In my thesis, I focused on the issue of marketing automation, with an emphasis on how modern technologies can simplify these processes. The theoretical part introduced key concepts of automation, its development through history, current trends, and its impact on business.
In the practical part of the thesis, I presented a concept of the architecture for a system designed to visualize and analyze data from the Google Shop online store. The data is collected in Google Analytics and then stored and processed in the Google BigQuery platform. The concept also includes the visualization of this data and analysis in a web application built using Node.js, Express.js, Vue.js, and Charts.js, which would provide insights and predictions for optimizing marketing strategies. The system was not actually developed but is presented as a conceptual architecture.
In the final part of the thesis, I examined the potential for system upgrades, such as advanced predictive analyses of market trends and customer behavior, integration with other marketing platforms, and I outlined how the system could be implemented. In conclusion, I can summarize that through the thesis, I gained significant knowledge about how automation works online and laid a solid foundation for building the proposed system for visualizing and analyzing online store activities.
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