tailieunhanh - Data For Marketing Risk And Customer Relationship Management_1

1 công thức khai thác dữ liệu cho thành công để tăng lợi nhuận và giảm chi phí trong thế giới kinh doanh ngày nay-Cuốn sách này cho thấy bạn làm thế nào để tạo ra và thực hiện mô hình các câu hỏi khai thác nhất thường yêu cầu dữ liệu tiếp thị, bán hàng, phân tích rủi ro và quản lý quan hệ khách hàng và hỗ trợ. | Page 2 Imagine you are someone who loves to cook In fact one of your favorite activities is preparing a gourmet dinner for an appreciative crowd What is the first thing you do Rush to the cupboards and start throwing any old ingredients into a bowl Of course not You carefully plan your meal. During the planning phase there are many things to consider What will you serve Is there a central theme or purpose Do you have the proper tools Do you have the necessary ingredients If not can you buy them How long will it take to prepare everything How will you serve the food sitdown or buffet style All of these steps are important in the planning process. Even though these considerations seem quite logical in planning a gourmet dinner they also apply to the planning of almost any major project. Careful planning and preparation are essential to the success of any data mining project. And similar to planning a gourmet meal you must first ask What do I want to create Or What is my goal Do I have the support of management How will I reach my goal What tools and resources will I need How will I evaluate whether I have succeeded How will I implement the result to ensure its success The outcome and eventual success of any data modeling project or analysis depend heavily on how well the project objective is defined with respect to the specific business goal and how well the successful completion of the project will serve the overall goals of the company. For example the specific business goal might be to learn about your customers improve response rates increase sales to current customers decrease attrition or optimize the efficiency of the next campaign. Each project may have different data requirements or may utilize different analytic methods or both. We begin our culinary data journey with a discussion of the building blocks necessary for effective data modeling. In chapter 1 I introduce the steps for building effective data models. I also provide a review of common data mining

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