Maximizing growth for your credit union: Harnessing data insights and propensity modeling

In today’s rapidly changing digital landscape, understanding members and delivering tailored offers and products is crucial for credit union growth. With the advent of AI and machine learning, credit unions now have an array of tools at their disposal to help make this possible.

Here’s how credit unions can use analytics and propensity modeling to increase member engagement and grow their business:

1. Understand member behavior. Start by collecting data on member transactions, demographics, and interests. This data is used to create a detailed profile of each member, which helps understand needs and preferences.
2. Identify members who are most likely to be interested in new products or services. Use analytics to identify members who were most likely to be interested in new products or services. This can be done by looking at factors such as past transactions, demographics, and interests.
3. Target marketing campaigns more effectively. Use the information gathered to target marketing campaigns more effectively to the members who are most likely to convert. This can drive a significant increase in sales and growth by increasing opportunities to upsell and cross-sell.

Another opportunity to use analytics to market more effectively to members is to go beyond using data to determine which members have a high likelihood of purchasing a product, but also use it to better understand members themselves. Armed with this information, credit unions can reach members with messages that resonate on a personal level and compel them to act.

Some options for doing this are to develop member personas and segments and create journey maps to market to them based on their life stage and where they are in their relationship with the credit union, as well as influence them along the way.

Research has shown that two-thirds of banking customers today want their financial institution to be more like Amazon or a personal shopper where their needs are known, and they are provided relevant recommendations. To be able to meet these expectations, credit unions must aggregate available data about members and combine it with syndicated sources to understand their broad purchasing behaviors, values, attitudes and motivations. The information must then be leveraged to reach members where they are and in the manner they want to be reached.

Here are some of the benefits of using analytics and propensity modeling to market to members for credit unions:

• Increased member engagement: By understanding member behavior and preferences, credit unions can deliver more personalized and relevant offers and products. This can lead to increased member engagement and loyalty for a credit union, but also helps members on their journey to financial well-being which gets to the heart of the credit union mission.
• Increased sales and growth: By targeting marketing campaigns more effectively, credit unions can increase sales and grow their business.
• Improved member service: By understanding member needs, credit unions can improve their products and services. This can lead to a better customer experience and increased member satisfaction.

If you’re a credit union leader, I encourage you to learn more about analytics and propensity modeling. These tools can help you to grow your business, improve member service, and make better decisions. Additionally, if more credit unions begin data and propensity modeling efforts, the more all credit unions will benefit.