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11:53 AM
Karen Hsu, Datameer
Karen Hsu, Datameer

Tapping Big Data Analytics to Acquire, Engage and Retain Customers

What it takes to fully leverage data for customer acquisition, engagement and retention.

According to a recent McKinsey Global Institute Report, marketing and sales consume about 15% of costs for bank and insurance customers. Recognizing that acquiring each new customer can cost hundreds of dollars, the most competitive financial services providers are turning to big data analytics to drive their customer acquisition, engagement and retention strategies in an effort to optimize their marketing spend.

These companies and their customers are generating massive amounts of data like purchase history, profile data, browsing history, product usage patterns and social media behavior every single day. Used wisely, this explosion in data can be harnessed to personalize marketing efforts tailored to customers' interests, adjust product strategy based off of usage patterns and preemptively predict which customers are likely to leave. To successfully acquire, engage and retain customers, and ultimately gain a competitive advantage with big data analytics, financial services organizations should consider the following strategies:

Acquire: Combine Data Sources for More Targeted Promotions

With increasing access to valuable customer insights, financial institutions have the power to craft customized messages that will win new customers and help maintain a competitive edge.

Not only do organizations have access to traditional sources such as transactional history and profile demographics, but they also have access to public social media behavior. By combining these data sources, financial institutions have the ability to orchestrate more personalized and effective customer acquisition campaigns. For example, if a prospective customer made a number of purchases at Whole Foods and "liked" the Food Network on Facebook, a company could send a credit card with a special promotion related to Whole Foods or the Food Network.

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