)
Bounce Rate is the percentage of single-page visits to total visits, whereas Exit Rate (% Exit) is the percentage of site exits that occur. A visitor, who visits your website, loads one page (or blog post) and leaves is considered in both your Bounce Rate and your Exit Rate. A visitor who visits your website, loads one page (or blog post) and continues on to another blog post or another page on your site, is considered in only your Exit Rate.
To view the Exit Pages for your website – the pages where visitors are leaving your site from, go to the Exit Pages report under Content > Site Content > Exit Pages.

Basic Google Analytics Checklist: Getting Started With Google

Melanie Wahl — Mon, 14 May 2012 12:10:21 +0000

The following is a basic Google Analytics configuration checklist for when you start using the platform (or when there have been changes on your site and you want to make sure everything is setup and working properly).

1. Google Analytics Tracking Code

What version of the Google Analytics Tracking Code (GATC) is currently being used if any and where is it placed? Is data currently being populated in the account? Is the GATC on all pages of your website (including 404 pages, footer pages such as disclaimer, terms of service, or other similar pages, etc).

2. Sub-Domain and/or Cross-Domain Tracking

Do you have multiple sub-domains? Do you have access to change the source code for the pages on all sub-domains and are all webmasters on board with the change? If not, realize that Google Analytics can only track the sub-domains that include the GATC. Do you have multiple domains that you want to track? Realize that the links between them will need to be set-up correctly. If in the future you wish to add any additional sub-domains or domains, make sure that they are properly set up as well.

3. Goal Configuration

You can have a maximum of twenty goals, sorted into four sets of five goals each. While setting up goals, you can also setup funnels. Goal funnels can help you visualize the path that a visitor took to completing the goal. They can also help you see from what part of the funnel process visitors are exiting and if they are leaving the site entirely or navigating to a different page.

4. E-Commerce Configuration

If you have an e-commerce site, you will want to make sure your e-commerce code is tracking correctly. It should be noted that the e-commerce GATC replaces the standard GATC.

5. Google AdWords Linking

If you currently use Google AdWords, linking your account with a Google Analytics account can allow you to better understand your data.

6. Google Webmaster Tools Syncing

If you are currently use Google Webmaster Tools, syncing your account with Google Analytics can reveal a wealth of knowledge about your website in the easily manipulated Google Analytics interface.

7. Event Tracking

Coding your site to track specific events (such as a PDF download) can help you better understand how visitors interact with your site. Additionally, events can be set up as goals. This allows you to set up a funnel for an event.

8. Social Tracking

Google Analytics offers social tracking reports so you can better understand how social media impacts your website.

9. Site Search Configuration

If you have onsite search setup, Google Analytics can help capture what your visitors are searching for. Consider looking to this report for navigation change or new pages about topics that are often searched for on your site.

10. A Word About Filters

Google Analytics allows you to add filters to your data – however, it should be noted that once a filter has been added, the data that has been filtered over a time period can not be unfiltered. For example, if you create a Google Analytics account in January and then add a filter February 1st – but realize on March 1st that the filter was written incorrectly and would exclude some data you wanted to include you will not ne able to get the February data back. Unfortunately, even if you delete the filter going forward, any reports that cover the February time period will only be able to show the filtered data.

Social Flow Visualization in Google Analytics

Melanie Wahl — Fri, 04 May 2012 13:44:34 +0000

The Social Visitors Flow report in Google Analytics, located under Standard Reporting > Traffic Sources > Social > Social Visitors Flow, allows users to obtain a deeper understanding of their website visitors who arrived through social sources. You can assign a date range, compare a date range to the past, select a segment, or increase or decrease the number of connections between steps in the flow. The more connections, the longer the social flow report will take to load, but the more information you can see visually.

If you click on one of the boxes or nodes in the flow, three options appear. The first option, “highlight traffic through here,” allows you to highlight all traffic that originated from a specific social source or passes through a specific page (depending on which node you click on and select it from) and grey-out all other nodes and pathways.

The following is an example of a highlighted path of traffic that originated from the social source: Blogger.

The other two options, “View only this segment” and “Group details,” allow you to further customize the social flow visualization report to see the data that is most helpful to you. The first will delete all nodes not related to the selected node (a cleaner view than the highlight/graying solution under “Highlight traffic through here”) and the second brings up an option box where you can view the data (displayed visually in the flow) in table form.

Three Flow Visualization Reports in Google Analytics

Melanie Wahl — Wed, 25 Apr 2012 12:03:21 +0000

Our previous blog post, entitled Google Analytics Flow Visualization Date Range Comparison, covered the addition of the “Compare to Past” date range feature in the Flow Visualization Visitors Flow report. This feature is available in all three Flow Visualization reports: Visitors Flow, Goal Flow, and Events Flow.

The Visitors Flow report, located under Standard Reporting > Audience > Visitors Flow, allows Google Analytics users to better understand visitor behavior.

The Goal Flow report, located under Standard Reporting > Conversions > Goals > Goal Flow, allows Google Analytics users to visually see the paths taken by those visitors who complete goals, including non-URL goals such as engagement goals like Time on Site or Pages Visited. For this Flow Visualization report, make sure to select the goal you wish to view from the first drop down menu. In the following example, we are viewing Newsletter Sign-Ups.

The Events Flow report, located under Standard Reporting > Content > Events > Events Flow, allows Google Analytics users to better understand visitor behavior in relation to the Events set up onsite. Users have the ability to segment the data and to display Event information as Category, Category / Action, or Category / Action / Label.

The three Flow Visualization reports are a great feature of Google Analytics that allows users to dive deeper into the relationships of different pieces of data about a website. If you have questions about any of these three reports, please contact MoreVisiblity or sign-up for a free Google Analytics Consultation.

Google Analytics Flow Visualization Date Range Comparison

Melanie Wahl — Tue, 24 Apr 2012 12:11:45 +0000

The Visitors Flow report in Google Analytics, located under Standard Reporting > Audience > Visitors Flow, now allows users to compare data with past date ranges to better understand how users interact with a website over time. The official announcement was made on the Google Analytics blog in the post entitled Better Insights with Flow Visualization Enhancements. The following is a screenshot of how the Visitors Flow report looks before you click “Apply” to assign a comparison with a past date range.

Notice that after you click “Apply,” the flow updates with green increase percentages or red decrease percentages indicating how this data compares to the time frame you just set.

This report can help answer questions like:

What pages on what paths of my website increased in visitors over this time frame?

Are more people reaching the “thank you” page or “order completion” page than before? Are certain pages delivering more traffic to this page than before?

Visitors Flow is one of three Flow Visualization reports currently available in Google Analytics. Our next blog post will touch on the three different Flow Visualization reports currently available: Visitors Flow, Goal Flow, and Events Flow.

Google Analytics’ Java Support report: Part II

Melanie Wahl — Mon, 02 Apr 2012 15:22:12 +0000

Our previous post touched upon the importance of the Java Support report, located under the Browser & OS report (Standard Reporting > Audience > Technology > Browser & OS, with Java Support dimension from the Other drop-down under Primary Dimension and the Data display type). We also promised to answer two main questions website owners have after seeing that visitors with Java support often have three times as many conversions as those who do not:

How much of your traffic does not support Java?
How can we calculate the potential amount of revenue being lost due to Java?

Question 1: How much of your traffic does not support Java?

For the following example, there were 141,706 visits during the one year date range, of which 31,260 (approximately 22%) did not support Java. That means that approximately one out of every five visitors to the website had trouble viewing some parts of the webpages.

Question 2: How can we calculate the potential amount of revenue being lost due to Java?

Keeping with the same example, let us calculate how much revenue is being left “on the table” due to there not being a version of the website to serve to visitors who do not support Java.

First, a basic formula:

Second, the numbers from our example:

In this scenario, there was potential for nearly $90,000 more in revenue if the visitors who did not support Java were converted at the Conversion Ratio and Average Order Value of Java Supporters.

Carefully testing your pages, especially those in the funnel, who are currently served with Java in scenarios where Java is disabled can help your web team and marketing team identify possible areas to test and tweak over time. Additionally, you may consider serving different pages that are coded without Java to visitors depending on whether they support Java.

Revisiting this report after implementing webpage changes or multiple served versions can help you gauge the success of your efforts.

Please don’t hesitate to contact MoreVisibility if you need help understanding reports in Google Analytics or if you need a full website analytics audit.

PS: Another way to consider the data is that in total there were 141,706 Visits, that break down to $427,197.85 in Revenue from 110,446 Java Supported Visits and $36,780.17 Revenue from 31,260 Visits. There were 951 Java Supported Transactions and 71 Non-supported Transactions. If the 31,260 Non-supported Visits were to convert at a Java Supported Ecommerce Conversion Rate of 0.86% there would have been 268 Conversions/Transactions instead of 71. If the incremental Transactions (268-71=197) have an Average Value of $449.21 as the Java Supported ones do, the total potential increase in Revenue during this time period would have been 197 x $449.21 = $88,494.37 (some variation since you can’t have part of a transaction and there is some rounding). So approximately $90,000 was lost potential.

Google Analytics’s Java Support report: Part I

Melanie Wahl — Fri, 30 Mar 2012 12:42:12 +0000

Businesses strive to create websites that not only have the look and feel of their brand, but that are user friendly. To this end, during the design and testing phases of website creation a site may be tested and tested again for user experience, functionality, data collection, browser compatibility, etc. One area that can be tested by browser but not by individual users is Java support.

If you have a beautiful website that has Java enabled pages throughout the conversion funnel, you may be curious to get your hands on a report of whether your website visitors are having trouble converting due to their not allowing Java. Google Analytics offers such a report, but it takes some digging and configuration to find.

First, you want to navigate to the Browser & OS report:
Standard Reporting > Audience > Technology > Browser & OS

By default this report uses the Primary Dimension of “Browser” and default display of “Percentage” – to reach the Java Support report, select the Java Support dimension from the Other drop-down under Primary Dimension and the Data display type.

Then select a Goal Set or Ecommerce to see the breakdown of conversions by visitors who have Java support and those who do not. In our findings, those with Java support often have approximately three times higher Ecommerce Conversion Rates and Per Visit Values than those who do not.

That being said, there are two main business questions to be answered:

How much of your traffic does not support Java?
How can we calculate the potential amount of revenue being lost due to Java?

We will answer these questions in our next Analytics blog post.

Please don’t hesitate to contact MoreVisibility if you need help understanding reports in Google Analytics or if you need a full website analytics audit.

Data Sampling in Google Analytics

Jarret Streiner — Thu, 15 Mar 2012 12:45:54 +0000

What is Data Sampling?
In Google Analytics it means selecting a subset of data from your website traffic.

Why is this done?
The idea is that using a subset of data will provide comparable results to using the full amount of data available. Using a smaller data set will speed up the process for reporting, as pulling larger amounts data slows down queries.

When will I see Sampled Data?
When a report collects data from a large data set, over 500,000 visits, visitors or pages, you will see that the data collected is sampled. While running Multi-Channel Funnel reports, sampled data will be used when you have over 1 million conversion paths.

When running reports in Google Analytics you may see a yellow box at the top of the report which says:

This gives you specifics on the percentage of visits that the report samples from. As you can see, the average of visits is a little over 210,000, but the percentage of visits is lower in each instance, based on the amount of data each report has to sample from. The larger the amount of data pulled, the lower the percentage of visits that will be sampled into the report.

A new feature in Google Analytics is the Adjust Sample Size tool. The slider, which is located below the date range, allows the user to choose between faster processing and higher precision.

This tool will allow you to adjust the sample size from the default of 250,000 (which is the center of the slider) up to 500,000 visits. As you will see in the samples below, the data samples differ depending on where the slider is placed. The c can be placed anywhere across the path, not just on either end or the middle of the tool.

When you choose a sampling threshold, that preference will be used in all reports until you close Google Analytics.

Google Analytics Webinar Summary: What’s New in Google Analytics

Jarret Streiner — Fri, 09 Mar 2012 13:54:18 +0000

As Google enhances and updates their analytics tool, MoreVisibilty will continue to stay on top of these features to help you understand what they do and how they will help validate then guide web site traffic and marketing efforts.

On yesterday’s webinar discussed four of Google Analytics newest features; Flow Visualization, Real Time Web Analytics, Multi-Channel Funnels and Social Media Tracking. To be able to use and evaluate these new features you will need to be running the newest version of GA. You can do this by simple clicking on New Version:

We started off our webinar with Flow Visualization, which uses a graphical representation to show how users flow across pages on your site. We looked at three types of flow visualization; Visits, Event and Goals and the impact they have on design and layout.

Next, we took at look at Real Time Web Analytics and the importance of this powerful tool in relation to its affects on marketing efforts. We reviewed the benefits, the best time to use it and what you would learn from the numbers provided.

Our third new feature was Multi-Channel Funnels, which are reports that are generated from conversion paths, the sequences of
interactions (i.e. clicks/referrals from channels) during the 30 days that led up to each conversion and transaction. During the discussion we went over the way funnels interact and what an “assisted” conversion meant in relation to the first and last interaction attribution.

The last but not least feature discussed was Tracking Social Media and how Google tracks its engagement. We discussed that having a social media account did not equal being socially engaged and using social media to view, share, like or tweet is the measuring stick.

To view our complimentary on-demand webinar, please click here.

As Easy As 1, 2, 3: Custom Variables – Part III: Visitor Level

Jarret Streiner — Thu, 01 Mar 2012 13:29:46 +0000

In Part I of this series we spoke about session level variables. In Part II we discussed page level variables. Now we are going to talk about Visitor Level variables. This variety of variable is the highest of the three levels; the tag assigned is permanent and remains disassociated during following visits until the visitor deletes the cookie or overwrites it’s value.

Visitor-level custom variables are used to differentiate the type of visitors who access your site across multiple sessions, such as a member, account holder, visitor or guest. You can make use of this variable to evaluate which users are paying members, what type of membership they have (if you have multiple levels), and visitors who are only guests. This custom variable would be set as a one-time function, given that the value would be carried across the life of the visitor cookie.

Visitor Level Variables follow these coding guidelines:
_setCustomVar(index, name, value, opt_scope)

The coding set up would look like this:
_gaq.push(['_setCustomVar',
1,                // This custom var is set to slot #1. Required parameter.
'Member Rate',    // The name of the custom variable. Required parameter.
'12 Months',        // The value of the custom variable. Required parameter.
// (possible values might be Free, 3 Months, 6 Months, and 12 Months)
1                 // Sets the scope to visitor-level. Optional parameter.
]);

The finished coding would look like this:

</script>

Now that you have set your variables and are tracking them, it is time to see the results. You can find your reports in Visitors > Demographic > Custom Variables report.

The report will display your variables as a “KEY”. There are 5 keys available with 5 values attached to each key.

During our three part series on As Easy as 1, 2, 3: Custom Variables, we have learned how to define additional segments to apply to visitors, about coding parameters, where and how to use each variable and how the different levels; Session (Used to distinguish different visitor experiences across sessions), Page (Used to define a collection of page-level activities by your users) and Visitor (Used to distinguish categories of visitors across multiple sessions) are unique.

We had a look at the reports and the type of information you can choose to add to your data flow. With custom variables, you can label additional segments to apply to your visitors in addition to what is already provided by Google Analytics.