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Personalization: Digital Printing Data Strategies

The Dirt on Data

When it comes to digital printing, the quality of your list data is an important factor in meeting your turn-around expectations. The three data issues we routinely encounter that customers should watch for, bearing in mind that each of them can be corrected on our side, though the correction process may impact both turn-around and cost.

Name Personalization. We often see list data with the name exported as a single, full-name field, yet the layout calls for first-name personalization. This requires extra processing and can be inexact when it comes to multiple-word first or last names. If your layout calls for first-name personalization, try to export your name as two discrete fields.

Address Export Format. We use powerful mail processing software that standardizes the addressing of your mail piece based on postal regulations. This software requires that address data be exported as separate fields (address 1, address 2, city, state, zip). If the address information is formatted as a single field, the data will need extra processing and time to carefully check the result for accuracy.

Missing or Incomplete Record Data. We routinely see records within lists that lack the basic information required to mail, such as missing or incorrect zip codes, address information, or contact names.

Get a handle on these three issues for the smoothest possible digital print experience, minimizing the potential for delays.

For great tools to help you clean up your data, try listwist.com. It offers a free suite of tools for marketers that does everything from validate each record of data to split full-name fields into first and last name. It even can figure out if each contact on your list is male or female with over 99% accuracy. The site relies on a number of interesting strategies to execute the required logic, including a database of male and female first names to figure out gender. It's worth taking a look!


Beyond 'Dear John' Personalization!

The early days of variable data digital printing conjure up images of dot-matrix printers and personalized salutations. Our state-of-the-art systems provide both enhanced flexibility and true commercial print quality for each piece produced.

Understanding the possibilities

With variable data digital printing, each piece produced has the potential to be unique. This is achieved by marrying a base layout with specific information associated with the recipient.

Substitution variables

An example is a salutation such as Dear [firstname], which uses a simple substitution variable to insert each recipient's first name. Each variable that will be substituted must have its own unique placeholder. Our software links the placeholder value, in this case [firstname], with the corresponding field, which in this case is the first name field of your data.

Substitution variables are not limited to the standard name-and-address fields of a typical contact record. There is no limitation on the placeholders you can insert in your layouts; of course, each placeholder must have a field associated with it in your data set.

Substitution variables aren't limited to text, either. There are actually five types of substitution variables we can define for a given run:

Text. The most basic variable type, a text value in the record replaces the placeholder text in the layout.

Calculation. A calculation variable combines one ore more variable values and static text to create the value for each record. You could calculate the [fullname] variable, for example, by combining [firstname], a space and [lastname].

Color. You can specify Pantone or CMYK color values as a variable: Define a color not otherwise used as a placeholder, and we replace all instances of that color with the color associated with each record or with a logic statement (e.g. if male, blue; if female, red).

Image. You can create image substitution variables by including a file name with the data for each record. You'll need to supply us with all of the files that will be substituted, along with the image placeholder file name that has been included in the master layout.

Layout. Finally, you can define multiple base layouts for your job if you identify the layout file to use with each record. An example of where this might be applicable would be an event sponsored by two organizations. Invitations mailed to each contact could reflect the branding of the organization that supplied the contact be processed.

Creating rules to simplify data

In the layout example mentioned previously, you wouldn't have to specify the layout as part of your data set. If there is a field identifying the source of the contact, we can write a rule that determines the file to use based on the value of the source field. That way, you don't have to merge frequently-appearing values into every contact record you create.



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