Digital Marketing
2
min read

What are Marketing Data Pipelines, and How Do They Work?

Published:
April 15, 2021
Updated:
February 6, 2024

If you work in advertising, marketing, or specialize in marketing analytics, it’s likely you’ve heard of data pipelines. But what is a marketing data pipeline, and is using one necessary? Let’s break it down.

What are marketing data pipelines?

A data pipeline is a series of processing functions that ingest raw data from various sources and transport it to a desired destination, undergoing a series of transformations along the way.  In the context of marketing analytics, data pipelines can take raw data (like customer behavior or ad performance metrics), process it, and generate insights that feed into marketing strategy and execution.

While the analogy of a physical pipe, where water flows from a well to your faucet, helps visualize the basic concept, data pipelines encompass a broader spectrum of functionalities. They handle diverse data formats, ensuring compatibility and coherence across different data sources.

Marketing Data Pipeline

The Role of Data Pipelines in Marketing Analytics

For marketers, data pipelines play a crucial role by aggregating results from various advertising platforms, integrating them, and delivering comprehensive insights. This integration is essential for creating a unified view of campaign performance, customer engagement, and overall marketing effectiveness

Data pipelines help solve some big problems faced by marketers: 

Inconsistency Across Tools: Marketing teams often grapple with varying metrics and visuals across different tools, which can lead to inconsistent reporting. Data pipelines mitigate this by standardizing data formats and metrics, ensuring uniformity across reports.

Manual Data Aggregation: The traditional approach of manually compiling data from multiple sources is not only time-consuming but also prone to errors. Data pipelines automate this process, saving valuable time and reducing the risk of inaccuracies.

Limited Customization: Tailoring reports to meet specific client needs can be challenging with rigid reporting tools. Data pipelines offer the flexibility to customize data processing and reporting, aligning with individual client requirements and strategic goals.

Data Quality & Security: Quality and security are paramount in data management. Data pipelines employ sophisticated processes to validate, cleanse, and de-duplicate data, ensuring high integrity and reliability of the information delivered.

Scalability: The structured organization of data pipelines facilitates scalable distribution, making them adaptable to growing data volumes and complex business needs.

Technical Deep Dive: Types of Data Pipelines

Data pipelines come in different types, each with its unique application and significance in marketing analytics. Let's look at three major types: ETL, Streaming, and Batch Processing.

ETL Pipelines: ETL stands for Extract, Transform, Load. These pipelines take data from one or more sources, transform it into a format suitable for analysis, and then load it into a destination database. In the realm of marketing, ETL pipelines can help organize and make sense of vast amounts of data, thereby simplifying the analysis process and providing a solid foundation for data-driven decisions.

Streaming Data Pipelines: Streaming data pipelines enable the processing of data in real-time. This means that as soon as data enters the pipeline, it is processed and made available for analysis. For marketers, this can be a game-changer, particularly in scenarios where timely responses are critical—like in programmatic advertising or real-time personalization.

Batch Processing Pipelines: Batch processing involves processing data in 'batches' or groups, at scheduled intervals. In contrast to streaming pipelines, batch processing pipelines may not offer real-time insights, but they are often more practical for handling vast amounts of data. For large-scale marketing campaigns that rely on historical data or long-term trends, batch processing can be a reliable and efficient choice.

Beyond the Data Warehouse: Multiple Endpoints for Data Pipelines

While data warehouses are a common endpoint for consolidated data storage and analysis, data pipelines offer the versatility to channel data into various platforms. This includes direct feeds into analytics tools, operational databases, or even bespoke business applications, providing businesses with the flexibility to choose endpoints that best suit their operational and analytical needs.

In the landscape of marketing analytics, where data is the cornerstone of strategic decision-making, understanding and leveraging data pipelines can significantly enhance operational efficiency and client satisfaction. By automating data aggregation, ensuring consistency and quality, and offering customization and flexibility, data pipelines stand out as a crucial tool in the marketer's arsenal.

To learn more about NinjaCat’s marketing data management solutions, including data pipelines, connect with one of our experts today.

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