Entries in cyber monday (1)

Monday
Nov282016

The Data Science Behind Cyber Monday

As you awaken from your Thanksgiving food-coma and return to the work-week grind, don’t forget: today is Cyber Monday!  The holiday-shopping season officially began last week on Black Friday, and today retailers are expected to reign in similar profits.  Forbes magazine predicts that retail sales will exceed $3 billion on both Black Friday and Cyber Monday [1].  

And in the spirit of giving this holiday season, shoppers will be handing over enormous amounts of data to every site they visit.  Behind the scenes at online retailers like Amazon are teams of data scientists tasked with pricing merchandise, targeting advertising, and predicting consumer behavior [2].  Ever notice that when you visit an online retailer and browse for an item without buying it, that item will show up in advertisements on other webpages for the next few days?  That’s a machine-learning algorithm at work, designed by data scientists.  As you browse the web, you leave a trail that can be picked up by advertisers.  So when you compare different cell-phones on Amazon, odds are you’ll start seeing ads for mobile devices in your Facebook newsfeed and in banner-ads while you’re reading the New York Times. With more data, these algorithms “learn” faster, so they actually become more efficient during the holiday-shopping rush [3]. The algorithms consider everything from the items you browsed and the stores you visited to the movement of your mouse and the number of clicks you made on a particular page.  On sites like Amazon, they’ll also consider whether you’re a Prime Member and items you’ve previously purchased.  

Thanks to Big Data and advances in machine learning, advertisers can push their products to targeted demographics like never before.  Still, this type of advertising does have some drawbacks.  The large amounts of data that companies accumulate about their shoppers could come with some security risks.  Moreover, last month Facebook came under-fire for offering the ability for advertisers in housing, employment, and credit, to target by “ethnic affinity” [4].  And in 2012, Target’s algorithms accidently exposed a teen girl’s pregnancy to her father [5].

Despite these drawbacks, advances in machine learning and data science and paving the way for new discoveries in other fields.  Similar algorithms power Siri and the Amazon Echo.  Machine learning and Big Data are revolutionizing the way we understand genetics, disease, and the human brain.  Like any new technology, machine-learning algorithms should be designed with their context in mind and implemented with care.  So as you shop this Cyber Monday, you can start by crossing one gift off your list: the gift of data that you’ll be giving to all of the retailers you visit.
-TM
[1] http://www.forbes.com/sites/shephyken/2016/11/19/2016-black-friday-cyber-monday-holiday-insights-and-predictions/#785131c5243f
[2] https://www.internetretailer.com/commentary/2016/11/12/science-behind-black-friday-and-cyber-monday-pricing
[3] http://everything-pr.com/big-data-black-friday/54064/
[4] http://www.forbes.com/sites/kathleenchaykowski/2016/11/11/facebook-to-ban-ethnic-affinity-targeting-for-housing-employment-credit-related-ads/#2980ba0ca747
[5] http://www.forbes.com/sites/kashmirhill/2012/02/16/how-target-figured-out-a-teen-girl-was-pregnant-before-her-father-did/