I just got off the phone with Jim Fowler, the CEO and Founder of Jigsaw Data Corporation. I must say that in the beginning I simply didn't understand their whole business model but after an hour long conversation I was good to go. Most people don't have the time or ability to spend an hour talking to the CEO of a company they want to learn more about but I guess I'm lucky, hah! Anyway, understand of the Jigsaw business model only took about 10 minutes once the privacy issues were explained.

It was pretty fun talking to Jim about how Jigsaw works and how contacts are traded among the users of the system. He reminds me a lot of one of my all time favorite salesmen, Steve Wayne. Jim made no bones about the fact that he's a salesman first and he's motivated by money and a good business model. Perhaps that's one of the reasons Jigsaw was able to secure Series A VC funding from El Dorado Ventures back in 2003 when the VC's weren't getting handing out cash for anything. It's also important to note that back in '03 when they received their Series A round of funding they had not decided to allow users to purchase contact information for cash rather than just points. That's kind of a big deal since they began offering the ability for users to purchase contacts straight-up in September of 2004.

Okay, okay, I've said too much already. I don't want to spoil your appetite to see the Q & A with Jim when I post it later this week so I'm going to stop now. I will have a lot more inside angles on how their operation works as well as what makes them uniquely dissimilar from other business service social networking sites like LinkedIn and from data companies like Dunn and Bradstreet and InfoUSA.

I'm testing out a new pinging service called PongPong. It's like pingomatic without all of the nasty wait times [remind you of a certain blog search engine that rhymes with Aristocrati?]. PongPong is a client side tool that allows you to ping the major blog aggregators slash search engines from your desktop, thus alleviating the slow load times resulting from a billion users using a web based xml-rpc blog pinging service.

The developer of PongPong is Chris Simpkins [could this be him?], is the one that contacted me about his application and seems to be keeping a close eye on the blogosphere for reviews and feedback on his pinging software.

You can download PongPong here, it's currently in beta and is available for Mac OSX as well as Windows.

btw, I just installed it and am having problems... appears that some java config file is trashed or something. Chris, where are you?

Media Post's Search Insider email has a piece on a HitWise executive who is a self-described Data Geek. Unfortunately I can't link to the original article because their registration is down, tisk tisk. The article was based on a Q & A with Bill Tancer, HitWise's manager of worldwide research [interesting title]. The first paragraph in the post made me chuckle...

"...is a self-described data geek who's not only a number cruncher but also has an eye for spotting trends."

It was funny to me because I thoroughly enjoy data aggregation and analysis, and anyone else working in the data analysis field understands the implicit relationship between data analysis and pattern recognition. Although I'm no Ray Kurzweil, I've seen a few interesting patterns in my time. In fact, when I roll out the new blogging system on mshift I'll devote an entire section to market trends and pattern recognition.

Any successful entrepreneur recognizes patterns. I didn't limit that to technology entrepreneurs because pattern recognition is not something limited to those of us in the technology arena. Think about your local grocery store produce manager. He has to know when to begin purchasing oranges in order to meet the demand from his customers. As fundamental as that example may sound, seasonal fruits and produce are part of a pattern. Even though the 4 seasons follow the same pattern year after year, it's still a pattern.

The more complex the pattern, the more reliant on technology is the process used to recognize that pattern. If you wanted to find out when another hurricane could be expected to hit Florida you'd rely on your local meteorologist or the Weather Channel who would then rely on the National Weather Service who uses complex formulas and algorithms to predict the path a hurricane might take. These algorithms are based on patterns the NWS has seen reoccur in the past. The more often a specific behavior repeats itself, the more evidence the NWS has to deduce the possible causes of that behavior.

I say all that to simply point out the growing importance of pattern recognition in our lives and how every level of our lives are affected by it. How many patterns can you recognize in your own life? I challenge all of you to take a single day in your life and write down as many patterns as you can to see how often you repeat them throughout your day, then your week, then your years and your entire life. Classification of personal patterns & behaviors can be an enlightening experience.

To help you get started I'll give you an example of some of my own personal patterns and the categories of patterns they fall into.

I wake up every morning [lifelong behavior]
my wife wakes up each morning [multiple years for me & entire life for Shannon]
Our two girls wake up each morning [multiple years for Piper & 11 mos for Finley]
I get online [12 years]
I eat breakfast [1/8th of my life]
I drive my car [1/2 of my life]

As you look at each of my personal events you can see that the more interesting ones are the ones that occur the least. Those are the ones that beg questioning and research. You probably noticed that I only eat breakfast 1/8 of my entire life. Why is that, am I not a "morning person", do I not like breakfast? You'll see that the questions you ask are all possible underlying causes of that specific behavior in my life.

This simple example can be applied to any market, especially those online and this is how a data geek's mind works. We constanly question the why and pattern recognition is a part of our daily lives. Pattern recognition, trend spotting, whatever you want to call it, fascinates me. It's always changing. Finding the latest patterns and documenting why I believe they exist and then testing those hypothesis is like exploring a new land. Only I don't have to travel anywhere physically because the majority of my data mines are virtual since all of the data is digital.

Are you a data explorer?