This article originally appeared on the BeyeNETWORK.
In this series, we have asked the question: how can a data warehouse be used for the corporation’s competitive advantage? The most obvious and immediate answer is that the data warehouse can be used to segment customers into different categories and then we can measure those categories over time.
By analyzing and extracting data from the data warehouse, a corporate manager can observe that there is a flow of customers between different categories. The data warehouse is useful in categorizing customers according to the data stored in the data warehouse. Some of the most useful data found in the data warehouse are:
- The length of time the entity has been a customer;
- The number of purchases the customer has made;
- The dollar value of the purchases that have been made;
- The offer that first attracted the customer to the company;
- The interval between the first and second purchase; and
- The number of complaints, product modifications and special advertisements that have been required by the customer, etc.
Using this information and other analytical data in the data warehouse, the customers can be categorized and the corporation can determine a strategy to maximize its profit from each category.
While segmenting customers is an important step forward, more sophisticated measurements can be made using the capabilities of the data warehouse.
The measurement and analyses that are discussed are the absolute heart of corporate strategic planning. In terms of understanding and defining business strategy, these activities form the nexus between corporate performance management and customer behavior.
Using the data warehouse optimizes the corporation’s ability to predict and effectively react to changing customer behavior.
Figure 6, below, shows the measurements of different categories of customers over time.
At the top of Figure 6, customers are seen to flow between categories. The number of customers and the rate in which they are moving between categories is of vital concern. The corporation should be vitally interested in monitoring these changes. Is it capturing more profitable customers? Is it losing profitable customers? More to the point, why are these changes happening? What is causing profitable customers to be driven to a sustaining category? Using the data warehouse, the corporation must determine which factors are relevant to the movement between customer categories, both positive and negative?
Furthermore, the movements that have been shown are not only important to the profitable and sustaining customer categories. The movement of customers to and from any category is important. Therefore, the quantity and quality of the data in the data warehouse must be capable of continuously tracking the customers within the categories.
Figure 6 also shows that the growth of a category is also very important. From a collective standpoint, the growth and contraction of each of the categories of customers is vitally important in order for the corporation to properly price its goods and services, attract new customers, maintain its customer base and maximize profitability.
This ends the series of articles on the relationship between corporate competitiveness and the data warehouse. It has been shown that the data warehouse can be used in many ways to analyze the segmentation and growth of customer categories. The data warehouse gives management the capability of taking a snapshot of the business at anytime. The changes in categories and the reasons for the migration of customers between categories are at the heart of corporate strategy. The effective use of the data warehouse gives the corporation the competitive edge it needs to achieve maximum profitability.
To read the first four articles in the series, click—The Data Warehouse and Customer Profitability, The Data Warehouse and Unprofitable Customers, The Data Warehouse and Customer Profitability Cycles and The Data Warehouse and Customer Segments.
Bill Inmon is universally recognized as the father of the data warehouse. He has more than 36 years of database technology management experience and data warehouse design expertise. He has published more than 40 books and 1,000 articles on data warehousing and data management, and his books have been translated into nine languages. He is known globally for his data warehouse development seminars and has been a keynote speaker for many major computing associations.