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Study Your Customers with Data Mining

By Exforsys | on July 26, 2006 |
Data Mining

After you have generated a model with a data mining program, you will next want to use the model to make predictions about your customers. Using the model is different from creating it, and it will be used numerous times to solve a number of different problems.

You could create a model which would predict the chances that customers who are sent a direct mail advertisement would respond favorably to it. To build this model, you would need to look at historical information. As the model is created, the data mining program will study information which is based on existing customers that buy products from the company.

The information from the existing customers would be used as inputs, and the output would come in the binary form of a 1 or 0. Once the model is generated, it can be applied to new information in order to create predictions about things that are unknown. This is where the power of data mining becomes evident. When you take the data mining model and use it to make predictions about behavior you are studying, you are using a technique that is called scoring.

The prediction that the model makes is referred to as being the score. While the score can come in a wide variety of different forms, the goal is basically the same. It will provide you with data that can predict the possible response rates of your existing customers or potential customers.

Generally, the score will come in the form of a number. Once you have the score, you will be able to study your customers or prospects. In reality, this is where the real work begins. Up to this point, most of the work was done by the computer and data mining tools. It is now your turn to analyze the information that the computer has displayed. This is a job that can be difficult and tedious, and it is your goal to analyze the data with as few errors as possible. Once the computer has scored a group of customers, it is your job to sort through this information.

When you find the customers or prospects who fall under the top 25 percent, you will want to target them with your sales offer. In addition to this, you will need to pull up the contact information of these customers so that you can send them your product offer. Once you have the contact information of the customers, you can then proceed to mail them your offer. While many companies run marketing campaigns once or twice a year, it may be helpful to do this much more rapidly. Instead of mass marketing to a large group of customers once every six months, why not market to smaller groups of targeted customers on a weekly basis?

While scoring your customers may sound like a simple process, there are a number of errors that could occur. First, you may score the wrong prospects. It is also important to make sure the correct database is scored. Generally, errors in scoring are caused by a lack of communication with the marketing department and the IT centers of a company. Another mistake that can be made is using the wrong model to make predictions.

Depending on the strategy of the company, multiple models may be used, and in a situation like this, there is a high probability of errors occuring. Once you obtain the scores, it is important to make sure they are stored in the right location.

If the scores are placed in the wrong location, this can cause problems. It is also important to understand the scoring system. Scores can come in a wide variety of different forms, and if the people working in the department don’t understand the scoring system, they could make costly mistakes.

If you are marketing you are marketing your products or services on a consistent basis, you can afford to make any mistakes. If you have errors, you won’t have much time to correct them. Because of the ongoing communication that will occur between the marketing department and IT center, it may be helpful to use software to make sure the communication process runs smoothly. Learning how to study your customers is crucially important.

« « Connection Between Data Mining and Customer Interaction
Analyze Your Customers With Data Mining » »

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Editorial Team at Exforsys is a team of IT Consulting and Training team led by Chandra Vennapoosa.

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