The market for data and predictive analytics is growing fast— and for a good reason. According to the Aberdeen Group, companies using predictive analytics enjoyed a 73% higher lift in revenue than companies that do not use this technology (1).

Many credit union executives we work with use data analytics to increase their market share against the competition. They understandably use this member data to focus on gaining new members. Instead of focusing on acquiring new members, we ask, “how can credit unions use data analytics to further engage existing members to improve retention rates?” After all, retaining existing members is often easier and less expensive than onboarding new members.

Enter predictive analytics. Predictive analytics is the use of data, statistical algorithms and machine learning techniques to identify the likelihood of future outcomes based on historical data. The credit union’s goal is to go beyond knowing what has happened to creating predictions of what will happen in the future.

By taking a predictive approach, credit unions can dramatically improve their ability to anticipate member behavior and key life events at an individualized basis. When properly deployed, credit unions can offer the right product at the right time via the right channel, all based on what the data predicts will best motivate the member to act. This enables credit unions to capture the member’s attention and trigger the desired behavior while also increasing loyalty due to marketing messages being relevant and personalized.

How can your credit union use predictive capabilities to provide an appropriate range of services for your members when they experience significant life events? Here are a few considerations as you get started:

Start with segmentation: By tracking and measuring important indicators in a member’s life – age, gender, marital status, income, a move, and more – you can segment members into easily targeted groups. From there, you can develop targeted marketing campaigns that create relevant, personalized experiences that improve engagement.

Analyze spending and behavior patterns: Studying member product usage and targeting the right product is a task. By employing predictive analytics, credit unions can quickly isolate different member segments to create highly individualized and relevant messages tailored to each member’s profile resulting in a higher response rate. This helps credit unions in targeting the right product for the right member. For example, promoting low interest auto loans properly targeted at a person who has shown a trend of purchasing a new car every three to four years will be happy to receive timely and relevant information on auto loans. These messages can be deployed using different marketing channels such as e-mail, call center, direct mail, mobile banking, etc. based on the members preferred marketing channel.

• Leverage Cross Sell/Up Sell Opportunities: An analysis of existing member behavior can lead to efficient cross-sell of products. By mining existing member product and service mix in conjunction with segmentation, credit unions can identify targeted cross-sell and up-sell opportunities. These efforts can drive an increase in member engagement while ensuring your credit union is the member’s primary financial institution.

• Maintain exceptional service: Members expect their credit union to provide top-notch service. Predictive analytics benefit any decision by providing credit union executives with the tools to forecast changes in a member’s life. From member purchasing likelihood to targeted marketing and up-selling to sales and revenue forecasting, there really is no limit to the potential benefits data analytics tools provide. In many competitive markets, if your credit union is able to provide members with the right products and financial services when they need it most, member loyalty, engagement, and retention will soar.

Shifting Your Focus in 2018

Credit unions that can better manage their member interactions while armed with in-depth and customized knowledge about each individual member will have a tremendous advantage to compete in a fast-paced, competitive market. Shifting to a more analytics-oriented culture to better understand and anticipate member needs is not an overnight task.

If your credit union is seeking outsourced talent, advice and best practices as you enter the evolving world of data analytics, call or email the Knowlton Group today. We will provide you with the tools and action plans to accurately analyze and act upon member and product insights so you can respond to your members’ needs faster than the competition.


Sources: 1. Aberdeen Group research group.


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  1. […] patterns that reveal life events such as, retirement, new home purchase, or a baby on the way.  By tracking and measuring important indicators in a member’s life – age, gender, marital status, income, a move, and more – you can segment […]

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