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Are you missing the data modeling boat?

May 19th, 2014 · Postal

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Learn how regression modeling could be a good fit for your direct mail program by recognizing these common list woes and understanding their possible modeling solutions.

If you’re like many direct marketers, there will come a time when you feel like you’ve exhausted all the traditional strategies of acquiring new customers through the mail. You’ve taken straight selects off of every file, big and small, that seem to make sense (and even some on those that don’t). But no matter what you try, you simply aren’t finding the volume of customers you want, within a CPA you can afford.

If you find yourself in this position, and one of the scenarios below sounds familiar, then it might be time for you to consider building an acquisition model.

4 List Scenarios Modeling May Help Solve:

1)  List Fatigue
List A has been a staple of your program for a number of years. With each passing campaign, the list results have begun to slip. You’ve begun questioning whether List A will still make it into upcoming mail plans. A regression model may help weed out names that are less likely to respond, thus allowing you to keep List A in the marketing mix.

2)  Too Large a Universe
List B has an enormous universe in excess of 5MM names. Finding a straight select that works may take time and prove costly. If List B also offers regression modeling, you may be able to use it to your advantage to mine for names that are most likely to respond to your mailing.

3)  Too Small a Universe
You are having success taking names off of List C using straight selects. If List C offers regression modeling, you may be able to find quality prospect names that fall outside of those straight selects that will increase your mailable universe. By taking more names from a single list, you can probably negotiate better pricing.

4)  The Need to Grow
Your organization is looking to expand its program. Through regression modeling you can mail “large, out of category” files. The model will define prospects on these files that are most likely to engage with your offer.

Modeling techniques have improved greatly over the last 15 years. Larger amounts of more quality data are now being gathered and added to files, which only enhances the ability of the models to select better prospects to be mailed.  If you are interested in modeling, rely on your list broker for advice on how best to move forward.

For a more in-depth look at postal modeling, read our whitepaper, “What to Know Before You Model: The 4 Most Commonly Used Models For Acquisition