DDM - Financial Services

Banks Turn Big Data into Big Revenue

Segment your customers and prospects to optimize your marketing campaigns

Issue link: https://resources.datadrivenmarketing.equifax.com/i/1006136

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Turning Big Data Into Big Revenue Segmentation Tips for Relevant Customer-Centric Marketing use case The term "Big Data" can be an anxiety inducing one for many financial services organizations and it is easy to become overwhelmed with the sheer volume and velocity of data available today. Yet, many would agree that if leveraged well, Big Data can become a substantial competitive advantage. In addition to valuable internal data (ex. client balances, products, demographics, etc.), there are many rich external data sources that can help organizations empower their marketing efforts by creating a more complete picture of their customers and prospects. The key to benefiting from Big Data is to find ways not to drown in it. How Does Big Data Play Into Actionable Segmentation Strategies? One common approach marketing organizations across the Financial Services industry rely on to gather and distill disparate data is segmentation. Many firms segment their existing customer bases as well as the markets in which they do business in some fashion today, but often find it a struggle to do so in a way that will be effective and actionable. Also, they may not know where to start when it comes to combining their own internal data with the vast amounts of rich, well-managed external data to gather actionable insights for better decision making. Here are four tips to help firms get started implementing actionable segmentation strategies for both traditional data sets and Big Data from internal or external sources: 1. Begin with the end in mind. Get agreement on the business goal and then design a segmentation approach around that goal. 2. Build only what can be operationalized. Define the steps for turning segmentation data into insights and then into decisions. Make sure each step is feasible, affordable, and compliant with regulations. 3. Use data that replicates the customer's view, not just your organization's view. For example, a bank needs to look beyond a client's accounts in your organization only and consider the client's total wallet and needs. Share the insights gained from segmentation. Often times, segment definitions can be applied without substantial changes by other core systems and customer-facing personnel.

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