If you work for a credit union and are looking for ideas on how to stem attrition or member loss, then this post is for you. This blog is part eight in Credit Union 2.0’s “Almost 99 Small Data Credit Union hacks” series and is based on the book Credit Union 2.0 – A Guide for Helping Credit Unions Compete in the Digital Age which covers in depth both big and small data for credit unions. There are six types of data that your Credit Union should be aware of:
- Digital Analytics – Desire
- Profitability – Fit
- Wallet Share – Depth
- Transaction – Triggers
- Design Data – Predictive
- Execution – IFTT (if this than that)
Sometimes members give us very subtle clues that they are moving on. Here are a few key actions to be watching for:
| What the member does? | What it means? |
| Reduce bill pay items by more than 25% | Moving over to somewhere else |
| Credit Card activity stops one month | New Credit Card |
| Member stops logging into online banking | No longer the PFI |
| Member doesn’t order new checks | Moving soon and not planning on taking you along |
| Member doesn’t get a new car loan from you and pays off the old | Found a better deal |
| Payroll declines or disappears entirely | Switching accounts |
| Checking account activity declines in volume | Switching accounts |
| Have more to add? Email info@localhost and help us improve this post! |
If you pay attention to the warning signs, you may be able to save the membership and get the member engaged again. Credit Unions spend over $200 for each new member, however most problems are way less expensive to solve for a current member and require a lot less labor.
Want to learn more about how your fellow Credit Union leaders are using data? We invite you to join our Credit Union 2.0 Strategist Group where over one thousand industry leaders comment on new news and trends while sharing and learning from one another.
This is the eigth post in a nine part series. If you can’t wait for next week and want the full “Almost 99 Credit Union Small Data Hacks Guide” click here!
In case you missed it:
Click here for part one of the data analytics series.
Click here for part two of the data analytics series.
Click here for part three of the data analytics series.
Click here for part four of the data analytics series.
Click here for part five of the data analytics series.
