Data analysis

The 9 Gotchas of Bad Direct Mail Marketing Data: Updated

A little while ago, we looked at the importance of good data and entering it correctly in our systems from the get-go.

Good data plays a huge part in successful marketing efforts, especially when doing a physical mailing. You can save a lot of money by avoiding a few simple, common direct mail marketing data mistakes.

Our official countdown list of the Top 9 Gotchas of Bad Direct Mail Marketing Data

  1. Multiple recipients per household: You wanted to send one postcard per household, but you ended up sending three to the same address. How did this happen?

Well, perhaps both spouses plus an adult son from the same family are all in your database. Luckily, Microsoft Excel offers a “remove duplicates” feature, which can help you eliminate duplicate entries from your data. You can auto-search based on specific columns—like address—and then decide which duplicate entry to keep. Checking for duplicates is an easy way to avoid sending out more pieces than necessary.

  1. Multiple entries for the same person: Adding a customer into your data system more than once is an easy mistake to make. And an easy error to fix—exact duplicates are no problem. As we learned from gotcha 9 above, those are easy to remove from spreadsheet data.

Trickier to fix are variations of the same name: Michael, Mike, Mikey, M., or even an incorrect spelling. The best solution for avoiding these types of duplicates is committing to accuracy and consistency when capturing the data in the first place.

  1. The wrong address: Wrong addresses can happen due to data entry problems. It’s also possible that your data is out of date, and the person no longer resides at the address you have on file.

As part of data preparation for our customers’ mailings here at The H&H Group, we run a postal report to look for any recipients who have recently moved. We send any updated address info to our clients so they can update their records. Unfortunately, this search will only show results for address changes within the last six months, but it is still a useful check to perform when prepping a mailing list. (And if your current mail house is not doing this check, you need to give us a call before your next mailing!)

  1. Address information in the wrong field: During data entry, it is easy to enter the state designator in the city box accidentally, and suddenly all subsequent address data is shifted over into the wrong field. You can avoid this by using electronic forms with validation logic. If that is not available, a second glance to confirm proper placement is worth the time it takes to ensure good data.
  2. Complete addresses in a single data cell: Creating a spreadsheet with all of the address information in one cell can make for easy typing, but this makes using handy features in Microsoft Excel, like data sort, almost impossible. Additionally, some formulas can break up the data and accidentally relocate it into the wrong fields, especially if the breakpoints are not obvious.

Always give each piece of data its own cell!

  1. Dropped leading 0 in the zip code: Some states have zip codes that begin with a zero. In fact, this is much of the Northeast United States, including much of New England and New Jersey! If the spreadsheet cell that a zip code is entered into is not formatted correctly in Excel, that zero is dropped, resulting in an invalid 4-digit number.

To fix this, set the cell format to “Special Characters – Zip Code” and Microsoft Excel will be smart enough to hold on to the zero.

  1. No address at all: If only part of a customer record is created and there is no address, there is no way to connect with the customer through a direct mailing. The only way to correct this is to have someone on your staff research the customer.

Better upfront processes to ensure clean data at its point of entry in your systems are the best solution to increase the efficiency of your marketing efforts.

  1. Special characters: Special characters can really mess up processing direct mail marketing data. Suddenly, your 2,000 records turn into 20,000 because Microsoft Excel is reading delimiters that are not meant to be there, which can divide your data in less than desirable ways.

Even worse than a special character is a hidden special character like a carriage return. It is hard to find something you cannot see!

And, the number 1 gotcha: Not using the most current, accurate, cleaned-up version of your data. Whenever The H&H Group processes data for a mailing, we always run the data through checks looking for these very gotchas. Finding and correcting these errors ensures that our customers receive the best possible outcome for their direct mail marketing campaigns at the best possible prices.

Additionally, we always share our corrections with our customers so they can improve their data.

Unfortunately, sometimes we see the old, unfixed data come back to us a couple of weeks later for a new mailing, with the exact same mistakes. Updating your master data set with corrected data from your mailing provider will help you avoid this gotcha and increase your response rate!

This article is a quick run-through of the most common errors we see when prepping direct mail marketing data. If you ever have any questions on how to make your mailing data better, The H&H Group in Lancaster, Pa. would love to help.

If you need affordable printing or fulfillment services for your direct mail marketing campaign or other marketing efforts, contact us to see how we can help you improve your direct mail campaigns and streamline your marketing strategy.

Happy Mailing!

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