Now that I’ve got treemaps on the brain, I keep noticing how many things could be better understood using this visualization technique. A few examples:

We thought it would be a nice demonstration to use data from the 1997 and 2002 US Economic Census (unfortunately 2007 isn't out yet) to see what kind of stories bubble forth. The demonstration was built using a component from JuiceKit™, our recently open sourced Software Development Kit (SDK) for building Information Experience™ applications. The SDK can be used by web designers and developers to build graphically rich and interactive information displays. JuiceKit currently integrates with Adobe Flex to create components that are easy to implement and aesthetically pleasing.

Check out the treemap here.

Here are a few of the macro-trends that I found:

• The rise of CostCo, Amazon, and Home Depot: This time period saw strong growth in warehouse clubs and superstores, online retailers (“electronic shopping”), and home centers.
• From manufacturing to services economy: Most of the growth was in service sectors (financial services, healthcare, professional services) while manufacturing was shrinking.
• Productivity gains, even in adversity: For struggling sectors, the employee declines almost always outpaced the sales declines — squeezing more sales per employee.
• Demographic shifts: Homes and services for the elderly were among the strongest areas of growth in the category of “healthcare and social assistance.”

And there were lots of little insights as well:

• No wonder hospital TV shows are so popular: Hospitals are the largest single employer as a business-type.
• Starbucks and Krispy Kreme steal the unhealthy food dollar: Cookies and frozen yogurt retail saw a rapid decline while coffee and donut shops flourished.
• Goodbye stand-alone pump: Gas stations with convenience stores overtook the just-plain gas station.
• It can’t last, can it?: Mortgage broker payroll up 177%.

Once you understand how to read treemaps, they are great for exploring data like this: hierarchical with both quantity and quality-type measures. In a true testament to their power, my wife admitted this visualization was “kinda interesting.”

We are pleased thrilled to introduce Concentrate™, an innovative long-tail search analytics tool. Concentrate is for SEO and paid search professionals who want to make sense of search keyword data and make the most of search investments.

Check out the demo here. Or try out the free version here (you’ll need admin access to a Google Analytics account).

We built Concentrate because we saw a fundamental conflict in the world of search analysis: On the one hand, search keyword data is terrifically interesting and valuable. It can tell you what your visitors and customers want and how they think about you and your products.

Unfortunately, search query data is also big, messy, and hard to get your hands around. In a typical month, the Juice site gets over 10,000 visits from over 7,000 unique keywords.

Even if I could somehow wrap my head around our top 100 keywords, I’d only understand 25% of the visits. For people spending money on search engine optimization or paid search campaigns, that’s a big blind-spot to accept.

We want you to understand and act on all your search data. Concentrate ingests data from sources that most sites already have available (e.g Google Analytics, Omniture, Coremetrics, Hitwise, Compete, etc.), enhances this data by finding common patterns and query types, and visualizes search phrases for exploration and analysis.

Over the next couple of weeks, we will share examples of some of the interesting things you can do with Concentrate, including:

Pattern identification to condense the long tail into keyword phrases with similar structures. For example, here are some common search patterns from a cooking web site (the “[x]” represents a wildcard).

Keyword visualization to show the connections between keywords and the relative performance of phrases. This wordtree shows the frequency of words within phrases (size) and average time spent on site (color).

Congratulations to Chris, Pete, and Sal for all their hard work, diligence, and creative problem solving to launch this solution.