For most manufacturers, success or failure is determined by how effectively and efficiently their products are sold through their marketing channel members, so the management of marketing channels plays an important role in market competition. Most existing work studies the problem of marketing channel management in a qualitative way. Recently, with the increase of amount of sales data, how to enhance the marketing channel quantitatively is significant. As the marketing channel can be viewed as a tree, in this paper, a new marketing channel management strategy based on frequent subtree mining is proposed. The proposed method is illustrated under the real-world sales data in ERDOS group. Firstly, the tree transaction is formed monthly. For each monthly transaction, only those channel members that pass the basic sales plan will be included. Secondly, we use the TreeMiner algorithm to discover embedded frequent subtrees. Finally, different management strategies are used for different kinds of discovered patterns. We show that our method can correspond to the seven decision areas in traditional marketing channel management.
Peng Gao, Daoping Wang
"A New Marketing Channel Management Strategy Based on Frequent Subtree Mining,"
Communications of the IIMA: Vol. 7
, Article 5.
Available at: https://scholarworks.lib.csusb.edu/ciima/vol7/iss1/5