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Abstract
The increasing digitalization of the Business-to-Business (B2B) market has driven the need for Marketing Analytics platforms capable of processing and analyzing data in real-time. This article presents a systematic review of recent literature (2020-2025) to address the technical challenges inherent in real-time data synchronization from multiple third-party sources (e.g., CRM, advertising platforms, product analytics). The research focuses on the areas of Data Engineering, Systems Integration, and Scalability. The main challenges identified include the heterogeneity of data schemas, the high ingestion rate, and ensuring data quality (cleansing, merging, and transformation) to build a “Single Version of the Truth” for the B2B customer. A scalable reference architecture model is proposed, highlighting the role of an asynchronous worker system (such as BullMQ) for task orchestration and the use of a high-performance columnar database, such as ClickHouse, for real-time analytical storage and processing. This model aims to provide a robust foundation for unifying marketing, sales, and product data, which is essential for predictive decision-making and personalization at scale.
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