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Nadia Basaraba
Nadia Basaraba

Posted on • Originally published at blog.coupler.io

What are the 5 Types of Marketing Data Management?

There are multiple operations happening in an average digital marketing data management system. Here are the most common ones.

Data integration

As marketing typically involves dozens of data sources, from marketing channels to CRMs, data integration is a key process in the data management cycle. It involves taking data from multiple sources that may have different data types and formats and bringing it together in the data storage facility.

Executing it correctly takes a deep understanding of the data systems of each of the sources used and transforms the data to conform to a uniform standard.

Data refining

Refining data is a process that searches for and eliminates data that is incorrect or corrupted. During data refining, your analytics tools should check for data entry mistakes and other inconsistencies, and catch wrong formatting like mixed-up date formats, duplicate or confusing column names, etc.

This turns raw data into a format that is easy to parse and analyze.

Data enrichment

Datasets are rarely complete, but thanks to having access to multiple sources, there’s a chance there is plenty of duplicate data. While the bulk of it should be cleansed during the refinement process, you can use some duplicate data to enrich your dataset. This means fixing missing data.

This also means adding more columns of data to a dataset, for instance adding sales data to the Facebook ads dataset. The result is a dataset that may provide much more insight into the effectiveness of your marketing campaigns.

Data stitching

Data stitching operates on a similar idea. It’s the process of taking customer data that is present across different datasets and integrating it into a single one. This allows for a deeper understanding of how customers interact with different departments like marketing and sales.

Data mining

Data mining helps businesses make more sense of large volumes of data. This process involves analyzing datasets to find trends and correlations. These are used for further business analysis and can help you arrive at conclusions about your marketing performance that may not be achievable with a simple marketing dashboard.

Check this useful guide to learn how to manage your marketing data effectively.

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