The percentage of your data

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How well related pieces of data match up Format consistency: How consistently your data is formatted across the dataset Duplicate rate: that consists of duplicates Data precision: How precise your data points are To learn about all of that information in more detail, keep reading. Basically, you measure data quality by looking at a variety of different metrics. What are these metrics? Well, that depends on your specific needs. The metrics you use will often depend on the type of data you have and your intended use for it.

Then subscribe to Revenue Weekly, our email newsletter, for more digital Belgium Phone Number Data marketing tips! Don’t miss our Marketing Manager Insider emails! Join 200,000 smart marketers and get the month’s hottest marketing news and insights delivered straight to your inbox! ENTER YOUR EMAIL BELOW: Enter your work email (Don’t worry, we’ll never share your information!) What is data quality? Data quality refers to the overall usefulness of your data. It’s a measurement of how effective that data is for whatever you intend to use it for. Data quality is commonly used in relation to lead or client data. You want that data to help you market and sell to different leads.



So, in that context, data quality is a measurement of how accurate and helpful for marketing your customer data is. Why track data quality? The primary reason to measure data quality is simple: You want to ensure that your data is accurate and useful. Needless to say, collecting unhelpful data is a waste of your time, and building your marketing and sales efforts on inaccurate data can outright sabotage your campaigns. Data quality is also a useful measurement for choosing third-party data providers. As time goes on, first-party data is proving way more valuable than third-party data. That doesn’t mean it’s not nice to have third-party data sometimes, though.