The continuous advancement of technology and communication brings not only opportunities but also challenges. Today is relatively easy to get data about your customers. It is also not overly complicated to deliver personalized content through ad campaigns. As a result, if data is accurate, the conversion rate and revenues should also increase. But the rising number of customer contact points raises the chances of errors added to customer databases. If companies don’t take the appropriate measures and cleanse their customer database, their marketing efforts will become less effective. Obviously, a company will not have a high data quality with no understanding of what data quality actually is.

Data Quality Definition

Even if data quality definitions may vary, there are several common key aspects. For starters, data is of quality when it achieves the requirements of its use. This means that data of high quality should allow companies to easily and effectively communicate with their customers and determine their needs. The definition is broad. But, it has the advantage of supporting enterprises in many different industries to find out if their data meets their standards. However, there are more detailed aspects that you should consider:

Accurate Data

It is important to have accurate information about your customers. With incorrect or incomplete data, the marketing department will not be able to reach out to a large enough audience.

Relevant Data

Data must be always relevant to the company’s business goals. Don’t waste expensive storage space for irrelevant data that might also prevent you identify key metrics in your analysis.

Complete Data

Another aspect you should consider is data completeness. Without complete data, it is not possible to get a comprehensive view of your customer’s needs. Thus, you must include all appropriate information and make sure that is constantly updated.

Why is Data Quality Important

The most important advantage data quality brings is that it lets enterprises stay in touch with their customer and understand their needs. Here are the most important benefits that data of high quality can bring:

Reduced mailing costs

With accurate customer data, you will reduce the amount of undeliverable mail. In turn, this will save money in postage costs. Also, the company could get significant postage costs discounts for shipping and direct mail.

Better customer relations

Data quality lets sales and marketing departments know and understand their customers. Hence, they will not send mails that customers don’t want to receive. Simply put, you will be able to anticipate and meet your client’s expectations.

Effective marketing

For example, lack of demographic data forces companies to only address the broadest audience. Most likely, this approach is a waste of money, because it targets people that are not interested in particular services or goods. By using demographic information, companies will be able to focus your marketing efforts more tightly and achieve your targets.

How to Improve Your Data Quality

As we have seen, data of high quality can bring significant advantages. WinPure Clean & Match is the leading provider of data quality software for businesses of all sizes. It is specially engineered to help them understand client data. Its advanced fuzzy matching algorithms will let companies cleanse and deduplicate their data with almost no effort. Furthermore, the new Data Cleaning Matrix provides several tools specially designed to transform, clean, and standardize data. Its data profiling tool provides more than 25 different statistics and highlights potential data quality issues with different colors. Our software also lets you automatize your tasks by scheduling them on a Daily, Weekly or Monthly basis.

Download WinPure Clean & Match 30 DAY FREE TRIAL and find out why large companies such as Bank of America, Vodafone, McAfee, Hewlett-Packard, and Emirates are happy to use our leading data quality software.

Written by Andrei Popescu

Andrei is a detail-oriented writer and enjoys the process of researching and learning new things all data quality.

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