What Is Data Quality And Why Is It Important? - Gilbert

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Data Quality

 Data quality is important because it allows you to spot potential issues that could impact your bottom line. Data quality is the first step towards improving customer experience and delivering value for customers. The term “data quality” refers to whether you have good information about your customers, how accurate the data is, how it has been maintained, and how accessible it is. A lack of robust data can lead to delays in delivery or in the decision-making process. Customer experience is improved by having access to relevant customer information quickly and accurately, which allows businesses to be more effective as they focus on delivering value for customers rather than dealing with a lot of data manually.

To get high-quality email listing data services for your business, contact us today!

What Does Data Quality Mean?

Data quality is the level at which accurate and properly formatted data is available for transaction processing, decision-making, and other kinds of business processes.

There are four important characteristics of data quality:

Completeness: Data completeness refers to whether all relevant fields are complete, working together to provide a complete picture of each record in the dataset.

Validity: The degree to which the data satisfies the requirements in effect at the time it was captured.

Accuracy: The term “data accuracy” refers to how correct or precise the data is when compared with its original sources. For example, a customer list may have inaccurate contact information (e-mail addresses or phone numbers) because some records were filled out incorrectly by customers themselves or by an employee on their records.

Timeliness: The point in time when a particular observation was created or captured by the data collection process.

Why Is Data Quality Important?

Data quality is an important consideration for any organization seeking to leverage their data. It is more than just ensuring the accuracy of the data being used, it’s also ensuring that the data is trustworthy, reliable, complete, and usable.

The MIT Sloan Management Review reports that organizations waste 15-25% of revenue due to poor data quality, which is caused by unused tools or inadequate data strategy.

Business process optimization is critical for data quality. Marketing campaigns often fail because vendors do not send the right message to the right customers. The data conflicts between departments slow down the process and require more manual work.

Data quality has a significant impact on the efficient response to business changes. Poorly-researched and outdated information can’t reveal new possibilities. Low-quality analytics won’t tell you if your current campaigns are working or need to change. Financial reports may show a misleading picture with incomplete or outdated data, which can affect timely performance. As companies are rapidly adopting automation, they need to value high-quality data more.

Benefits Of High Data Quality

Because of a lack of good data, it is hard for marketers to make better decisions in marketing campaigns. When the data is in a poor state, the marketing team might not know what to do. This can lead to ineffective and expensive marketing campaigns.

By paying attention to data quality and improving data quality, marketers will have more opportunities to improve their performance and find new techniques that are more effective with less expense.

Good data quality can be achieved by:

  • Clear and correct content to ensure that it is understandable by the audience
  • Ensuring that the message in the content appeals to the target audience;
  • Being specific and relevant when communicating the messages or advertising campaigns to users.

Five important benefits of acquiring good data quality:

  • The ability to make decisions based on real data means very clearly understanding which marketing tactics are actually working.
  • Marketing campaigns become more efficient and personalized.
  • Increased return on investment as a result of less wasted marketing spend.
  • Lower campaign management costs because less data cleansing is required.
  • Companies can use artificial intelligence to automate some of their marketing campaigns, resulting in increased productivity.

Whether you have your own business or are working for another organization, data quality is an important concept to understand. The better the data quality of your business or organization, the more apt you’ll be to see success – thus, it’s something worth taking the time to examine and fix if need be. And whether you’re a business person or just someone interested in business, understanding data quality will help you make better decisions when it comes to your investments.

Without good data, you can’t have a quality analysis. This applies no matter what type of company you have or what industry you are in. So to ensure that your business’ data is of good quality, you should start with your database. It must be accurate, timely and consistent with its intended meaning.

Email listing data service providers like Gilbert Data can spend more time helping business users and marketing executives get the most out of data in their systems. They can also focus on more productive tasks, such as promoting best practices for reducing data errors.

Final Thoughts

As more and more companies are collecting and storing a lot of information related to their customers. Organizations that have invested in customer data management have seen significant benefits. For example, one company was able to find additional revenue opportunities by using customer data insights to improve its sales process and increase conversion rates by 10%. The future is only going to bring even more opportunities for organizations with high-quality email listing data services.

You already know that data quality directly impacts customer satisfaction and financials. If you don’t know how to get quality data, we can help. We specialize in offering high-quality email listing databases that are ready-to-use and cost-effectively.

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