Evaluating Big Data in Your Credit Union

4 Steps to Advancing the Conversation

Why data analytics?

The market is flooded with data that is available to financial institutions to assist them in a variety of areas, including better understanding their members and the products and services they need. Whether you’re in the early stages of understanding what Big Data is and how to assess your credit union’s needs, or you’re an early adopter continually looking for ways to disrupt the competition with innovative marketing strategies, analytics can help your institution understand who your members are, recognize their needs, and deliver relevant solutions. However, sourcing and analyzing the data you need to make strategic marketing decisions can be overwhelming.

1. Assess Your Current Capabilities and Data Structure

The market knows that the use of Big Data isn’t just a nice resource to have –it’s a requirement to keep your organization competitive. However, if you work for a credit union that hasn’t started developing a data strategy, know you’re not alone. Simply taking those first steps in evaluating and assessing your data capabilities and needs is the most important action you can take today.

In order to build a solid foundation in your data roadmap, you should conduct a data audit and consider what role transactional and life cycle data plays in how you identify members who might be in the market for financial products and services.

Assessment Questions to Consider
What’s your biggest challenge today with existing data?

For some institutions, the issue is determining where it’s sourced and stored, while for others it has to do with the quality, purity, and integrity of existing data.

What stakeholders touch data across the enterprise?

Most experts agree that data analytics should not be managed by the IT or Marketing departments. However, IT is an important partner as they may need to coordinate a variety of data sources across a number of departments. Setting up that functionality can be a labor-intensive process depending on how many departments are involved.

What quick wins could help advance your credit union’s data conversation?

Compliance and regulatory concerns are driving a number of reporting requirements. So, how can your institution automate reporting from existing data sources? How much time and money will you save by advancing automation?

2. Define Your Data Needs and Strategy

Whether you’re a newcomer to leveraging data or a seasoned data analytics pro, you understand that your members have increasing expectations when it comes to their financial needs. From your credit union’s footprint, to the solutions that are offered, members want to learn about product offerings through relevant and personalized communication.

Types of Data to Consider

Another consideration in building out your data roadmap is what type of data sources you’ll need to access on member categories you want to grow. For instance, if your institution’s goal is to add more Millennials to your member base, consider:

  • The types of data you’ll need.
  • Whether you can access the right data categories in-house, or if you will need to source them externally.
  • How to access identified data categories efficiently.

For example, transactional data can help close the gap you may face when it comes to cross-selling your members into solutions that make sense for them. However, by combining that transactional data with life-cycle data from external sources, you can paint a more powerful picture of your members and give you valuable insight into the broader perspective of a member’s financial lifestyle.

3. Build and Promote Your Case for Data Analytics

Once your institution’s strategy is set, your next step is to determine how you can leverage that strategy into a data analytics action plan. For instance, if you want to grow your institution’s footprint, you’ll need to understand that community’s demographic factors. Then you can ask questions like, how many of these households respond to advertising, and what types are most impactful to use when crafting your institution’s message?

Questions to Assess Gaps

You may build a credit union case for leveraging data or reinforce the value of your data analytics, only to realize you have some gaps.

Ask yourself these questions:

  1. Do you need additional data sources that you currently don’t have access to?
  2. What data could be appended to transactional data to create a more complete picture?

4. Implement Your Strategy and Plan

The next step is to take a broad, management-level perspective of data and the data analytics action plan, and combine those into an implementation strategy. That implementation strategy should then create a steady and powerful trickle down of member data to a branch level, providing the relevant analytics to help drive your institution forward on a daily basis.

All About Crafting the Right Message

Delivering the right solution, to the right member, at the right time, through the right channel, doesn’t happen by accident. Instead, it takes an understanding of your membership base and the products that will resonate with them, so you can focus on solutions that have the highest appeal, based on your internal transactional and lifestyle data. When that is combined with external data analytics, you should have the tools to tell a more influential story about your members and the types of product development needed to keep you relevant in the community. Crafting and delivering a simplified marketing message can help members make faster decisions, which will enable you to dive into available member-level reporting to help you craft a more meaningful story that resonates.

How do you start?

If your goal is to create a simplified marketing message that converts members into buyers, and eventually buyers into advocates, one strong recommendation is to seek outside assistance. Competition when hiring a data scientist is stiff and can be cost-prohibitive. Estimates show that when many credit unions develop and maintain a true data warehouse, it will cost them about $2 million over 4 years.* Instead, you can partner with established external data providers to help your institution focus on the right data sets to drive the right activities at your institution.