Building a better data quality strategy requires a layered approach

It goes without saying that high-quality customer data is critical to a successful campaign.

Recent research from Dynamic Markets indicates that 86 percent of businesses admit to having incomplete or inaccurate customer data files. Additionally, 75 percent of businesses admit that potential revenue is lost because of missed opportunities due to poor data quality.

These data quality problems occur in an environment where most marketers already employ list hygiene services or sophisticated data quality software.

Few would challenge the idea that getting data entered into your database correctly in the first place is essential to good data quality. Verifying and correcting data before it enters your company’s system can also enhance your existing backend hygiene processes.

As a result, developing proactive processes and taking advantage of real-time verification solutions can save your organization time and money currently spent reactively fixing problems.

So what else can your organization do to make sure that your data quality efforts are actually providing clean data and improving your bottom line? One approach is to consider the many layers of data you can verify to improve response.

At the most fundamental level, you can review the format and deliverability of an address against data from national postal authorities.

A more advanced approach would include verifying a customer data to understand if the name agrees with known residents at an address.

If that isn’t enough, you can test whether or not an address is a business or residence, which in addition to reducing the volume of returns can save you residential delivery surcharges from parcel carriers.

Accurate name and address data verified at point-of-entry helps minimize incidents of undeliverable mail, preventing returned-mail processing fees and time-consuming hassles.

More accurate data also helps with more effective segmenting and targeting. Finally, getting it right the first time supports a company’s commitment to customer service.

It is no great secret that there is room for improvement in data management practices, whether driven by the need to improve customer satisfaction or stem revenue leakage.

Exploring a range of datasets and technologies that can verify information before it enters your system can have a direct impact on your bottom line.

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