The Dangers of Misidentifying Your Best Members

The Complexity of Relationships, Channel use & Profitability can Distort True Value

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Every Credit Union feels they understand their best members. But, in truth, your best members are often the most difficult to understand.

High-value members often have several products, use different channels over longer periods of time and, as a result, their data is messier and harder to accurately unify. Members who do not drive such strong performance often have one or maybe two products, and they don’t use as many channels. Therefore their data is simpler - but they don’t make as much of an impact on the success of the credit union, including the bottom line.

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Siloed systems without unity around a member make it extremely difficult to understand who these superstar members are - which are indeed different for each credit union.

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When Credit Unions misidentify or overlook their actual best members, they fail to value them correctly, and lack good insight into their behaviors and preferences. As a result, brands are unable to connect with them in a way that feels tailored and authentic (see “The personalization of data builds brand loyalty and profit”). A variety of ways to gear the organization to attract and serve them better - from product development, to branch network, to daily marketing efforts - will fall short of their potential. Or worse, will be misdirected toward initiatives that distract or undercut this strategic priority.

Siloed systems without unity around a member make it extremely difficult to understand who these superstar members are - which are indeed different for each credit union. CRM systems had been promising to help solve this issue for years, but have continually struggled to live up to this ideal. MCIF systems, although extremely helpful, have not taken advantage of newer technologies. In fact, an average credit union has over 30 systems they currently use, many of which do not talk to each other seamlessly.

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Even the best data warehouses themselves do not drive ROI without power users who are engaged and actively using them well.

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What Credit Unions need is results, and the process to get there requires a data warehouse. To answer this call, many IT departments have invested significant money and time developing data warehouses - an exceptionally difficult challenge to do well in-house. This approach often takes twice the amount of time and twice the amount of money as originally planned. But even the best data warehouses themselves do not drive ROI without power users who are engaged and actively using them well.  

Harnessing next-gen data and managing successfully through the data transformation needed has frustrated many financial institutions, big and small. As credit union leaders decide between building and outsourcing their analytics, Dave Doss, the former CEO of OneAZ Credit Union in Phoenix, offers this recommendation based on his own multi-year data journey:

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“I would seek an outsourcing option that is built and fully operational. This significantly reduces risk and allows organizations to employ and realize benefits more expeditiously. This route also reduces the opportunity costs related to what other strategies or strategic initiatives suffer while tackling this complex project.”

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Credit unions are sitting on a treasure trove of information, which can also be enriched by appending second and third-party data to better understand their own membership (see Lifestyle Segmentation & Personas). It’s a remarkable opportunity for insight to help the organization unify its own message, create personalized offers for members, and to focus and align the entire organization around what’s best for its membership. The ability to personalize the member experience through great data not only helps the organization deepen relationships and drive organizational performance, but it ultimately helps members make important progress in their financial health - which is at the heart of every credit union’s mission.

To get there, credit union’s will need to continue to focus growth around their own unique best members. And the only way to identify them and attract more of them is to have the data in place and in use.

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