Tracking Your Movements

Traveling is one of my favorite things to do, so I explored how data mining might affect this activity. I was interested to find out the travel industry is using data mining as much as any other.  While any service provider uses data mining to create higher profits they are also using it to better serve customers.

By tracking behavior patterns of all clients and by individual IP addresses or customer IDs, service can be in a way, customized.  The travel industry focuses on predictive analysis for future trips.  The analysis can be created by the manipulation of the massive amounts of data collected.  The predictions of what customers want allows them to cater to that and increase sales and therefore profits.

Patterns found in analysis of travel data can allow companies to identify groups of similar customers.  Groups could be those that who travel only based on price or others that are set on specific destinations.  This type of information along with your unique preferences like only flying first class and only staying at boutique hotels will help build the recommendations that online travel booking sites like Expedia use.

Just as our group explained in our presentation grocery store reward cards and frequent flyer numbers help to track customers and create these profiles.  The nature of the traveling industry means that its customers are often moving, and regardless of which branch of a hotel they are staying in data mining creates the ability to track the preferences of their customers.  The ability to cater to a customers wants creates a happy customer who will visit this establishment again.

As we have asked before are we willing to share all of this information? Do we know that others have it?  What is more important privacy or convenience?


 Source and further reading:
http://www.executivetravelmagazine.com/articles/how-data-mining-impacts-your-travel

Insurance DENIED

http://patients.about.com/od/yourmedicalrecords/a/Supermarket-Or-Pharmacy-Loyalty-Rewards-Card-Can-Affect-Your-Health-And-Care.htm

In summary, this article talks about “reward” cards. We save money using these reward cards at the time of purchase. The different stores that offer these receive money because they can sell all the data collected when swiping the card. Different companies for different reasons would buy this information. An example in the article is about a car dealer maybe wanting this information because if you buy expensive meats and wine, you might be more inclined to buy a more expensive car. Another example in that stuck me is that insurance companies will buy this information. They might buy the information to track what you eat, and if you buy a lot of fatty foods or beer they might determine you as a high risk client and charge you a higher premium compared to someone else; or deny you insurance period. With the beer example, I don’t think one purchase will hurt you, it was mentioned in the article if you buy it six times a week it could become a problem.

I’m not exactly sure how I feel about this? I have mixed feelings either way I go. What do you guys think?

Big Data On Campus

With 72,000 students, A.S.U. is both the country’s largest public university and a hotbed of data-driven experiments. One core effort is a degree-monitoring system that keeps tabs on how students are doing in their majors. Stray off-course and a student may have to switch fields, so this system suggests alternatives courses match with your interest and field.

If they fail to sign up for a key course or do well enough, the computer cracks a whip, marking them “off-track.” Wander off-track two semesters in a row, and a student may have to change majors.

If that sounds harsh, there’s a rationale: One way to ensure that students will reach the finish line is to quickly figure out if they’ve selected a suitable track. So the A.S.U. system front-loads key courses. For example, to succeed in psychology, a student must perform well in statistics.

At Arizona State, algorithms figure in course content, too. Thousands of A.S.U. students now take math courses through a system that mines performance and behavioral data, building a profile on each user and delivering recommendations about what learning activity they should do next. The system, created by the start-up company Knewton, has given the university a fresh way of addressing the continuous problem of students being unprepared for college math. But it also offers a glimpse into what many more students will experience as teaching increasingly shifts from textbooks and lectures that feed the same structure of information to a class of 300, regardless of individual expertise, to machines that study their users’ learning patterns and adapt to them.

So do you think all these countless hours of online Homework really worth it?

At Rio Salado, a community college with about 70,000 students, 43,000 of them online, Mr. Lange got excited about the behavioral data students leave behind: the vast wake of clicks captured by software that runs Web courses. Records of when they logged in opened a syllabus, turned in homework.

Could you mine it to model patterns of students who succeeded in the past? Use that to identify current ones likely to fail? And then help those students? Many educators are now asking similar questions.

“Mr. Lange and his colleagues had found that by the eighth day of class they could predict, with 70 percent accuracy, whether a student would score a “C” or better. Mr. Lange built a system, rolled out in 2009, that sent professors frequently updated alerts about how well each student was predicted to do, based on their course performance and online behavior.”

Research shows that social ties can influence academic success. If students are more integrated into campus life, they’re more likely to stay in school. If a friend drops out, they’re more likely to as well.

Do you believe in these theories of social ties or the ability to predict a students grades for the future?

-Parry, Marc. "Please Be EAdvised." The New York Times. The New York Times, 22 July 2012. Web. 03 Apr. 2013.

Data Mining Equals Competitive Advantage

When I hear the words Data Mining, I think of the invasion of individual privacy.  But let’s say that you run a business, we’ll use a Coffee Shop, would you use Data Mining to help your business increase in profits as well?  Your competitors like Starbucks and Dunkin’ Donuts are already doing it.  Data Mining, if used correctly can be a pot of gold for your company’s success and here are a few ways that you can use the information that you collected to your advantage.  Data mining helps you forecast sales, market, plan, and identify market segment. 

When you forecast sales, you’re using past sales to predict when your customer will buy again!  You might ask how many people, households, businesses will buy your coffee?  How many competitors are in a mile?  How many people, households, businesses are in 5 miles as well as how many competitors are in that 5 mile?

Marketing:  By examining customer purchasing patterns and looking at the demographics and psychographics of customers to build profiles, you can create products that will sell themselves.  With that being said, you can now begin to send weekly emails about your company’s promotions/discounts, or new incentive awards/bonus programs.  (Example, for every $3 purchase you make, you’ll receive 1 point to your card.  10pts=1 free coffee)

Planning:  Data mining will help you identify which products are selling the most, how much inventory you will need to have, and how you should price your items as you uncover customer sensitivity.

One of the best uses of data mining is to segment your customers. And it’s pretty simple. From your data you can break down your market into meaningful segments like age, income, occupation or gender. Segmentation can also help you understand your competition. This insight alone will help you identify that the usual suspects are not the only ones targeting the same customer money as you are.

In conclusion, if I were a business, I would use Data Mining to my advantage as well.  Powerhouse companies like Wal-Mart, Amazon, Microsoft, Starbucks and much more survive not by sitting on these data but to put them to use.  As I continue to understand the usage of data mining this semester, this is a technique that companies use to get ahead of their competitors.  Companies may know my purchasing history, street address, phone number, email, and credit card information but so far, my account balance still remain the same and my credit is still good, so it’s safe to say that companies who invaded my privacy are keeping me safe from thieves.

Source: http://blog.kissmetrics.com/data-mining/