Often a data mining is likened to finding a needle in a haystack. It is very true, because we are living in the world full of information. The challenge is to search through the heap of information and unearth the connections between data which was previously unknown. Acquisition of such relevent knowledge will allow for an organization to succed in a long run.

Let us have a look at some of the practical situations that the companies face today.

Data mining for effective marketing

Most of the companies have a list of their customers and a marketing list. A marketing list is information on a number of potential customers that you can market your products or services to. he 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.

The use of data mining is definitely not limited to businesses that are looking to learn more about the behavior of their customers. It can be used in other areas like Banking, government, sports etc. However for the sake of example lets digg more in the area of marketing.

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.

What will data mining tell you?

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." This can be effectively used for the growth of an organization. For example, 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. Based on the information the bank analyzes, they can advertise certain products to one group while advertising different products to another group.