An efficient smart data mining framework based cloud internet of things for developing artificial intelligence of marketing information analysis

Because of the big volume of marketing data, a human analyst would be unable to uncover any useful information for marketing that could aid in the process of making decision. Smart Data Mining (SDM), which is considered an important field from Artificial Intelligence (AI) is completely assisting in the performance business management analytics and marketing information. In this study, most reliable six algorithms in SDM are applied; Naïve Bayes (NB), Logistic Regression (LR), Random Forest (RF), Support Vector Machine (SVM), ID3, and C4.5 on actual data of marketing for bank that taken from Cloud Internet of Thing (CIoT). The objectives of this study are to build an efficient framework to increase campaign of marketing for banks by identifying main characteristics that affect a success and to test the performance of CIoT and SDM algorithms. This study is expected to enhance the scientific contributions to investigating the marketing information capacities by integrating SDM with CIoT. The performances of SDM algorithms are calculated by eight measures; accuracy, balance accuracy, precision, mean absolute error, root mean absolute error, recall, F1- Score and running time. The experimental findings show that the proposed framework is successful, with higher accuracies and good performance. Results revealed that customer service & marketing tactics are essential for a Company’ success & survival. Also, the C4.5 has accomplished better achievement than the SVM, RF, LR, NB, & ID3. At the end, CIoT Platform was evaluated by response time, request rate & processing of bank data.