Category Archives: Analysis

Visual and XML Sitemap Generator – See the flow of your website

While chatting with a colleague today (Hello, Beverly Sastri), we were saying it would be so great to have a tool that could “scan” a website and generate a visual sitemap of the site. This is particularly helpful for site re-design and development projects so that you can see how all the pages of the site connect with one another.

I have a wonderful tool called A1 Website Analyzer that I use to pull the page urls, titles, meta-descriptions, heading tags and keywords, for site analysis but Beverly wanted something more like a visual flowchart.

So, here it is, PowerMapper. The maps can also generate an XML sitemap, can be exported to CSV, a webpage or an image. Here’s part of an image from‘s website map.

Visual Sitemap - St. Rose Church

More Word Clouds – New York Times Homepage Content

While looking for new ways to play with Word Clouds, I did the cloud from the previous post on the SEOMoz blog main page. I have been using the clouds with keyword research as well, filtering on types of words, number of searches, etc.

I wanted to find some public (not proprietary client data) to play with, so I thought about News. Some of my hobbies revolve around researching my Ancestry and Scrapbooking. I love the idea of preserving information for future generations.

So, for the last couple of days, I have been pulling the keywords from the NYT Homepage. I exclude words that are related to date, brand name and function of the page and concentrate on keywords that are repeated 4 or more times (less than that and the cloud is very confusing!).

Following are word clouds for the last 3 days.

What do these images “tell us?” I’m not really sure. Right now, they’re just a snapshot in words of what was being reported/talked about on those days.

When Tableau 8 releases, and word clouds like this can be uploaded to Tableau Public – where interaction with the data is possible, these might be more fun. Like looking at the frequency of certain words over time, looking for trends in weeks or months of data. It could be the basis for some interesting sociological research. Or it could just be fun, like looking at old snapshots can be.


What can Word Clouds tell us? SEOMoz Blog Homepage Keyword Cloud

I’ve really gotten interested in Word Clouds since I’ve been playing around with the beta version of Tableau 8. It’s just so fun to see the words that POP in both size and color…

The following image is a keyword cloud using words from the SEOMoz blog homepage today, 25 Feb 2013. It’s been filtered to exclude date related terms and terms related to the functioning of the blog (like post, read full, comment, etc.). The size of the words is the average number of repeats on the site. The color shows whether the keywords are just in the content or if they appear in the page title, meta-description (or both) on the site. The image has also been filtered to show words with 3 or more repetitions (otherwise the volume of keywords makes it harder to see any patterns.)



Using a word cloud can help you visually focus on the words that are being used most often on a site. And compare that to the words you WANT the search engines to see on the site.

There are lots of variations of this keyword/word cloud theme… you could look at the Google AdWords keyword tool results of a scan of your site. Or, the keywords in your analytics account that show the keywords that are actually generating traffic to your site. Or the advertising keyword results via Google AdWords or Bing AdCenter.

Ah, the possibilities are endless! 🙂


The Beauty of Word Clouds | Look at your data in a new way

I love data. I really love turning data into information, going from columns of words and numbers into something that you can actually make sense of …

For example, here are the keywords that brought organic search traffic to my website in 2012 (excluding, of course the ubiquitous not provided and not set in GA)


It’s easy to see that Ask Joanne and other brand related keywords are the keywords with the highest search volume, but how else can we make sense of this data.

Here is a word cloud that excludes all phrases with “jo” in them – which covers most variations of my business name and website name. It also excludes all keywords that generated only one visit (to eliminate some of the more fringe words.)

Ask Joanne Keyword Traffic Analysis

In this word cloud, the size indicates the sum of visits to the site, the color indicates the bounce rate – orange is a higher bounce rate (only one page of site viewed), blue is a lower bounce rate. So, we can see that the phrase What is Yext brought in the greatest number of visitors, and that it had a high bounce rate. However, since it’s a blog post, it doesn’t bother me much that the page had such a high bounce rate. It would be good, however, to track if any outgoing links on that page were clicked (like to my Yext Affiliate link). I should know how to do this.. but with the asynchronous Google code, I actually have to research how to implement it.

You can also look at Word Clouds in other ways:

Data can further be refined, this cloud contains phrases excluding brand name with a bounce rate that is better than the average bounce rate:

Ask Joanne Keywords by Bounce Rate


Or phrases that brought traffic that visited at least 2 pages per visit:

Ask Joanne Keywords with greater than 2 pages per visit

Keyword Research Data Visualizations

I recently found a handy way to do some theme-based, in-depth keyword research.

Start with what you  know as your “head phrases,” the short phrases that form the “root” of many of your keyphrase variations.

Use a tool like SEMRush‘s phrase match report to find other, related phrases along with estimated search volumes, CPC costs and number of results on Google.

Use this data to generate data visualizations so you can SEE your keywords:

Keyword Research Dashboard at Tableau Public

Click the image to get to an interactive keyword research data visualization .

Diving into the DATA

Working with Tableau has helped me to understand many of the ways that rows and rows of data can be turned into useful information.

For example, I did a little bit of keyword research, using Google’s AdWord tool to try to find the best keywords for a potential client to optimize on.

The initial result is a data-download from Google that looks something like this:

Data Download from Google AdWords Keyword Tool

In Excel you can sort, arrange and even highlight certain rows based on criteria you set. However, by quickly pulling this data into Tableau, you can turn an unmanageable list, into a visualization that can clearly help you see where the keywords fall within certain criteria like greater or less than average search volume, greater or less than average costs-per-click and even by defining a range of search volumes, which keyphrases fall into a range that can reasonably be assumed to provide a good return on advertising investment.

Tableau Software – A Data Analyst’s Dream

Here it is, my first publicly published data visualization:

Cancer Incidence Rates by State and Cancer Site (Stats from National Cancer Institute)

Facts quickly gleaned from this visualization:

  • Breast and Prostate Cancer are the highest incidence cancer sites in the United States
  • The District of Columbia has the highest Prostate Cancer Rate
  • Massachusetts has the highest Breast Cancer Rate
  • Kentucky has the highest rate of Lung Cancer per 100,000 people

Some helpful tips for interacting with this visualization:

  • At the top of the screen are tabs for the different “sheets” of the visualization (Dashboards are sheets that combine one or more detail sheets): 
  • If you hover over a column heading, you get a little icon that allows you to sort the data in ascending or descending order:
  • You can click on a type of cancer or a state and either exclude it, or display only that data: 
    • Use the <ctrl> key to select more than one filter at the same time.
  • You can also filter the data by State:
  • To Undo or Reset to the default settings, click on the reset button at the bottom of the visualization:
  • You can get more detail about any datapoint by hovering your mouse over it to get a “tooltip” to pop-up: 

Feedback welcome. More visualizations coming soon.