Data mining is a term that has become quite popular within certain industries. In a nutshell, data mining could be likened to finding a needle in a haystack. We live in a world that is full of information, and the biggest challenge is not only getting information, but searching through it to find connections and data that was not previously known.
It has been said that knowledge is power, and this is exactly what data mining is about. It is the acquisition of relevant knowledge that can allow you to make strategic decisions which will allow your business or organization to succeed.
Before you can efficiently use data mining tools, you must have large amounts of information in storage. Most companies already have this information. A simple example of this would be a marketing list. A marketing list is information on a number of potential customers that you can market your products or services to.
The more you know about the customers on your list, the better your chances are of earning a large profit. Many businesses are using automated tools to study the behavior of their customers. Once this information has been obtained, it can be used in a way which will allow the organization to predict the behavior of their clients.
But data mining is not simply limited to businesses that are looking to learn more about the behavior of their customers. It can be used in other areas as well. For example, a basketball coach can use data mining to analyze the behavior of his team versus the behavior of their competitors. It can also be used by banks, organizations, and governments. However, data mining is useless if you don’t have any data to analyze. While most organizations already collect data to some extent, this is not enough if you want to use data mining successfully. The information must be specific and refined.
The information that you use for data mining must be prepared beforehand. To successfully use data mining on the information you have obtained, there are two terms that you will want to become familiar with. These two terms are segmentation and clustering. These two terms will play an important role in marketing and customer interaction. These two terms deal with tracking the purchasing behavior of your customers over a given period of time.
When you use segmentation and clustering, you will be able to split your customers into categories based on the revenue they bring into your organization. You can determine how much revenue they will bring you over time, and you can also determine the chances of retention based on the shopping behaviors of the customer.
Most companies will want to keep customers which are high in value and low in risk. Because of the 80/20 principle, many companies and business are well aware of the fact that a maximum of 20% of their customers will bring in 80% of their profits. The customers that make up this 20 percent are extremely important, and the company cannot afford to lose them.
The goal of the company would be to use retention to keep these customers purchasing their products for a long period of time. When it comes to the other 80 percent, the goal of the company should be to increase the profits that they earn from them. To achieve this, they could either cross-sell or up-sell their products in order to get this segment to purchase more.
One thing that data mining can be used with is demographics. The use of data mining with demographics will allow you to target the type of advertising that you use with certain customers. You will want to use advertising that is directly related to their behavior. A bank is a good example of an organizaation that could combine demographics with data mining in order to be more successful.
The bank could split the customers into high-profit and low-profit, and then they could spend some times studying the behavior of these different groups. While data mining isn’t good at telling you "why" a certain segment behaves in a certain way, it is excellent tool for telling you "how." Base on the information the bank analyzes, the can advertise certain products to one group while advertising different products to another group.
