Use Product Segmentation to Enhance the Competitiveness of Enterprises in the IoT

With the development of technology, the world of Internet of Things (IoT) is more and more developed, resulting in the rapid growth of diversified data and the formation of Big Data. Extract suitable data from a pile of seemingly useless materials, and apply different analysis and processing methods to form new and valuable data for the enterprise to enhance the competitiveness of the enterprise. Therefore, in this paper, the SOM (Self-Organization Map) will be used to aggregate the samples with similar characteristics from the product. In addition, RFM data analysis technology is used, we find out the more valuable customers in each cluster to solve the problem that the RFM total score has a large difference in different product attributes. After identifying the customers who are more valuable to the company, they then observe the products they purchased based on their past transaction data, perform the FP-Growth algorithm and construct the FP-tree. Finally, find out the frequent itemsets of the products through FP-tree and observe their relevance to provide companies with more accurate marketing strategies.