Big Data Assisted Empirical Study for Business Value Identification Using Smart Technologies: An Empirical Study for Business Value Identification of Big Data Adaption in E-Commerce

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Abstract

The main problem for the big data for an e-commerce site is getting a meaningful data analysis, which the big descriptive statistics consider the most crucial usage. The collection, segmentation, and analysis of customer insights are critical to developing an effective and precise tailored experience for each consumer. Analyzing and segmentation of customer insights are essential to creating an effective and personalized experience for each customer. Using price optimization (BDA-PO), big data analytics has been proposed, enabling enterprising services like tourism, shopping, transportation, and creative industries to provide variable rates for products and services using Smart Technologies for E-Business and Commerce. Price optimizing can be automated with machine learning algorithms to enhance profitability when pricing decisions are taken effectively. When pricing decisions are made correctly, it is possible to automate price optimization using machine learning algorithms.

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APA

Zhang, C., Liu, B., Mohammed, B. S., & Jumani, A. K. (2023). Big Data Assisted Empirical Study for Business Value Identification Using Smart Technologies: An Empirical Study for Business Value Identification of Big Data Adaption in E-Commerce. International Journal of E-Collaboration, 19(7). https://doi.org/10.4018/IJeC.316882

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