Amazon - Using Data to Succeed

Ever wonder how Amazon became one of the top e-commerce sites? Data is what has helped set Amazon above their competitors. So, what data exactly are we talking about? How has this data helped Amazon to be the successful company that is today? Truth is, data is really how the company was formed.

There are several ways in which Amazon uses data:

1.     PRODUCT SUGGESTIONS

Amazon collects data every time a consumer makes a purchase. The customer’s contact information and address are submitted upon checkout, and the products that the consumer buys are also documented. Ever wonder how the company seems to know you so well in the suggested items? This is because Amazon has data on your account and the products you have purchased.

2.     TO DETERMINE PRICING

Additionally, Amazon uses data to determine their pricing. Products are compared to other store pricing, and Amazon will define the price that is within the same price range as its competitors, if not, cheaper.

3.     CUSTOMER FEEDBACK

Like most companies, Amazon uses customer reviews to understand their weaknesses, and improve on the feedback they received.

4.     MEDIA CHANNEL

As an Amazon Prime member, you can receive media streaming services to watch television shows and movies. Amazon collects data on the different shows you watch, and provides suggestions based on viewers who watch similar shows.  

Amazon wouldn’t really exist without data. Data has really shaped the company to become what it is today. Amazon has utilized this data to create new concepts in the company, and also improve their business as they evolve. 


Source: https://datafloq.com/read/amazon-leveraging-big-data/517

Moneyball - Learning About Analytics in Sports

Have you seen the movie "Moneyball", featuring Brad Pitt, and Jonah Hill? You have? Great. If you haven’t then you’re missing a great film that teaches you how analytics is used in the all American sport, baseball.

"Moneyball" is a film that tells the story of how Paul DePodesta uses analytics to find undervalued baseball players and creates a winning team from a small budget. Other teams with larger budgets had looked right past these players because they didn’t realize how valuable these players were, and only focused on the top players that the entire league was raving about. Without DePodesta, the Oakland A’s wouldn’t have identified these players either. DePodesta was really the first person recognized in the industry to use data to analyze players’ performance and scout who he believed (according to the players’ data) to be the next best players to add to his team. Now all sports are using data to create their roster, not just baseball.    

When you have free time, I highly suggest that you watch “Moneyball”. As I said, the movie wasn’t just talented actors, and a well-produced film; you will actually learn how data is used in sports to construct a team of talented players.

Regression Analysis to Determine Placement of Products in a Store

With regression analysis you can determine the relationship between two variables. SAS enterprise miner is a great tool to use for this. You can look at different variables and determine the expected confidence that someone buying one item would buy another item. This can be useful in establishing a store layout.

You could go about a store layout in two different ways:

1.     Put items that are likely bought together in the same aisle.

2.     Put items that are likely bought with another item spread throughout the store so that customers will actually walk throughout the entire store.

Ever wonder why fruit and vegetables are on the opposite end of a supermarket as dairy? This is because fruit, vegetables, and dairy are all common items that consumers buy when they make their weekly trip to the supermarket. Having these items on opposite end will drive someone to walk through the entire store, hopefully picking up other items along the way. It wasn’t just a coincidence. There was a strategy behind these grocery store layouts. It’s amazing what you can do with data. I bet you didn’t even realize that data could be used to shape a store layout!