Cloud-Based Marketing Analytics Using Apache Flink for Real-Time Data Insights

This research introduces a proposed cloud-based marketing analytics architecture incorporating Apache Flink that parses and analyzes an RTDS. The framework is intended to maximize marketing communication plans by providing options to segment, behave and even predict consumer response in real-time. Marketing information from e-Commerce sites, social media marketing, and email marketing campaigns are obtained using Apache Kafka and processed in real time using Apache Flink. It adopts cloud-based nature of profound scalability to address the efficacy of data processing and storage. The outcomes show that the architecture performs low-latency data processing (with mean 150 ms), high streaming throughput (2000 events per second), and good customer behavior prediction (up to 85% accuracy). Implementation of real time customer segmentation in our company made a dramatic impact on variable recommendations where the conversion rates were raised by 50%, other fields such as retargeting and emails also recorded high engagement. Further, the system was found to be quite robust and sustainable with regard to the traffic loads that it had the capacity of managing up to 50GB per hourly rate without compromising on speed. All in all, the framework indicates the prominence of real-time marketing analytics to make better decisions and achieve greater marketing returns, to understand the consumer behavior patterns and their effects on the business, and to even rebuild the overall business performance. The analysis also emphasizes on how Apache Flink can be used to work with big data streams and provide real-time solutions for today’s progressive marketing.