Designing for Variable Data

Success with VDP campaigns is not guaranteed. You have to design with your results in mind, then track and measure them.

WHY BOTHER with variable data? A lot of sales people hit their customers with lines like: "It always gets a better response than static mail pieces."

Red Alert! Red Alert! Failure is imminent!

Too many printers and designers think that variable data is automatic and a simple process that is going to solve their economic problems. If you do not develop a strong analytical and practical deductive reasoning process for implementing variable data campaigns, you will not be helping your economic problems; you will be intensifying them. The percentage of variable data campaigns that show 0 percent gain or even 0 percent response rates is larger than most people think.

The great variable data campaigns did not typically happen on the first attempt. They evolved and continue to improve as the printer/designer and print customer better understand the end customer's needs and response patterns. The good printers/designers also learn from one campaign how to get to the best solution a bit faster. The key to success is test, test, test. Find out what works and what does not.

Design with Results in Mind

If you are designing a piece that will use variable data in it—regardless of whether it is a printed piece, an e-mail, a PURL (personalized universal resource locator) or a text message—you need to design for the results (i.e. increased sales, reduced acquisition costs, higher levels of customer retention, improved customer loyalty, improved customer satisfaction). So when you design for variable data, make sure that anything you change produces some type of result. There is only one way to know that this is really happening, and that is why you should also design to track and measure the results (we are back to test, test, test).

Many people base the success of their results on a mythical response rate of 2 percent. Somehow, it has gotten out that 2 percent is the average response rate for a typical mail piece, and anything higher than that is considered a success. The Direct Marketing 2010 Statistical Factbook is out, and the new average response rate for cold calling (that is sending a mail piece to someone who is not a customer currently) is now 1.9 percent—but the average response rate for a mailing to existing customers is 16.8 percent.

The important thing to remember here is that these are averages, and if you properly set up a way to measure the results you can know what the response rate would be with or without variable data (the details of that will have to be covered in another article). Response rates are impacted by many customer specific characteristics: the past relationship with the customer, the value proposition for the customer, the offer and call-to-action, the culture variables in the customer base (age, gender, race, political party, pizza topping preferences, parents with kids at home, etc.) and a host of other characteristics.

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