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Proving Data Strategies ANALYZING MEMBER GROWTH AND COMPOSITION - PowerPoint PPT Presentation

Proving Data Strategies ANALYZING MEMBER GROWTH AND COMPOSITION Contact us at: ai@cuanswers.com How to count members? Philosophy vs Data Is a member the account or the person/entity? Membership = Account Base Individual = Social


  1. Proving Data Strategies ANALYZING MEMBER GROWTH AND COMPOSITION Contact us at: ai@cuanswers.com

  2. How to count members? Philosophy vs Data – Is a member the account or the person/entity? Membership = Account Base Individual = Social Security/Tax ID Number Primary Individual SSN/TIN = MASTER table Secondary Individual SSN/TIN = SECNAMES table ‘Active’ = No written off loan(s) ‘In Good Standing’ = Criteria varies per credit union and purpose

  3. How to count members? Philosophy must meet data somewhere. Someone has to set a definition or make a call. It’s the data analyst’s job to be aware of the potential philosophies, determine the relevant philosophy, then translate that to the system and practicality of data. CUSO Magazine Article - cusomag.com/2019/11/20/how-many-members- does-my-credit-union-have

  4. How to count members? Know the 2 ways CU*Answers tools count a member. CU*Answers counts members as any membership (account base in MASTER) CU*Answers bills for members as active memberships (subtracts account bases with written off loans) Then… Marketing needs members ‘in good standing’ memberships Eligible to vote for board is often any individual* * Details are typically dictated by bylaws - Primary or joint? Do businesses get one vote per Tax ID number or does each person on the business account get a vote?

  5. Tools - Member Growth & Demographics • 520 Membership Analysis Report / 525 Membership Summary Comparison • 553 New/Closed/All Memberships Dashboard • 752 Relationship Analysis • 508 Member Retention by Age Group / 509 Member Retention by Year Opened • 840Targeted Tiered Score Analysis / 856Tiered Services Comparison • 132 Losing the Love/Mbr Behavior Patterns • 232 Common Bonds for Member Group • Analytics Booth –Trends and Alerts on Member Data

  6. New Members – New / Closed / Net Every month you win some and you lose some. Be wary of focusing too closely on new members. It’s risky to minimize data on memberships lost and how quickly you are losing them! New = Opened a new membership Closed = Closed an existing membership Net = New – Closed

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