Where should you relocate? How well would you fit?

Great news!  You have just received a new job opportunity.  But, it is not that close to home.  The commute could be awful.  Maybe you should relocate.  But, where should you go?  How long will it take you to fit into a new area?  Will you really be a fit?

Analyze Corporation provides insights that can help with all kinds of decisions.  We have a vast collection of information on consumer demographics and consumer behaviors that we tap for solving problems.  We have recently posted a web-based tool that allows a user to evaluate various characteristics of other communities.  This could help narrow down the search when considering re-locating.  By feeding the site a desired zip code and answering several questions, the program will show you how you compare to people in your potentially new neighborhood. 

Below is an example of the web-screen’s questionnaire that is filled-in with some sample data:


In this case, the user’s annual income level ranges from $60-74K.  The following graph shows how the user’s income level compares with others who live in the 22003 zip code.


The income ranges for the people in the 22003 zip code are shown with the green bars and are separated into 8 income ranges.  The user’s income range is designated with the orange bar.  By hovering the mouse over any bar in the chart, a pop-up will appear that indicates the income range for that bar as well as the percentage of that range.  From viewing the chart above, the user can see that his income level would place him slightly lower than most of his future neighbors.  In fact, he would be in the lower 35%.


Other comparison charts showing community demographics  are available as well.  The chart below shows how he stacks up in the area of education:


In terms of education, there are four categories.  The green bars show the education levels of the 22003 zip code.  The yellow bar shows the education level of the user.  From viewing the education details in the graph above, the percentage of those who have completed just high school is similar to those who have completed college.  Both of these categories have a slightly greater percentage than those people who have completed graduate level work.


If this kind of data and analysis is intriguing, keep in mind that Analyze Corporation has all kinds of data and experience in analytics that can help you and your business gain valuable insights.  Give us a call at 703-273-1900 or fill out our contact webform and we will reach out to you via email.

To actually run this web application, go to this link.  

News Flash: Direct Marketing is not Dead!

I've said it before and I'll say it again, direct marketing is not dead (cringe). Don't worry, I'm not diving into the details, I'm only stating a fact. And let's face it, facts are cool. They validate statements and opinions, and quiet all the objectors. So... to validate my statement that direct marketing is not dead, here are ten facts about direct marketing and mail. A word to the objectors, a wise man named Confucius once said, "real knowledge is to know the extent of one's ignorance." For those who agree, grab your blanket and a warm cup of hot chocolate. Here are ten satisfying facts about direct marketing/mail. 

source: DMNews

1. 52% of over-performers say their organizations leveraged data and analytics to improve marketing effectiveness compared to just 35 percent of under-performers.

source: CMOcouncil

2. Direct Marketing produced $2.05 trillion in sales in 2012 - representing roughly 8.7% of US GDP.

3. "Traditional offline marketing," which includes direct mailers, was a $93.6 billion industry in 2012.

source: TheDrum

4. 79% of consumers will act on direct mail immediately compared to only 45%, who say they deal with email straightaway. This research is from the DMA.

5. Direct Mail Triggers an online response: 44% visit the brand’s website, 34% search online, and 26% keep the piece for future reference.

6. In just over 1200 surveys, 74% said personalization of mail was important.

7. 66% of consumers keep their mail, 17% regularly keep an item of interest, and 48% do so occasionally.

8. 56% of people think that print mail is the most trustworthy of all communication channels.

source: Yahoo

9. A recent Direct Mail Information Service report highlights that over 75% of direct mail is opened by the recipients and 63% read the contents.

source: DirectMailMarketing101

10. According to a USPS poll, 64% of customers said they valued the mail they received, yet only 36% of business owners believed customers valued their mailings. 

I hope you found these facts new and enlightening, and can make use of them in your marketing strategy moving forward in the year.

Socio-freak-onomics: Do baseball fans pray more than hockey fans?


Winter ended late this year in Boston and people are still trying to figure out how to dress.  The Bruins are in the playoffs, which means we're in one of those weird years here where Hockey and Baseball seasons overlap.  Should we be wearing Red and Blue, as summer fashion suggests, or put on one more weeks’ worth of black and yellow to show the B's some spirit?  (I'm wearing Red Sox under my college sweatshirt; statisticians have always been partial to Baseball.)

In this way, our own Dr. Nolker and I could not be more different.  I coach special needs baseball; he plays amateur hockey.  Sometimes it seems like baseball and hockey people are from different worlds.  Ever wonder what data science has to say about it?  I looked at sociometric data from 100 thousand US households to try to come up with an answer.  Here's what I found:

(1) Hockey fans are twice as likely (20% vs 11%) to ski recreationally.  No surprises there.

(2) Hockey fans are more likely to gamble at a casino (24% vs 19%).  Baseball folks don't gamble, unless it's in the locker room.  (Remember Peter Rose?)

(3) Hockey fans are more likely to smoke cigars or premium tobacco (17.5% vs 13%).  Chewing tobacco was not factored.

(4) Baseball players are significantly more religious.  38% read religious or inspirational books and magazines, vs. 29% of hockey fans.  (We had 93 seasons without a series win to get some religion.) 

(5) Hockey fans are better off, financially at least.  They are more likely to have an "upscale lifestyle" (53% vs 48%) and a credit card from a premium department store (57% vs 50%).  They'll need one to buy all those sweaters and ski equipment.

At least there was one thing we could both agree on.  Only two baseball fans and absolutely no hockey fans (0% vs 0%), reported that they watch professional soccer.  Guess we're not so different after all.

Do you have an interesting topic you'd like us to research and write about?  Send us your ideas for future topics. 

Pull meaning from social networks without reading every post

Recognizing that if you're reading our blog or our social media posts, it’s unlikely that you're attending Dr. Nolker’s presentation at the Sentiment Analysis Symposium, we’ve posted a paper on our site that you can download for free entitled, “Social Computing and Weighting to Identify Member Roles in Online Communities.” This paper was the genesis of what has become a groundbreaking approach for pulling meaning out of social networks. 

For those that would rather get the meat without sifting through the paper, here’s a summary of the paper and how it's useful when doing social network analysis: 

A. Not everything that everyone says in an online social network is worth analyzing. We've all met that guy or gal that post things that don't matter. 

B. Structure mining provides a means for finding and weighting which individuals are most worth analyzing and which individuals we should ignore in an automated fashion.  

C. Not surprising to those that work in teams, the most important people to analyze are Influencers and Motivators (defined more specifically in the paper).  

D. You can detect roles (like Influencers and Motivators)

in online communities (like Facebook, LinkedIN, Twitter, or other more specialized forums like those for Hackers) and sift out individuals that detract from a community by measuring things like:

  • The number of one and two way conversations, 
  • Whether those conversations or posts are directed at individual persons, 
  • The number of different people users converse with, and 
  • How close (first, second, or third level connections) a user has in a given social network, among others.

C. This type of analysis can help businesses target to whom they market, social networks measure how healthy their communities are, and data scientists choose whom to target for more in-depth sentiment, natural language, or link analysis. 

Download the paper for more detail.

Dr. Nolker to Present at Sentiment Analysis Symposium this Week

Dr. Robert Nolker, Analyze’s Vice President of Research and Development, will be presenting at the Sentiment Analysis Symposium in New York this week, March 5, during the Technology and Innovation workshops. Dr. Nolker will be presenting his groundbreaking research in identifying user roles within social networks using structure mining approaches.  Dr. Nolker’s approach provides two primary benefits.  First, a user’s role provides insight into how much weight their opinions or comments should be given in text and sentiment analysis. Second, role identification can be used to reduce the size of your dataset, an important step to reducing processing costs when doing text analysis.  Dr. Nolker will demonstrate these structure mining techniques on cybersecurity networks, more specifically software vulnerability research forums, in order to demonstrate how to choose the most important targets for additional sentiment and text analysis. 

Analyze successfully uses advanced analytics to improve marketing return on investment, reduce operational labor costs, and improve cybersecurity by providing businesses next generation analytics using machine learning, graph theory, and structure mining techniques. 


Read more about Dr. Nolker at http://analyzecorp.com/executiveteam

A Method for Predicting Fishing Activity Based on Geospatial Motion Behaviors - Summarized from an Analyze Technical Report


Illegal fishing is a significant economic and environmental challenge for countries around the world.  Up to 40% of fishing catch in certain parts of the world is unlawful or unregulated, resulting in approximately $10B to $20B in economic losses and significantly depleting international food stocks. 

Using geospatial position information, data scientists at Analyze provided a reliable method for characterizing fishing behaviors among ships on the high seas.  These methods have the potential to significantly improve interdiction of illegal fishing on the high seas.

Using data transmitted from the Automated Identification System, Analyze studied nearly 500,000,000 data points for 110,000 vessels.   They analyzed time-codes, vessel identity and motion data including:  navigational status, rate of turn, speed over ground, lat/long, true heading, true bearing and more.  The hypothesis was that unique motion behaviors could be associated with fishing activity using motion analytics.  For example circular and duplicative motions could indicate fishing behavior. 

Analyze research consisted in identifying and characterizing this unique motion behavior.  To accomplish this, we employed a basic “big data” analytics strategy consisting of data acquisition, data extraction, transformation and loading, data analysis using statistical and machine leaning approaches, predictive analytics and visualization.

Once the data set was identified for a specific geo-fenced area in the, Analyze utilized a number of analytics from the Mercury Motion Analytics Module that would aid in the discovery of motion behaviors including position information, boundaries & geocoding, distance, velocity, acceleration, motion primitives, shape conformance and consistency of motion.  Measures were derived from this data. 

We noticed that frequent and significant changes in the vessel's compass heading (erratic heading) and erratic changes in velocity were strong predictors of fishing activity.  The vessels themselves use a navigational status of 7 to self-report fishing activity but this was under and over reported throughout the data set.  Analyze was able to derive a fishing prediction function using candidate analytics to positively identify fishing behavior on the open seas.

Data Scientists working on this analysis would be willing to discuss the process and methods used in this analysis.   If you happen to be attending Strata 2014 in Santa Claravisit Analyze in booth 928 in the Innovators Pavilion.

What is Data Science?

Data Science describes the processes, techniques, and tools used to extract deeper, non-obvious meaning from data of all kinds. Whether an organization is attempting to understand it's customers, operations, competition, or market, data science draws from best practices in computer science and statistics to find more meaning in the world.

While most organizations already make basic observations about their data by tracking sales, operations, productivity, and customer satisfaction; these organizations don't realize how much data science can improve decision making.

For example, several years ago I was asked to analyze a company attempting to address staffing problems. After gathering data, I was impressed with this organization's breadth of understanding of their sales cycle and staffing--the sales department knew exactly who their customers were, how frequently they purchased, and when they purchased and it knew how many hours it paid employees and for which projects it paid them. With data fusion and trend analysis techniques, this data produced much more depth such as trigger events in the sales cycle that could be used to plan staffing and supply chain events. 

You can read many more examples of how data science produces deeper insights into data on our Case Studies page. 

What is Big Data?

Big data is code for difficult data. More precisely, it is any data set where traditional techniques (databases and software) are inadequate -- whether trying to to store, query, manipulate, analyze, or otherwise use the data. 

Because (by definition) Big Data is difficult, an industry is springing up, with various database, software products and analytical techniques to address the most common problems with traditional techniques. These are often described using the three (3) V's: Volume, Variety, and Velocity. Essentially, data sets that become too big, contain incongruous data types (such as video files, images, documents, and text and numerical values) and require real time storage (such as click behavior online or sensor outputs from satellites, cell phones, and vehicles). 

The Big Data industry as a whole, in an effort to solve the 3Vs is still evolving as to how it will provide additional, non-obvious meaning difficult data giving rise to Data Science and Big Data Analytics.


New Cybersecurity Training Video - SCADA Vulnerabilities

In response to the requests we've received, we've created a simple video demonstration of our virtual Cybersecurity Training curriculum. You can read a sample list of our training curriculum here. Having developed more than 400 hours of the most advanced training curriculum and interactive cyber exercises for customers such as the Department of State and Department of Defense, Analyze's instructors offer both a mentored approach to teaching advanced cyber to practitioners as well as specific cyber demonstrations to offer management and executives looking to stay abreast of cyber threats.

If you would like to email this video or include it on your website, you can view it on youtube or download it here.

Analyze Hosts First IUU Fishing Roundtable

IUU Roundtable 1

On June 19, Analyze hosted the first Illegal, Unregulated, and Unreported (IUU) Fishing Roundtable. With attendees from the United States, United Kingdom, and Israel, the Roundtable brought together the most influential players in the campaign against IUU fishing, including the National Oceanographic and Atmospheric Agency, Pew Charitable Trusts, Google, SpaceQuest, Greenline Systems, IHS Fairfplay, Windward Maritime Solutions, OrbComm, and SkyTruth.  Read more about the meeting by downloading Analyze's report.

Click here to download the report

Innovation Tank


Innovation is a way of looking at the world. Analyze takes pride in being innovative outside the bounds of any industry, product, or service. Some of our most innovative ideas come from the shower, the gym, nap time, family time, and anywhere but work.  We are passionate about our ideas, love to share them, and are thrilled to see them come to reality. Whether they make us a $M or $0.99, we love our ideas.


The mobile app for iPhone and Android designed to ensure that your phone never embarrasses you again. Open the app, click NOT HERE, and your phone will go on silence. Whenever you return to that location again, your phone remembers and will ensure you're not interrupted. Important meetings, Movies, Theaters, Parent Teacher Conferences, Church... you choose ONCE and you'll never be interrupted again. Download for Android from the Google Play Store here.