Data cleaning is an important step to ensure customer data is up-to-date, accurate and actionable. There are various best practices that can help maintain a clean database, such as regularly auditing the data, standardizing contact data, verifying data accuracy and integrity, identifying and merging duplicate records, and unifying data. Tools like Omeda’s customer data platform can help automate data cleaning processes and ensure data accuracy.
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Data cleaning is essential for ensuring that your customer data is actionable and easy to use. Unfortunately, many marketers fall short on that front: 45% of marketers don’t validate their data for quality and accuracy, and 62% use incomplete or invalid prospect data, according to research from Mercury, a creative digital marketing agency. That’s bad news, because inaccurate prospect data can undermine your marketing campaigns before they even begin. There’s the obvious consequence — not being able to reach your prospects at right email address. But if you never check your contact lists for accuracy, you might also assume that …
Data Cleaning Best Practices For a Better Database – Omeda was originally published on Omeda
