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Learn about Term Clouds in Google Analytics
Category: Google Analytics

Why are Term Clouds in Google Analytics so Special?

March 19, 2011

Well, many of us Google Analytics Consultants performing SEO analysis provide stakeholders with data visualizations because they simply and instantly tell the story of what is going on in large/complex data sets.

Previously, this type of visual analysis required manual integration with the Wordle word cloud tool.

Now, in Google Analytics Version 5 there is a new report view called “Term Cloud“, which is easily accessible within almost all of the “Traffic Sources > Incoming Sources” reports.

Wait…What the Heck is a Term Cloud?!?

Term Clouds, commonly referred to as Word clouds, display words based on their frequency. Basically, words that are bigger in the cloud appear more often. Check out the examples below that make this much easier to understand.

How to Access the “Term Cloud” View

Within the “Search” reports and the “Adwords > Keywords” reports you can change the view from the default “Data” view to the “Term Cloud” view.

How to Access the Term Cloud View in Google Analytics

After you change the view from the default “Data” view to the “Term Cloud” view, it is recommended that you change your date range to 90 days for improved data analysis reliability.

Select 90 Day Date Range for Data Reliability

Term Cloud SEO Analysis Examples

How well is your site driving non-branded, targeted keywords?
The ultimate goal with Search Engine Optimization (SEO) is to increase the top of your sales funnel by bringing new visitors to your site. After you perform keyword research to determine where the search query opportunities exist based on volume and relevancy, you will have a target list of primary and secondary keywords.

Before you optimize your site, and at least on a monthly basis as you optimize, it is a good idea to measure how well your site is or isn’t driving people to your site via these targeted terms. The “Term Cloud” view is a perfect tool to analyze and share this data with management and other non-technical users.

The following Term Cloud examples represent aspects of SEO analysis we perform for SEO audits and reports, which will enable you to gain key insights into your SEO performance.

Term Cloud Analysis showing Good SEO

If your website SEO is working well, then you should be receiving a large volume of broad to long-tail keyword traffic that doesn’t include branding like your company name, as in this example below.

Good Prominence of Targeted Keywords

Term Cloud Analysis showing Weak SEO

In this example, Branded keywords are the only terms that have prominence in this Term Cloud used to analyze the organic keywords that are driving traffic to this site. Even if your brand awareness is extremely strong, you should still see targeted keywords stand out from the keyword noise.

Low Prominence of Targeted Keywords

Which Keywords are Bouncing?

Below is an example of using the “Term Cloud” view to identify your worst performing keywords. Just change the Keyword drop-down (highlighted below) from “Visits” to “Bounce Rate.” Then you can find your worst performing keywords like we did which is highlighted in red below.

Be aware that low visit keywords can throw off the quality of your analysis so we recommend that you use the search filter to include visits with a significant volume. In this example, we only included visits greater than 100.

Use Term Clouds to Identify Your Worst Performing Keywords

Which Keywords are Driving the Highest Quality of Visitor (measured by pages/visit)?

Identify Keywords Driving Highest Quality Visits

Hope you enjoyed this tour of the new Google Analytics Term Cloud view and how to use it to improve your website SEO analysis.

Keep an eye out for more posts on how to use and benefit from all the new enhancements in Google Analytics Version 5. Especially, the forthcoming post on how you can now use events for Goals.

  • Word clouds. Still around, are they? They need to either improve or fade away.

    A word cloud has several available dimensions — size of type, location within the cloud, color, and color intensity. A good word cloud would use all of these dimensions and current word clouds use just one. Location (adjacency) could represent either similarity or co-occurrence. Color could represent a typology (problem words vs solution words, or whatever fits into your strategy). Color intensity could represent something quantitative, such as pages per visit.

    Google absolutely has the in-house talent to make word clouds into something better. What a shame they didn’t bother.

  • Chris,

    I agree with your assessment that Google could have done something even better. For now I am happy to have this basic visualization tool that can help us more easily communicate when data tables overwhelm executives.

    Perhaps you are lucky enough to work with executives that are more engaged and willing to dig into data tables, but even this limited word cloud functionality will help us quickly communicate large conceptual issues. Clearly, it won’t allow us to provide deep insights but that isn’t what we will use it for.

    Thanks for the rant. Maybe you will be more excited by the post we just put up on “How to Use Events as Goals.” This should get a savvy analyst like yourself more excited. Then again, I get the impression you are not a fan of Google Analytics, right?

    BTW, I enjoyed your post on “What, exactly, do you consider a search engine?”

  • Kayden – I’m actually a fan of GA lately, now that it has grown up! Before the functional improvements of the last year or so, I was generally happy to see *other* people using it because, being free, it brought so many people into the web analytics world and taught them the basics.

    But I do object to the fact that it’s funded by my paid search fees — I think it’s time for it to pay its own way and let my paid search costs find their own level. Also, as an extremely well-funded freebie, it kills worthy competition not necessaily because of its merits but because it’s being given away.

    I guess I’m not much of a fan of Google. What do you think?

  • I agree with you in regards to how Google Analytics helped evangelize web analytics. Plus, GA has helped raise awareness of how important ease of use is and luckily other analytics platforms like WebTrends and Omniture are finally listening. More emphasis needs to be on the analysis and getting insight, not setting up, learning and never using overly complex interfaces.

    I don’t really have a problem with Google’s paid search fee funding model. Several pretty awesome free and paid analytics technologies have come out in the last couple years which have been successful even with GA being free.

    GA being free has helped to keep the pricing of other analytics solutions like WebTrends and Omniture in check. Their licensing fees were getting out of control. They have been much more aggressive with their pricing as of late, which I believe is partly due to the pressure from a solid free solution like GA.

    Don’t get me wrong though, I definitely appreciate many of the sophisticated analytics tools inside Omniture that let you drill in much further to make insights that wouldn’t be possible in GA. Especially for high traffic volume ecommerce sites that are converting at high levels, you need a more sophisticated solution than GA.

Kayden Kelly
About the Author

Kayden is the founder and CEO of Blast Analytics & Marketing. He leads overall strategy and execution in positioning Blast as a leading analytics and digital marketing consulting company. An industry trailblazer who stays ahead of trends and opportunities, Kayden has spent nearly two decades building his expertise in all areas, with a deep focus on analytics, search engine optimization, and user experience. He is an evangelist for “the customer,” helping clients create sustainable competitive advantage by developing, optimizing, distributing, and connecting valuable content to customer needs. Connect with Kayden on LinkedIn. Kayden Kelly has written on the Web Analytics Blog.

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