In order for your business to grow, you will naturally want to gain more customers. You can gain new customers by advertising to people who do not know about your product, or you can acquire customers who are currently buying from your competitors.
Data mining is a tool that can not only help you learn more about your existing customers, but it can also help you acquire new customers as well. Before you can understand how this can be done, it is first important to look at traditional customer acquisition strategies.
In the past, most companies acquired new customers by using direct mail, telemarketing, or mass advertisements. These projects would generally be headed by a marketing manager. The product would typically be placed in magazines which were related to it. The goal of putting ads in mainstream publications was to reach a larger segment of the population. Direct marketing has traditionally been connected to mass marketing. The marketing director would find a demographic that they wanted to target, and then they will contact a list broker who can provide them with a list of people that fell under the demographic.
Once the list broker has found a list that matches the specifications of the marketing director, the director would pay for it, and they will have the necessary information needed to market their products or services to people that are targeted. However, the customers on the list would have a number of different attributes, and the list wouldn’t be extremely targeted.
While collecting a list of customers within a certain demographic would tip the odds into the favor of the company that used it, it was not exceptionally precise. For example, even if a company wanted to market baby products to a list of customers who fell in the 13 to 29 year old age range, they would still have to guess whether the products are being purchased after a child is born, or in anticipation of the child being born.
Because they had to make guesses about certain customer behaviors, this reduced their chances of being successful, and to some extent, marketing was a game of chance. However data mining has changed this. As the marketing director continues to deal with more data, it will become more difficult for them to make strategic marketing decisions.
The reason for this is because the patterns will become more complex, and the number of customers will increase. The goal of using data mining is to help process this large amount of information. It is still the job of the marketer to decide which marketing strategy they will used based on the information they have received.
In order for a company to successfully acquire more customers, they must become familiar with term that is called response behaviors. Even if a large number of people fall under a certain demographic, they will respond to advertisements in different ways. The different ways that customers will respond to an advertisement must be considered.
The behavior of a customer is a form of data, and will create new scenarios that must be analyzed. The easiest response behavior to deal with is either a "yes" or a "no." If you send a direct mail ad to a customers, did they purchase any of the products that were advertised?
This is called the binary response, and it is easy to analyze. However, another customer response which is more detailed is called categorical response. This is a type of response in which a company can study different types of customer behavior. For example, instead of just finding out which customers paid for your products versus those that did not, you can go on to analyze which products each customer purchased. As you can see, this is more detailed. It gives you more information that you can allow you to make better marketing decisions.
Data mining is a powerful tool that will allow you to refine the data you receive on customers. It can help you analyze data that is too large to be done by a human. However, it can only present patterns or predictions to you. It is the person who uses the tool that must make the ultimate marketing decision.
