Amazon A-to-Z

Amazon.com, Inc. (Amazon) is an American online ecommerce company headquartered in Seattle, Washington. While Amazon started strictly as an online bookseller, it has since branched out to offer DVDs, CDs, downloadable content, software, video games, clothing, home electronics, food, toys, and innumerable other sundries. Additionally, Amazon produces its own e-reader (the Kindle) as well as compatible e-books. Lastly, Amazon has launched its AWS web services to provide enterprise hosting of cloud computing services. Amazon is certainly a company that offers everything from A-to-Z.

For the better part of its existence, Amazon could not even finish a year posting a profit. “Amazon has a tendency to polarize people. On one hand, there is the ruthless, relentless, ferociously efficient company that’s building the Sears Roebuck of the 21st Century. But on the other, there is the fact that almost 20 years after it was launched, it has yet to report a meaningful profit.” (Horowitz, 2014).

 

In 2013, however, “Net sales increased 22% to $74.45 billion, compared with $61.09 billion in 2012. Excluding the $1.28 billion unfavorable impact from year-over-year changes in foreign exchange rates throughout the year, net sales grew 24% compared with 2012.” (Amazon, 2014).  This increase in profits is not based on pure happenstance or lightning in a bottle. Every decision and every strategy plotted out of Amazon headquarters is based heavily on big data. Since its founding, very few companies outside of Google have kept as much analytical data as Amazon. The company’s use of analytics has lead to intelligent and responsible growth during a down economy, making Amazon one of the most powerful and influential companies in the world.

A-to-Z Data Collection

When it comes to collecting data, Amazon collects nearly everything imaginable. From the moment a consumer arrives on the website to the moment they exit, Amazon collects every single action a user makes. David A. Steinberg, digital marketing expert and founder of Zeta Interactive, states that Amazon collect and analyzes even the most granular level of data. “[The company] looks at everything consumers do transactionally, and also looks at what shoppers have looked at. Amazon then folds this info into its algorithm and whenever you buy something, it'll tell you that 'people who bought this also bought x, y, and z.' ” (Carlozo, 2013).

Amazon use of an item-to-item collaborative filtering algorithm is based on behavioral data and creates product recommendations to not only help consumers, but to increase sales. The behavioral recommendation algorithm has certainly been a successful use of analytics for Amazon and Fortune.com credits much of Amazon’s recent growth to this item-to-item collaborative filtering algorithm.

But not to sit on their laurels after finding one successful technique, Amazon is always plotting its next big move. One such move was the implementation of the “One Click Buy” feature for which the company received a patent. (ESpacenet, n.d.). This idea was fantastic, but the genius part was being able to get a patent for something seemingly so simple. As Bernard Marr states, Amazon has combined their, “strengths in data analytics and it’s instinct for patenting key features to obtain a patent for what it calls: Anticipatory Shipping.”  (Marr, 2014). Which leads us to the next big thing for Amazon.

The Next Big Thing 

Amazon continues to push ahead of the analytics game with its forward thinking. Today the company is embarking in its most ambitions strategy yet. Amazon’s latest patent is the process of shipping an item to a customer in anticipation that this customer will order that product. Essentially, Amazon trusts its big data insights to accurately predict what a consumer will order next, and when. Marr states that the primary reason for this patent is that Amazon wants to deliver products faster. This is also why it Amazon now offers Sunday deliveries and is toying with the idea of utilizing unmanned drones for future deliveries. (Marr, 2014).

While traditional retailers often use predictive analytics to guarantee that items are in stock, Amazon is taking the concept to a new level. They are using their algorithm to predict the items a specific individual may purchase, as opposed to using the formula to stock the items that larger populations may wish to buy.

H. Donald Ratliff, Ph.D., executive director of the Supply Chain and Logistics Institute wrote that, “Supply chain and logistics optimization is neither easy nor cheap, but it is the biggest opportunity for most companies to significantly reduce their cost and improve their performance. For most…operations, there is an opportunity to reduce cost by 10% to 40% by making better decisions.” (Ulanoff, 2014).  For a company the size of Amazon, a 10% to 40% in annual savings is no small amount of change.

So how exactly does all of this work? According to the patent, this predictive model uses data from a consumer’s prior Amazon activities such as time on the site, duration of product views, what links were clicked, shopping cart activity, and what items were added to a consumer’s wish list. If available, the predictive algorithm will also include data from real-world information collected from customer telephone inquiries, responses to marketing messaging, as well as other external factors. (Ulanoff, 2014).  To help clarify the process, Amazon included a simplified flowchart in its patent detailing the predictive shipping process might work.

Additional Tools and Strategies

While Amazon is certainly forward thinking, because it offers such a diverse product line there will always be room for improvements and innovation. One such business property that could use a little TLC is the company’s online video streaming service. The Amazon Instant Video product is an Internet video-on-demand service similar to Netflix or Hulu. . The service offers television series and films for rent or purchase. The service is free to customers with an Amazon Prime subscription and a la carte for everyone else.

    While Netflix is the undisputed king of online pay-per-content video streaming, Amazon Instant Video may be just as appealing to some. But for whatever reason, the service goes highly under publicized and remains relatively unknown.  Like Amazon, Netflix thrives on the use of its recommendations system. And like Netflix, Amazon Instant Video uses the consumer’s past viewing history and saved favorites to generate suggestions based on that person’s taste. The two products are similarly priced with Netflix coming in at about $96 annually and Amazon Instant Video coming in at $99 annually. But with Amazon’s service, you also get its free prime shipping service. So by watching the movies you were already planning to watch on Netflix, you will also get Amazon’s free shipping service to boot. This really makes the Amazon Instant Video service a great deal and a viable competitor to Netflix.

    As far as analytics goes, I think Amazon should start suggesting videos to purchase or rent based upon what books and DVDs Amazon shoppers are looking at or buying. By utilizing the same data the company is already collecting, Amazon could begin promoting this terrific, but under utilized service to a new wave of consumers.

 

Conclusion

Tracking big data one the web has become essential element in developing online marketing and business strategies. No company better exemplifies this than Amazon. Every element of the ecommerce giant’s website is carefully planned and implemented based upon analytical data. The data that Amazon collects not only helps the company to better identify what consumers what, but also what they may want in the future. Through important patents and concepts, Amazon is not only forecasting what consumers will want to purchase, but also the company’s future as an innovator and industry leader.

References

Amazon. (2014, January 30). Amazon.com Announces Fourth Quarter Sales up 20% to $25.59 Billion. Retrieved December 7, 2014, from http://www.marketwatch.com/story/amazoncom-announces-fourth-quarter-sales-up-20-to-2559-billion-2014-01-30.

Carlozo, L. (2013, December 23).  How Online Retailers Collect & Use Consumer Data. Retrieved December 7, 2014, from http://dealnews.com/features/How-Online-Retailers-Collect-Use-Consumer-Data-/938928.html  

ESpacenet. (n.d.) Method and System for Placing a Purchase Order via a Communications Network. Retrieved December 7, 2014, from http://worldwide.espacenet.com/publicationDetails/biblio?CC=US&NR=5960411&KC=&FT=E&locale=en_EP.

Horowitz, B. (2014, September 5).  Why Amazon Has No Profits (And Why It Works). Retrieved December 7, 2014, from http://ben-evans.com/benedictevans/2014/9/4/why-amazon-has-no-profits-and-why-it-works/.

Marr, B. (2014, February 5).  Amazon: Using Big Data Analytics to Read Your Mind. Retrieved December 7, 2014, from http://smartdatacollective.com/bernardmarr/182796/amazon-using-big-data-analytics-read-your-mind/.

Ulanoff, L. (2014, January 27). Amazon Knows What You Want Before You Buy It. Retrieved December 7, 2014, from http://www.predictiveanalyticsworld.com/patimes/amazon-knows-what-you-want-before-you-buy-it/.