There’s no escaping the increasing reliance on advanced data analytics. Your credit union’s data is a critical asset you have that can anticipate member needs and allow you to execute personalized interactions.

How do you make a data analytics strategy work for you even more in the coming year?What do you need to include in your 2020 initiatives?

How do you plan a strategy that delivers insights that can be turned into tangible business outcomes – insights that help you increase your credit union’s performance and drive greater efficiencies?

Most failed data analytics strategies can be traced back to the fundamental error of focusing solely on the technology and not the credit union’s vision, mission and strategic goals.  As you plan for your 2020 Data Analytics Program, consider these key action plans to ensure a successful data analytics strategy and outcome:

1. Identify organizational strategic priorities and align the technology solution accordingly.
2. Establish a data warehouse to centralize data integrated from several applications.
3. Identify and plan for tangible and measurable use cases.

Business Objectives, Strategy and Technology Alignment:


Too often, executive teams have an unclear strategic direction with regards to their data analytics investments and how they align with their corporate objectives. In these cases, I recommend that the team take a step back and work on clarifying the overall strategic direction and outlook. Without this direction as a guide, the credit union’s technology decisions end up driving the overall strategic direction instead of the strategy driving the technology.

Your data strategy and strategic priorities should include:

  • A strategy defining your how analytics will help drive the credit union’s strategic priorities
  • A tactical roadmap describing how you will accomplish the analytics goals outlined
  • Plans, tactics, and processes to develop analytics skills and create a data-driven culture that embraces the daily use of data analytics

Clearly understand and outline the long-term strategic goals of the credit union (i.e. growth, branching, new products and services, etc.) to identify and select data analytics solutions that fit your requirements both today and, more importantly, where you want to be in the future. Otherwise, you run the risk of a costly blind spot: investing in software that doesn’t fit the credit union’s vision, and the cost of converting later can be significant.

Implement a Data Warehouse:

The foundation for a successful analytics program is data. But, without accurate and quality data, it’s nearly impossible to make informed business decisions. As data becomes an even greater asset for the credit union, the ability to store large amounts of complex data in a unified, central database, known as a data warehouse, is critical.  This single source of truth is the repository for all the data that has been collected and integrated from multiple sources across the organization. Everyone in the credit union is using the same data derived from the same source, which leads to quick, easy access to accurate data and better decision-making.

Measure and Monitor Success:

Tracking and measuring the ROI of an analytics program allows the credit union to re-prioritize goals and take corrective action steps along the way. By measuring the action taken from the data’s prescriptive recommendations, the credit union can focus efforts on the most promising and revenue-driving opportunities, resulting in an immediate boost to earnings and member service and resources. Once key data segments are identified, efforts should be focused on the campaigns that delivered the greatest ROI and devise a set of recurring best practices for future campaigns.

Some tangible and measurable data analytics use cases The Knowlton Group clients have experienced include:

 Effective Marketing and Segmentation:

Deeper, data-driven member insights are critical to tackling challenges like improving member conversion rates, personalizing campaigns to increase revenue, predicting and avoiding member churn, and lowering member acquisition costs. Deploying member segmentation such as geographic, demographic, behavioral and other categories will help your organization target the right products and services and help reduce member churn. Using data analytics, you can successfully segment your members data, and invest more resources into those members who are most likely to respond to your product offerings.  You can then further refine your messaging and product/service offering to retain their loyalty.

 Enhance Member Experience:

Analytics also has the potential to identify the needs of new and existing members, so the credit union can effectively match the best products for them. For example, the credit union can use call center contact information, new member questionnaires and other behavioral attributes to predict what type of products would be the best fit for a new and existing member.  By matching members with the right products and services, the member is less likely to have complaints or start looking for better services elsewhere.

Elevate Efficiency:

Advanced data analytics provides credit unions with intelligence to make better, faster and smarter decisions. This knowledge leads to reducing duplicative systems, manual reconciliation tasks and redundant information technology costs.

 Improve Analysis of Transaction Data:

Your members’ transaction data is a goldmine of information and opportunity.  Deploying transaction categorization and classifications allows for the combining of ACH, Debit Card, and Credit Card transactions into a single view.  You get clean and standardized merchant information to gain the most value out of the data.  And you can identify where your members are spending their money and to which competitors’ payments are being made.  By categorizing member data into tiers, you have the greatest opportunity for deep analysis of transaction behavior.

Refine Member Engagement

Utilizing a member engagement analytics model, the credit union can assign an engagement score to each member based on all member activity.  It will enable you to separate members into defined segments based on their engagement and can create recommended action to take for each segment so you can continuously improve member engagement scores.

 The Right Guidance Leads to Success

Looking for help with developing your data strategy and plan for analytics?  The Knowlton Group is staffed by resources with both extensive technical analytics skills and decades of a line-of-business strategic leadership knowledge.  We work with many credit unions– helping them understand the full impact of data analytics to their business model, define a compelling data analytics strategy and ultimately provide results. From strategy, to conceptualization to full implementation, we are ready to make your credit union a data-driven organization. Contact us today.

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