Want to knock your 1:1 (personalized) printing campaign out of the park? Do more than personalize the document. Use your data to describe and predict.
The process starts with understanding what your customers look like. Do a basic database analysis. What is their mix of ages, incomes, genders, and races? Where do they live? Then filter this customer information through general demographic and psychographic patterns to predict their behavior. Let’s look at a simplified example.
Say you are an auto dealership and discover that your lease customers fall into three basic categories: young singles, families, and retirees.
Because these are all current customers, you know their ages, incomes and ages of their children (if any) at the time of initial lease. You know their current vehicles and the options selected. This allows you to match appropriate upsells and cross-sells based on the likely needs of each group.
In the young singles category, for example, it would be reasonable to assume that, after five years, they might have higher earning power. At the end of a five-year lease, you might be able to trade them up to the next class of vehicle with more options.
In the families with young children category, you might assume that, after five years, they might have had more children. If they currently lease a sedan, they might need to move into something larger like a minivan or crossover vehicle. Families with older children might need to move into a vehicle with greater towing and storage capacity.
In the retiree category, customers might be looking to downsize. Those with higher levels of disposable income might be looking for sportier cars or luxury vehicles.
In all cases, you know when the customer will act—at the end of the lease period. This information in hand, you can craft marketing campaigns with appropriate messages, offers and incentives.
Your customer base might look different than the one described here, of course, but you can use this process against your own customer mix. Just remember the letters “d” and “p”: describe, then predict.
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