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Predictive Analytics: Personalized Marketing in the Financial Sector

by: SilverTech

The financial industry has welcomed predictive analytics into the broader marketing and sales strategies with a number of recent cases in retail banking that have demonstrated promising success rates. However, the benefits of using big data in the communication touch points of the entire customer lifecycle aren’t just on the side of the financial organizations. The customers can also benefit from being served information more efficiently and accurately according to their requirements, which can’t be overstated given the wide variety of products and services offered by financial organizations.

From a strategic perspective, behavioral data and predictive analytics are two areas in the world of big data that can have and are having positive impacts on the way financial institutions communicate with their customers. The key to success in these cases is the implementation of a strong tech foundation, which at the very least is a well-managed Customer Relationship Management (CRM) platform, such as Salesforce, and a highly utilized marketing automation platform, such as Pardot or HubSpot. Together, these systems collect and manage the baseline of customer data necessary for diving into predictive analytics.

Predictive Analytics First Tennessee Bank

Using a predictive analytics software solution from IBM, First Bank Tennessee has been able to use predictive customer insights based upon data around buying behavior, web activity and social media presence, to inform and optimize the bank’s marketing strategy. Using this data to inform marketing strategy has resulted in an impressive 600% ROI, due in part to a more efficient allocation of marketing resources and an associated 20% reduction in marketing costs. The bank’s marketing campaigns also achieved a 3.1% increase in response rates through more accurately targeted offers within high-value customer segments.

Using Behavioral Data at US Bank

US Bank, with the help of Adobe Marketing Cloud, has also demonstrated a successful strategic use of customer behavioral data to produce predictive, personalized campaigns aimed at greater engagement and conversion performance. Based upon a deeper understanding of the interactions between their customers’ online and offline behavior, they have been able to further segment their audiences in real time to produce highly targeted, personalized marketing campaigns. This behavioral data has also been integrated into its Salesforce CRM platform too, which is helping inbound and outbound call center teams to personalize the experience of their callers. This resulted in significant increases in campaign lead conversion rates of 100% when compared with the traditional approaches of their previous marketing campaigns.

The Road to Data Backed, Personalized Marketing Strategies

Getting to a point where financial institutions can start utilizing predictive analytics tools first requires evaluating existing technologies. Choosing the right CRM system and marketing automation software is an important step in realizing this.

CRMs and Marketing Automation tools both contain data on each online and offline communication point with a prospect/customer, in addition to information on their purchasing behaviors. In short, they should collect data on the entire lifecycle of customers and prospects if managed correctly. While it’s easy to view each platform as an endless vortex of lead and customer data, incorporating a predictive analytics tool into the mix suddenly opens the door to recognizing patterns in this data. This data enables businesses to realize another foundation for successful personalized marketing strategies – the development and refinement of buyer personas. Knowing what customers look like, what motivates them, and what influences their decisions, is essential to better segmentation and personalization of marketing and sales communications.

US Bank and First Tennessee Bank are both good examples of how innovative, creative players in the financial sector are being empowered by predictive analytics. All that is needed to get started are the right platforms and a good baseline of customer intelligence. If you need help with your marketing and sales strategies, contact us today.


US Bank and Adobe Marketing Cloud Case Study

First Tennessee Bank and IBM Case Study