Maximising results with data-driven financial marketing strategies

Tony Rizzo
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Tony Rizzo: Marquis, USA

Journal of Brand Strategy, 2015, vol. 4, issue 2, 114-126

Abstract: The amount of financial and non-financial data collected by banks provides a wealth of knowledge into consumers’ buying habits and preferences. A bank supports the ability to finance and to make payments and gives customers a secure haven from which to conduct their financial lives. The ability to turn such data into actionable communication is what sets any financial institution's brand apart from its competitors. Any financial institution has three business development goals: (1) to increase volume at the point of sale; (2) to increase purchase frequency; and (3) to increase new customers. A bank's ability to gather financial data from both a transactional and behavioural perspective, combined with its ability to convey trust, gives it a competitive advantage. This collection of information can provide the firm with behavioural insight leading to improved service and enhanced products, and can provide real-time analytics for marketing execution. The ability to reach current customers is cluttered and complicated. In order to match the right offer to the right customer, various segmentation methods (geographic, demographic, psychographic or behavioural) can be executed. Brand trust is the willingness to believe in a brand based on personal beliefs in spite of the risk or uncertainty connected with that brand. Ultimately, a financial institution wants customers to demonstrate support for the firm by making purchases, providing positive referrals and opposing rival brands. Armed with this knowledge, the firm can create multi-channel messages, which are relevant, specific and timely. These messages must contain content that demonstrates knowledge of the customer in such a fashion that he or she elevates the bank to become one of the customer's most valuable and trusted brands.

Keywords: segmentation; personalisation; financial marketing; data analytics (search for similar items in EconPapers)
JEL-codes: M3 (search for similar items in EconPapers)
Date: 2015
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