Harnessing the Power of Data-Driven Marketing...

The observations you can collect about your members extend well beyond just a single service or product. Data analytics can be used to identify the account holders who are most likely to also acquire lending products like auto loans or home mortgages, and suggest offerings before that customer makes a big purchase decision.

Take auto loans for example. We can anticipate who would be a candidate for an auto loan program by examining their similarities to other customers that were already approved for auto loans. We use an algorithmic technique called “collaborative filtering,” it analyzes data based on principles of “similarity,” “nearness” and “neighborhoods.” We utilize two notions of similarity:

• User-based similarity, which defines nearness among users

• Item-based similarity, which defines nearness among products

Individuals are considered “similar” if they purchase many of the same products, while two products are considered to be correlative if consumers tend to purchase them together.

The data analytics platform might yield several observations about auto loan purchasers, such as:

• 4.9% of those at the financial institution

• have multiple auto loans

• 10.8% of those with mortgages have multiple auto loans

• Those with mortgages are 2x likely to purchase multiple auto loans

The high correlation between mortgages and multiple auto loans indicates a similarity between the two products, you can identify individual users who would statistically be more receptive to targeted marketing messages promoting car loans.