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4 Tips for Data Quality Maintenance

Ashly Arndt | January 29, 2024

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Data quality is important in the fight against marketing fraud

Data quality is an important driving force behind marketers’ technology use. If they aren’t able to use address management solutions to ensure that consumers’ mailing addresses, emails and phone numbers are recorded accurately, then they won’t be able to effectively measure the efficacy of their promotional efforts. They also won’t be able to prevent fraud.

Small-scale data analysis can be just as important as big data

Many firms emphasize data quality because of the perceived importance of big data - the general consensus is "more is better," and corporate IT departments often work tirelessly to amass as much information on consumers as possible. But lately, another school of thought has begun to emerge. Perhaps size doesn't matter - it's not the amount of information in one's database that counts, but rather, its accuracy and relevance that matters more.

How retailers overcome the 'silo problem' in data management

In retail, the "silo problem" is especially worrisome.

Maintaining accurate data helps financial institutions service customers

While every company has a need for data quality, financial institutions are perhaps the best equipped to put their data to use, compiling accurate contact information, financial statistics and demographic knowledge on their customers, which in turn can help them perform customer analytics.

Why social media is king in direct marketing

Perhaps the best direct marketing outlet of all is social media.

Six critical steps to enriching customer experiences with data

Data is a critical but often overlooked component of delivering superior customer experiences. Most of us know firsthand how bad data creates a negative experience. Customers, rightfully, want to be treated as if they are special. They expect the companies they do business with to know them, understand them and remember them. Delivering on that expectation requires great data.

What's your frame of reference for data quality?

Companies should think about their particular goals with data.

Business users demand more from their data

Last week, Gartner released the new 2019 Magic Quadrant for Data Quality Tools. The report provides an overview of the players in the space and the “key capabilities that organizations need in their tool portfolio, if they are to address the increasing importance and urgency of data quality”.

Data quality problems are expensive and time consuming

At some point in today's dynamic business environment, companies will need to modernize.

Balancing the 'data-centric' and 'human-centric' approaches to marketing

Data and human interaction can work in concert to help companies improve.
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