Best Practices When Using
Variable Data in Direct Mail
When crafting a variable data mailing list, it's crucial to begin with accurate and up-to-date information to ensure your messages reach the intended recipients. Additionally, segmenting your list based on relevant criteria, such as demographics, purchase history, or location, enables you to personalize your direct mail content effectively and optimize your campaign's success.
Below we'll show best practices when creating a personlaized mail campaign. What seems to be the easiest way to prepare a campaign may result in extra time on machines and comprimising the accuracy of the list.
An Example Mail Campaign
Lets use a school as an example who is looking to send a letter to its community. Its community consists of prospective donors, current donors and suppliers, advertisers and business neighbours summerized as corporate donors. These three groups will each receive a unique letter so they'll have to be segmented.
Segmenting the recipients between three seperate mailing lists seems to be the logical way to carry this project out. By doing this we've essentially created three mail projects and opened the possibility of human error when mapping the lists to the letters.
As you can see above the lists are inconsistant. This opens up the possiblity of human error when mapping fields or processing the list with Canada Post.
One Campaign = 1 Mail List
DO NOT CREATE MULTIPLE LISTS FOR ONE CAMPAIGN. For efficiency and accuracy keep all the data within one list. Having one list reduces the risk of error and greatly improves the efficiency of the printing process. Segmenting a campaign should be done with a trigger field which tells the press which letter to print.
