skip to main content
How Good Data Makes for Great Direct Mail

How Good Data Makes for Great Direct Mail

Wednesday, May 15, 2019

In an age of email, social media, and big data, marketers have many choices for engaging their customers and prospects. By leveraging multiple channels and consistent messaging across all of your marketing touch-points, you’ll quickly be able to see why direct mail is one of the most impactful channels you have at your disposal.

Although many might say they believe in the power of direct mail, a common question that often arises is, “How can I make my direct mail marketing piece effective?”

The answer is simple: you need good data and a great message.


Your approach to any direct mail campaign should always focus on data first.

Like other marketing channels, the need for accurate and pertinent data builds your campaign's foundation. If your data isn’t accurate and relevant to your target audience, your return on investment (ROI) results will be inadequate. Remember, the quality of your data is crucial not only to engage your current clients but also in prospecting for more of them.

Here are two key factors to keep in mind about your data:


Making sure your data is accurate and up-to-date is essential to maintaining the trust of your customers.

Data is not something that’s freely given anymore. Like trust, it’s something you need to earn. In fact, according to Bardess Group: “the implementation of a Data Quality Initiative ultimately leads to increases of 15 to 20% in revenues and 20 to 40% in sales.”

Here are three actions you can take to ensure you’re working with quality data.

  • Save money and ensure data accuracy with CASS (Coding Accuracy Support System).
    CASS is used by your mail house to ensure accurate addressing and to meet the USPS requirements for lower postage rates.
  • Guarantee delivery with DPV (Delivery Point Validation).
    If an address is not matched during the DPV process, two things happen. First, the postage for that piece will end up being higher than an address that did match. Second, the chance of that mail piece being delivered drops by nearly 75%. Your mail provider should be able to send you the DPV results, and you can look at the addresses that did not match. Be sure to take the time to get these records updated in your system by contacting the customer. The savings can be significant by not mailing to the records that don’t match.
  • Update, update, update! Over 40 million Americans change their address annually, so if your list has not been updated in over a year, chances are up to 20% of your list is no longer at the address recorded. That’s where the NCOA (National Change of Address) comes in. Once your list is run through the NCOA database, your mailing provider should be able to send you any required new addresses. Make sure to take the time to update your database with the NCOA results. By implementing a system for these records to be updated, you can reduce your undeliverable mail and save money by not buying print or postage for these records.

Remember, putting in the extra effort on the front end to properly review your data will reap tremendous benefits as you associate facts and events with your prospects and customers.


It’s easy to buy data for prospecting, but how do you know what data to buy?

A data modeling program is an excellent tool to help guide you. It takes the guesswork out of determining who your best customers are. Data modeling aims to define a company’s target customers and leverage their most important characteristics to establish an optimal audience for marketing efforts. This process typically includes an in-depth profile of your current data and a statistical view of the targets.

Keep in mind that many times what a client thinks is their ideal audience is either inaccurate or too broad. A data modeling vendor can take your list and run it through their algorithms to find demographics that stand out. Once they have run this process, they will deliver a report showing the characteristics that make up your best customers. This information is useful in two ways. First, you can use that model to find new potential customers. Secondly, you can now market to your current customers more aggressively.

Data is the lifeblood of any organization. What are you doing to treat it as such?