Data Analytics-Target
Data analysis is of high importance to any businesses. They are always spending money and effort on advertising campaigns, product development, marketing strategies and so on. They must have some sort of check to see to what extent this will pay off. It is important to understand the mindset of people, market trend, seasonal trend and so on especially in the retail industry in order to survive. New technologies at first are met with a degree of skepticism in the form of “What can I do with this?” According to McKinsey late last year, “these are still early days for big data, which is evolving as a business concept in tandem with the [evolution of] underlying technologies.” While big data itself is not new technology, it use can be thought of similarly to the Technology Acceptance Model, in which the first step of adoption is Perceived Usefulness. Data Analytics has been around for many years and will continue to grow in the years to come. My dad who incidentally works for Target Corporation tells me that they are always on the lookout for people with knowledge of Data Mining and visualization tools. A successful implementation of these techniques can help a business pin point its areas of low performance, predict their growth in sectors and most importantly present results in a clear cut visual format. I have read a very interesting article on how Target implemented Data Analytics for their marketing campaign. The methods were questioned later and they did get into trouble for this but this goes to show how data analytics can sometimes accurately predict to a certain level. This implementation used some level of frequent item sets which we did discussed in class and once again this was implemented to a ‘grocery’ store scenario. After a certain amount of research it was found that a woman changes her shopping needs at two points in her life. One point being the time she gets married and the second is when she has a baby. Every time you go shopping, you share intimate details about your consumption patterns with retailers. And many of those retailers are studying those details to figure out what you like, what you need, and which coupons are most likely to make you happy. Target, for example, has figured out how to data-mine its way into, to figure out whether you have a baby on the way long before you need to start buying diapers. They ran test after test, analyzing the data, and before long some useful patterns emerged. For example lotions turned out a as a hit point. Lots of people buy lotion, but they noticed that women on the baby registry were buying larger quantities of unscented lotion around the beginning of their second trimester. Another analyst noted that sometime in the first 20 weeks, pregnant women loaded up on supplements like calcium, magnesium and zinc. Many shoppers purchase soap and cotton balls, but when someone suddenly starts buying lots of scent-free soap and extra-big bags of cotton balls, in addition to hand sanitizers and washcloths, it signals they could be getting close to their delivery date. As their computers crawled through the data, they were able to identify about 25 products that, when analyzed together, allowed them to assign each shopper a “pregnancy prediction” score. More important, they could also estimate her due date to within a small window, so Target could send coupons timed to very specific stages of her pregnancy.
Well, turns our scary but this study was generating actual results. Everything was going well until the following example.
An angry man went into a Target outside of Minneapolis, demanding to talk to a manager:
My daughter got this in the mail!” he said. “She’s still in high school, and you’re sending her coupons for baby clothes and cribs? Are you trying to encourage her to get pregnant?”
The manager didn’t have any idea what the man was talking about. He looked at the mailer. Sure enough, it was addressed to the man’s daughter and contained advertisements for maternity clothing, nursery furniture and pictures of smiling infants. The manager apologized and then called a few days later to apologize again.
On the phone, though, the father was somewhat abashed. “I had a talk with my daughter,” he said. “It turns out there’s been some activities in my house I haven’t been completely aware of. She’s due in August. I owe you an apology.”
What Target discovered fairly quickly is that it creeped people out that the company knew about their pregnancies in advance. They had to change their ways around this particular analysis. It goes to show that data analytics can be very true and can pin point certain parameters and maybe key in aiding to the growth of your business.
References: How Companies Learn Your Secrets-NYTimes.com.
Prashant,
ReplyDeleteI read this when it happened and I thought that this brings some interesting discussions to big data and privacy. I would like you to know your opinion about this topic.
Fadel
I have a biased view on this topic as I mentioned, my dad works closely with Target Data Analytics and uses the data to develop and troubleshoot new features on the dot com portal of Target. I find that it is a violation of privacy to an extent, but in today's world where there is a vast sharing of information. People willingly share information about their interests, events in their life on social web portals, instagram, blogging sites. Companies can use this to their advantage from a business growth model perspective and use to for Data Analytics. What happened in this article is a story which came to the surface, but there are various other techniques such as the one mentioned above which many companies use to keep track of their customers. To a large part what Target used for their analytics did work and they were successful in predicting 'changes' in consumer requirements which was the purpose of their study. As long as there is a a non-disclosure agreement on their part I think it is fair for companies to 'invade' our privacy to develop their business. At the end of the day they can effectively use it only for advertising or marketing purpose. It is on our part to finally agree to do business with them:)
ReplyDeletePrashant
I found a mention of this incident in another article.
ReplyDeletehttp://www.npr.org/2013/03/07/173176488/the-big-data-revolution-how-number-crunchers-can-predict-our-lives
This article gives other examples of how companies are using big data in order to increase profits. The examples listed were
1. Netflix tracking what movies and shows viewers watch. They used this data to decide on their first original series, House of Cards.
2. Google tracks the flu by storing all of its searches and identified likely predictors. They also reported their findings in real time.
Also with the examples, the article discussed different things about big data in general.
• Big data doesn’t take cause into account, just correlation. The example used was that a study found that orange cares break down less than other cars. Does this mean that the paint color of a car has anything to do with its breakdown rates? Probably not, but you don’t see a lot of orange cars driving around (at least not in Auburn, Alabama) because it’s usually a custom color. If a person decided to have a custom color car, then they might have customized other aspects of the car as well. So that could be why orange cars breakdown less than other color cars, not because they’re painted orange.
• Big data crosses the line. One supporting argument used is predicting things before they happen and then responding to them. The example was if a police station identified a person of having certain traits that leads them to believing they would commit a crime. Well, it’s not fair to punish someone for a crime they didn’t commit yet but may in the future.
o This may be a justified example but does that mean that big data is crossing the line? Using big data to predict when crimes are going to occur and where could greatly benefit the standard of living in some areas. (I mentioned this issue in a post recently as well http://auburnbigdata.blogspot.com/2013/03/big-data-can-save-lives-save-money-and.html ). I feel personally that this doesn’t mean that big data is the problem, but the people using it. I just thought this was a really interesting point and I wanted to share it and give some context as well!
Katy
Good explain about data analytics.
ReplyDeleteBig Data Analytics Services
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