3 Steps to Tracking Data – and Getting Results

So, you’re ready to send out a new direct mail campaign, and wonder how customers will respond. Hold it right there—before you ship your mailers near and far, you need a plan.

 

 

1. Time to experiment

Tracking data is like doing a science experiment. You wouldn’t wait until you were halfway finished to decide what to test. To see how one variable affects another, you’d divide your subjects into groups, changing the “treatment” (in this case, the type of mailing) that each group got.

You’d choose some outcome to measure (like number of responses), and compare these outcomes from one group to the next. Your findings would tell you which treatment worked best, giving you an idea of how to campaign going forward.

What types of variables can you test? You could vary copy, the offer itself (25% off vs. buy-one get-one), color, images used, or whether a mailing is personalized with a recipient’s name. Or you could use two variables, such as copy and offer type, yielding four copy/offer combos. Whatever you decide, make sure your mailing list is divided evenly (and randomly—don’t send all mailers of one type to the same ZIP code) between groups.

2. Crack the code

Once you’ve chosen your variables, you’ll need a foolproof way to determine who received what. If a customer calls to redeem an offer and you don’t know which mailer she got, your back-end work won’t be much good. The solution is simple: add a different code to each mailer version. Simply ask customers to read off the code when they call, or show it when they visit your storefront.

These codes can be as simple as three-digit numbers, or as advanced as QR codes, distinct web URLs and toll-free numbers, or unique usernames and passwords. But remember this, too: your system is only as good as those doing the recording. Make sure your customer-facing employees are on board with the plan. If some team members don’t know to ask customers for their codes, your data will suffer. You could even consider offering incentives for campaign data collected.

3. Assess and adapt

Give customers time to react to your campaign—responses to direct mailings can take months. In the meantime, develop a streamlined way to record your data (Excel spreadsheets work). Once you’ve tallied your results, create a graphic to easily visualize what your data mean. Chances are, you’ll find that one mailer type really did outperform others.

But that doesn’t mean your work is done. Let your findings guide future campaigns. Constantly testing new ideas against the current “winning” mailer allows you to refine over time, better understand your customers’ preferences, and watch your response rates climb.

Need help planning a direct mail experiment of your own? Contact Oregon today to get started. 

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