DDM - Financial Services

Segmentation Tips for Credit Unions

Segment your customers and prospects to optimize your marketing campaigns

Issue link: https://resources.datadrivenmarketing.equifax.com/i/1006130

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Turning Big Data Into Big Revenue Segmentation Tips for Relevant Member-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. member balances, products, demographics, etc.), there are many rich external data sources that can help firms empower their marketing efforts by creating a more complete picture of their members 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 members 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 member's view, not just the credit union's view. For example, a credit union needs to look beyond a member's accounts at the credit union and consider the member'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 member-facing personnel.

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