Data Mining Case Study

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Register to read the introduction… New customer can be an existing customer that is new to the category when they found a new category of solution for their existing need. Like Amazon's customer, currently their customer may only buy book from Amazon. But when amazon offer new product called Kindle which is an e-book reader, the current customer may switch to buying Kindle instead of book.

When a company acquiring new customers, it is not simply targeting all the new customer with all the promotion tools and methods. The first thing that the company do is to estimate the customer lifetime value to find whether it worth to acquire. Finding the prospects customer to target on is important since not all customer segments are giving the same value to the company. After having prospect customer in hand, the company may needs to choose the appropriate approaches to get to the customer.

Data mining can often help in finding the customer that gives the highest value to the company and using appropriate promotional tools to get to the customer. As the amount of data increases, the process of choosing relevant demographic would be troublesome without data mining techniques.

Data mining helps the company in the following ways:

1. To differentiate and value customers and distribution
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This activity includes day-to-day analysis of prospects in the sales pipeline at a different points and can supply the company with important information about the effectiveness of their distribution partners.

Another way to measure performance is through intelligence information that can be derived from sales activity. This intelligence supplies management with aggregated information that is used to drive future strategies related to the sales and customer acquisition function.

Conclusion

Nowadays, data mining is very well-known to optimize the customer acquisition efforts. By combining the internal and derived data, it can improve hit ratio and decrease cost in customer acquisition. Data mining contribute greatly in identifying opportunities and weaknesses in the business that on the surface may not obvious. Thus, the result in deploying data mining tools in customer acquisition are getting the right customer with the minimum cost to generate the maximum revenue since it is targeting the valuable prospect customer with the appropriate channels.

References:

Sudaran, J 2008, 'Managing the Customer Lifecycle: Customer Acquisition', Lecture note distributed in the topic HBM271, Swinburne University, Sarawak on 13 October

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