When it comes to personalized marketing, whether in print or email, there are two types of data: quantitative and qualitative.
Quantitative data is data that you can put numbers on—household income, ZIP Code, number of children. We often call these demographics. Qualitative data is data that you cannot put numbers on, such as preferences and behavior. We often call these psychographics.
Marketers have become used to using quantitative data to speak more personally and relevantly to customers. Customers in this household income bracket get these offers. Customers in that household income bracket get those. Customers with elementary school age children get information on Product A. Customers with high school age children get information on Product B.
Qualitative data can seem more challenging than quantitative data, but it can be even more rewarding. This is because, while we can make general statements about certain demographic groups, it’s limited. Just because someone is a homeowner doesn’t mean they need roofing services, for example. Conversely, people who receive Trail Runner magazine are likely to be interested in similar types of outdoor running gear even if they have different ages and household incomes.
This is why marketers are increasingly using both quantitative and qualitative data to inform their marketing strategies. For example, a manufacturer of outdoor running gear might start with lists of people who read Trail Runner and similar magazines, then sub-segment offers based on other factors, such as income or geographic region.
So when it comes to creating targeted and personalized direct mail and email campaigns, think in terms of data that can be put into numbers and data that cannot. Then, most importantly, how they go together.
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