One of the biggest challenges many modern marketers face is trying to make sense of siloed marketing performance data across multiple different platforms.
A study conducted in 2022 found that 99% of marketing teams manage data from more than 10 sources, which is a big reason why many CMOs feel overwhelmed by data.
The solution to this challenge?
Consolidate all that scattered data into a single source of truth.
For many businesses, consolidating and standardizing data in one place nurse database is a big step forward. It helps eliminate data silos and enables more meaningful comparisons and deeper analysis.
However, for businesses to truly unlock the potential of data, simply aggregating the data is not enough.
This is the importance of data enrichment as a part of the data transformation process.
So, what is data enrichment?
Understanding data enrichment can be challenging, primarily due to varying definitions, particularly in the areas of customer data management and data integration.
When it comes to customer data management, data enrichment helps best for real-time web data and research applications you build deeper, more comprehensive customer knowledge by attaching relevant data about your customers, often from third-party sources.
For example, let’s say you have a customer database that contains basic details of your customers, such as name, postal address, and email address. You have phone numbers for some of your customers, but only a few records have this field filled in. Using a GDPR-compliant third-party solution, you can enrich the data with the phone number that is missing this field, making your database more complete.
In the context of data integration
Data enrichment is defined differently and is more about enhancing singapore data and increasing the value of existing data through automated data cleansing, automated calculations, and data transformations during the integration process.