A Best-Marketing Time Prediction Algorithm Based on Big Data Analytics

As the rapidly development of 5G mobile communication network and smartphone market, almost every person takes a mobile phone during their daily time. To be sure, the expansion of smartphone makes people’s life more convenient. According to the latest research report, the current 40%–45% penetration of smartphone in the mobile phone market will reach to 65% by the year 2020. It is well known that the customers watch TV, chat with their friends and go shopping by their smartphones at any moment and anywhere. As a result, the little device carries abundant information of a person’s profile and behavior. In that situation, telecom operators could use data mining technology to develop personal daily routine information such as the busiest time in the day and which time to go to bed for rest. In that way, the telecom operators could take full advantage of this research achievement in accurate marketing. In this paper, a best-marketing time prediction algorithm (BMTA) is proposed to analyze the daily routine of customers and to predict best-marketing-time by using big data analytics. At last, the analysis results show that the algorithm proposed is high-efficiency.