Efficient customer segmentation in digital marketing using deep learning with swarm intelligence approach

Highlights：

• Developing an efficient AI-based customer segmentation to improve digital marketing growth is a challenging task.

• The proposed model, uses an unsupervised deep learning model called a Self-organizing map with an improved social spider optimization approach that has been used for efficient customer segmentation.

• The customers are clustered using self organizing neural network (SONN). Based on the clusters, the customers are classified using the deep neural network (DNN) model.

• The experimental results prove the performance of the proposed model with high clustering and segmentation capability to improve the business profit in marketing.

摘要

•Developing an efficient AI-based customer segmentation to improve digital marketing growth is a challenging task.•The proposed model, uses an unsupervised deep learning model called a Self-organizing map with an improved social spider optimization approach that has been used for efficient customer segmentation.•The customers are clustered using self organizing neural network (SONN). Based on the clusters, the customers are classified using the deep neural network (DNN) model.•The experimental results prove the performance of the proposed model with high clustering and segmentation capability to improve the business profit in marketing.

论文关键词：Digital marketing,Customer segmentation,Clustering,Classification,Self-organizing map,Social spider optimization,Deep neural network

论文评审过程：Received 24 June 2022, Revised 23 August 2022, Accepted 30 August 2022, Available online 7 September 2022, Version of Record 7 September 2022.