Amazon has been using big data and turning it into an integral part of their business model. They’ve acquired data-mining firm Datageist to help them with this endeavor. What is Amazon doing with all of this big data? And how should organizations that are not involved in the Amazon ecosystem approach this differently?
Amazon uses various sources to analyze consumer habits. For example, the company has tracked millions of e-mail addresses and broken down what parts of an address seem to correlated with what kind of products a consumer typically buys. That lets the retail giant avoid sending junk mail or impulse buying to a person’s home. This approach has proved very effective for them. It is used by other aspects of their business as well, including their retail stores and fulfillment centers.
Amazon has also used data to determine where to location in their brick-and-mortar locations. The result has been to make their in-store locations more user-friendly, to increase sales and in turn generate more profit. In some ways, they have leveraged leveraging the power of location-based data to serve the needs of their customers better. As they have done with so much of this kind of activity, they’re likely to continue to do so moving forward.
The question then becomes, how does Amazon use big data to improve their operation? It’s too early to draw any firm conclusions, but we can get a feel of some of the approaches that they are taking. One interesting area of focus includes the implementation of a customer loyalty program. What kind of benefits could such a program deliver? In my view, a company should look into whether or not such a program improves the bottom line by improving customer relations and retention.
Of course, how does Amazon use big data to implement a customer loyalty program by using it to analyze customer behavior is only part of the equation. Such an approach may be good from a strategic standpoint, but it can also be good from a financial standpoint as well. Consider the fact that most shoppers are impulse buyers. Their buying impulses are governed mostly by the factors of supply and demand. They want that product or service when they see it, but they are sometimes unable to fulfill their need at that moment for whatever reason.
Such a situation calls for a data solution that can capture and predict shopper’s behavior so that they are able to plan their shopping trips ahead of time. This data can help retailers determine when they should offer incentives, or when they should raise prices. In both cases, such information can prove to be extremely valuable to the merchant.
At the same time, there are concerns about how does Amazon use big data to drive its business forward. The concern about the security of Amazon’s data centers is one that we hear often. Amazon uses the colocation facility at a facility in North America, and it has claimed that the facilities have rigorous security measures in place to protect customer data. While such precautions would be standard in any data center environment, it is always good to know that Amazon takes this issue very seriously. After all, the security of customer data is probably the single most important thing an e-commerce company could possibly decide to invest in.
Concerns about big data have become more than just hype. While the term is new, the potential applications for such a technology are quickly becoming apparent. Whether or not Amazon plans to use this technology to serve as a competitive advantage remains to be seen. In the meantime, such a move could only be good for its customers.