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Technique #2 for Increasing Loan Balances: Targeted Prospects Get Results

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The added benefit of using data append and modeling to refine the audience within your customer base is that the same model can be used to refine a prospect universe. It is good practice to utilize the same data source as the original data append to rent the prospect list, ensuring the quality of the data is the same as the data the model was built upon. This will not be an issue if you outsource the modeling and the data append to the same company. If you build the model in house, you can either use a profile of the ideal audience to order the list or get a much larger list of prospects in the area and run the model to narrow the list. Just make sure the list provider allows for a “net record” arrangement so you don’t have to pay for records you won’t use.

If you have not created a profile model for your existing customers and do not want to go through the expense of creating a custom model, many of the reputable list providers have “off the shelf” models. Sometimes called propensity or intent models, there are many data companies that create them (or source them) from data sets with millions of records. Since there may be nuances in the type of customer your institution brings in, these models will not be as robust as using your actual customer data. However, they are still fairly predictive and much better than using a basic demographic profile.