Lesson 2: Building a Targeted Mailing Scenario
The marketing department of Adventure Works wants to increase sales by targeting specific customers for a mailing campaign. By investigating the attributes of known customers, the company hopes to discover patterns that they can then apply to potential customers. They hope to use the discovered patterns to predict which potential customers are most likely to purchase a product from the company.
Additionally, the marketing department wants to find any logical groupings of customers already in the company's database, such as customers who have similar demographics and buying patterns.
The company's database, Adventure Works DW, contains a list of past customers and a list of potential new customers.
In this lesson you will create a targeted mailing scenario. After you complete the tasks in this lesson, you will have the following:
- A set of mining models that will suggest the most likely customers from a list of potential customers.
- A clustering of current customers.
To complete the tasks in this lesson, you will use the Microsoft Naive Bayes Algorithm, the Microsoft Decision Trees Algorithm, and the Microsoft Clustering Algorithm.
This lesson contains the following topics:
- Creating a Targeted Mailing Mining Model Structure (Data Mining Tutorial)
- Modifying the Targeted Mailing Model (Data Mining Tutorial)
- Exploring the Targeted Mailing Models (Data Mining Tutorial)
- Testing the Accuracy of the Mining Models (Data Mining Tutorial)
- Creating Predictions (Data Mining Tutorial)