Patrick Schwerdtfeger is a motivational speaker who can speak about predictive analytics and provide ‘Big Data’ case studies at your next business event. Contact us to check availability. The full transcript of the above video is included below.
 

 

Full Video Transcript:

 
Hi, and welcome to another edition of Strategic Business Insights. Today we’re going to give some examples of big data analytics. Big data is just an exploding topic today, and basically people are looking at enormous quantities of data and they’re doing analytics on the data – in other words, to find out what happened, and then they’re trying to find attribution – in other words, why did it happen?

Another way you could look at this is to look for correlations and then find causation – same thing. What happened? Where’s the correlation? Causation – why did it happen? Did A lead to B or did B lead to A? Or were both of these influenced by C, which created them both? Attribution or causation as it turns out is one of the most challenging parts of big data and predictive analytics.

But once you have those two pieces—what happened and why did it happen—you can create algorithms, which actually calculate this stuff on an ongoing basis and spit out insights that you can take action on as a business or what have you. So you can think about it as the three A’s: Analytics, attribution, and algorithms. That’s basically what they’re trying to do with big data.

So let’s get some examples. This happened a few years ago – an angry father stormed into Target in Minneapolis, a Target store, and started screaming at the store manager because his daughter, 17-year-old teenage daughter, started receiving coupons for like maternity clothes and cribs and things. He was livid. He’s like, “Are you kidding? Are you trying to encourage my daughter to get pregnant? She’s 17!”

And of course the store manager apologized profusely and made sure she was taken off of the list. And four days later that store manager called again just to say, “Look, I’m really sorry. I just wanted to make sure everything’s okay.” On that phone call the father said, “You know, I actually owe you an apology, because it turns out there are some things that have been happening in my house that I was unaware of and my daughter’s due in August.” So it turns out the daughter’s due.

Target knew she was pregnant before her father knew she was pregnant. How did they know? Because she bought prenatal vitamins and scent-free soap. Prenatal vitamins and scent-free soap – turns out that if you buy those two things there’s a very, very high probability that you’re in your second trimester of pregnancy, and Target does this to try and get coupons in front of these women before they have their baby because when you have a baby it’s one of the times when your shopping habits change very, very quickly. All of a sudden you go to new shops, new retail stores. So it’s an opportunity for retailers.

This is big data. You look around, Netflix knows what movies you will like before your friends know what movies you will like. Pandora knows what music you will like before you know what music you will like. Google can tell where there’s a flu outbreak because they see that people are searching for flu-related keyword phrases. They can see it by neighborhood to neighborhood because they know the IP addresses of people who are doing this kind of searching. So the CDC, the Center for Disease Control, they also monitor flu outbreaks, but Google knows when there’s a flu outbreak two weeks before the CDC knows because they can look at the data. The answers are in the data.

There was a guy who used a freedom of information request to ask for all the information that Facebook had about him, just through this regular profile. He was active on Facebook but wasn’t anything extraordinary. They sent him a thousand pages of data that they had accumulated on his activity on Facebook. Unbelievable. This is data.

There’s a company in India, a cell phone provider in India that realized that their payment history with all their customers could be used as a credit score, effectively a credit score, because they don’t have credit rating agencies in India like Transunion and Equifax and Experian. So this cell phone company that had like hundreds of millions of customers, the payment history could act as a credit score, which means the banks could use their payment history as a surrogate credit score to determine who was worthy of loans and who was not.

There are police departments across this country—United States—that have a camera that’s attached to their dashboard and it’s just like facial recognition but they’re not looking for faces, they’re looking for license plates, and they camera just all day long. The officer driving the car doesn’t even know what’s going on, but that camera is constantly looking around, taking pictures of these license plates, and every picture it takes it attaches the date, the time and the location of where that picture was taken. There are some police departments that have 700 million photos of license plates in that community, virtually guaranteeing that any car in that city has been photographed at least a dozen times. They sell this data to private investigators and insurance companies. Unbelievable examples of big data.

In fact, there’s even such a thing called predictive policing. It turns out that just like when you have an earthquake you have aftershocks, much the same way, when there’s a crime there are aftershocks. In other words, other crimes happen in the same area. Why? Because someone who’s just committed a crime, what do they do? They immediately go to where their friends are and they’re like, “Hey, check this out. I just robbed a store,” and they basically show off. And so now their friends are like, “Man, I want to do that too,” and there’s some inherent pressure, there’s some competition between them, and all of a sudden other people start committing crimes.

There’s a television commercial, an IBM television commercial where they show, basically they depict this scenario where a police officer ends up at a store just when a guy shows up to try and rob it. It’s called predictive policing. This is a reality today. People are using data to anticipate crimes before they happen.

Weather models is another example of big data. There are satellites going around the earth that are measuring high-pressure zones and low-pressure zones. They have sophisticated algorithms to do determine when those zones are moving and what the weather patterns are going to look like.

Walmart looked at their data to determine…it was correlation analysis based on weather patterns, and in particular hurricanes, because when a hurricane comes you’ve got six or seven days’ notice, so you know it’s coming. So the question is, what products sell more when a hurricane’s coming? And all the usual suspects were among the list, but one of the ones that they didn’t expect and it was consistent – strawberry pop tarts. Strawberry pop tarts! Who would have thought? But it turns out that strawberry pop tarts consistently go up in sales when a hurricane’s coming.

And you might immediately think, “Why is that?” Who cares why it is? The bottom line is it happens, and so now Walmart can cater to that demand knowing it’s coming. Bottom line is the answers are in the data.

One last example is when you go to a grocery store and you buy wine. Grocery stores typically have wines in the 10-dollar range, 25-dollar range, and 45-dollar range. Well, the truth is that nobody buys the 45-dollar bottles, but just having them on the shelf increases the sales of the 25-dollar bottles because people always want to buy the center solution, the center option, the middle option. If the grocery stores just had 10, 15, and 25, most people would be like, “Oh, I don’t need the top of the line. I’ll get the 15-dollar bottle.” So by having 45-dollar bottles, people say, “Oh, I don’t need the 45, I’ll buy the 25,” which is a higher sales price than what they would have bought if the 45-dollar bottles weren’t there.

This is human behavior. The data is starting to provide insights on human behavior, and so our world is becoming more intuitive. And rather than trying to understand the psychology behind it, just value the fact that this data is finally being analyzed because up until now businesses made their decisions for the most part based on hunches and theories. Now, today, businesses are making decisions based on the data, and as a result our world is becoming more intuitive and smoother. So I’m a big supporter of big data analytics and I can’t wait to see some of the changes it has for our world as we move forward. And if you’re in business, then you should start looking at your data as well from a very strategic perspective and start asking yourself what insights can you pull from that data which will make your business thrive in the future.

My name’s Patrick, thanking you very much for watching my video, and reminding you as always to think bigger about your business, think bigger about your life.
 


 
Patrick Schwerdtfeger is a keynote speaker who has spoken at business conferences in North America, South America, Europe, Africa, the Middle East and Asia.