Implementation of Slowly Changing Dimension to Data Warehouse to Manage Marketing Campaigns in Banks
Publication Type
Conference Proceeding Article
Version
acceptedVersion
Publication Date
5-2013
Abstract
Management of updating and recording campaign leads in data warehouse of any banking environment is complex especially with multiple campaigns are active simultaneously. As a way to avoid overly contacting customers for sales-based marketing contacts, the concept of Recency Frame is introduced to “lock” the customers who are targeted in Sales-based campaign for a specified time period. During this Recency Frame, the customer cannot be targeted by other Sales-based campaign under the same channel. This approach increased the difficulties of managing the customers’ data with proper data updating and storing and procedures have to be placed and made sufficiently robust for incorporation of the recency rules. In this paper, we will illustrate the concept of slowly changing dimension and how it could be utilized in an innovative manner in the data warehouse of a bank to update and maintain campaign records of customers.
Keywords
Banks, data warehouse, marketing, customer relationship management, MITB student
Discipline
Artificial Intelligence and Robotics | Marketing | Operations Research, Systems Engineering and Industrial Engineering
Research Areas
Intelligent Systems and Optimization
Publication
SAS Global Forum 2013: Proceedings: Data Mining (SUGI 31)
First Page
1
Last Page
8
Publisher
SAS
City or Country
San Francisco
Citation
WANG, Lihui; CHOY, Junyu; and CHEONG, Michelle L. F..
Implementation of Slowly Changing Dimension to Data Warehouse to Manage Marketing Campaigns in Banks. (2013). SAS Global Forum 2013: Proceedings: Data Mining (SUGI 31). 1-8.
Available at: https://ink.library.smu.edu.sg/sis_research/1676
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://support.sas.com/resources/papers/proceedings13/239-2013.pdf
Included in
Artificial Intelligence and Robotics Commons, Marketing Commons, Operations Research, Systems Engineering and Industrial Engineering Commons