Credit Union Data Analytics: Who are your best members? :)

Our “A” members are the ones who know the difference between a credit union and a bank, believe it, feel it, and espouse it. They bring us all of their financial services business and tell all their friends. If you are interested in what their data tells you about them then this post in Credit Union 2.0’s “Almost 99 Small Data Credit Union Hacks” series will be helpful.

This blog is the ninth and final part 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:

  1. Digital Analytics – Desire
  2. Profitability – Fit
  3. Wallet Share – Depth
  4. Transaction – Triggers
  5. Design Data – Predictive
  6. Execution – IFTT (if this than that)

The key here is patterns. Once you sniff out the predictive behavior, you can be proactive with how you interact with the member.

Here are some ideas on where to look for your “A” member patterns:

Data What to do with it?
Favorite Grocery Store Special promotion with that store
Favorite Vehicle Special promotion with the local auto dealer
Favorite Coffee Shop Hang out there too – send them a cup on you!
Favorite Online Retailer Special Promotion
Favorite Local Small Merchant Hang out there too
Favorite Gym Special Credit Union deal
Who They Follow on Facebook Could this be a potential guest blogger on your site? Maybe there is an opportunity for you to update your content to be more relevant.
Where They Work Follow their leadership online
When They go to Branches Better service hours
Who Their Favorite Tellers/Call Center Reps Are Understand why
What Life Stage They are at What is next for them and how can you help?

 

Knowing your “A” members inside and out and further tailoring your services will help those members bring their friends. You want your “A” members fiercely loyal and believing in the credit union difference. Show those members the difference every day and hang out with them and their friends.

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 final post in a nine part series. If you 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.

Click here for part six of the data analytics series. 

Click here for part seven of the data analytics series. 

Click here for part eight of the data analytics series. 

Credit Union Data Analytics: Who are your best members?

Our “A” members are the ones who know the difference between a credit union and a bank, believe it, feel it, and espouse it. They bring us all of their financial services business and tell all their friends. If you are interested in what credit union data analytics tells you about them then this post in Credit Union 2.0’s “Almost 99 Small Data Credit Union Hacks” series will be helpful.

This blog is the ninth and final part 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:

  1. Digital Analytics – Desire
  2. Profitability – Fit
  3. Wallet Share – Depth
  4. Transaction – Triggers
  5. Design Data – Predictive
  6. Execution – IFTT (if this than that)

The key here is patterns. Once you sniff out the predictive behavior, you can be proactive with how you interact with the member.

Here are some ideas on where to look for your “A” member patterns:

Credit Union Data Analytics Patterns

Data What to do with it?
Favorite Grocery Store Special promotion with that store
Favorite Vehicle Special promotion with the local auto dealer
Favorite Coffee Shop Hang out there too – send them a cup on you!
Favorite Online Retailer Special Promotion
Favorite Local Small Merchant Hang out there too
Favorite Gym Special Credit Union deal
Who They Follow on Facebook Could this be a potential guest blogger on your site? Maybe there is an opportunity for you to update your content to be more relevant.
Where They Work Follow their leadership online
When They go to Branches Better service hours
Who Their Favorite Tellers/Call Center Reps Are Understand why
What Life Stage They are at What is next for them and how can you help?

 Credit Union Data Analytics: A Members

Knowing your “A” members inside and out and further tailoring your services will help those members bring their friends. You want your “A” members fiercely loyal and believing in the credit union difference. Show those members the difference every day and hang out with them and their friends.

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 final 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.

Click here for part six of the data analytics series. 

Click here for part seven of the data analytics series. 

Click here for part eight of the data analytics series. 

Credit Union Data Analytics: Wallet Share

We only have a couple of posts left – but don’t fret – we have saved some of our best content for the end of our Almost 99 Small Data Hacks for Credit Unions – Guide series. Today, we are covering how to gain wallet share for your credit union from data analytics. Who doesn’t want that?

Credit Union 2.0 – A Guide for Helping Credit Unions Compete in the Digital Age 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:

  1. Digital Analytics – Desire
  2. Profitability – Fit
  3. Wallet Share – Depth
  4. Transaction – Triggers
  5. Design Data – Predictive
  6. Execution – IFTT (if this than that)

This is a fun list with lots of innovative ways to trigger marketing campaigns once you have your marketing automation and content marketing in place.

Idea Data Action
Big Deposit Grooming Watch for unusually large deposits ($25k+) Develop a content campaign on key strategies to deal with new money. The strategy should be 5 to 10 blogs long and drive for a Call To Action (CTA) to download the guide. Once you see the deposit, start emailing the member weekly with one blog each week on the topic.
Loan Renewal 24 month Auto Loan Triggers a new content campaign on educational topics such as: maintenance requirements for older cars, when to trade your car in, how to determine your cars trade in value, etc.  Have 5 to 10 blogs targeting the goal of educating the member and renewing the loan!
Address Change When a member changes address Trigger an offer to order new checks
Venmo Usage Watch for the first Venmo usage Trigger a campaign on pros and cons of Venmo. Alternatives to Venmo.  Etc.
PayPal Usage Watch for the first PayPal usage Trigger a campaign on these various topics: pros and cons of PayPal, PayPal security vs. Credit Union Security, and the difference between PayPal and a credit union.
Bitcoin Usage Watch for the first Bitcoin usage Trigger a campaign on pros and cons of Bitcoin.  Educational piece on Bitcoin and how it works.
Low Balance Savings/Checking Low Balance Offer a skip a pay option that month for a fee and donate a portion to a local charity.
Pricing Auto price loans .25 points higher On the third consecutive good payment, send an email thanking the member and auto reduce the payment .25%.  This is a great built in surprise!
Rewards Monitor reward tiers on debit/credit Auto trigger outbound emails when the member hits new rewards tiers and options.
Tax Refunds When a one-time tax refund is deposited Trigger outbound content on key strategies for tax refunds, i.e. the impact of saving your tax refunds, what would your tax refund be worth if you saved it for thirty years at a credit union, etc.
Local Merchants Top usage and dollars locally Look at your members local purchase habits.  Create unique rewards where they already shop at local businesses.

a.       Ford – free car wash

b.       Coffee Shop – free cup of coffee

c.       Flower store – coupon

d.       Dry Cleaner – coupon

e.       Theatre (movie or otherwise) – free popcorn

f.        Kids Gym or activity – coupon for a class or session

g.       Home decoration store – special offer

h.       Home improvement store – coupon

i.         Gas Station – a fill up on us

j.         Grocery store – special offer

 

ATM Set the preference ·       Language

·       No Receipt

·       Last Deposit

·       Last Withdrawal

Credit Card Offer timing Other bank credit card payment date Most members pay their credit cards within the same 3 to 5 day window each month. Time credit card switch and educational content to when payments are due for each member.
Credit Card Purchase Subscription Data Members who aren’t using the credit union’s credit card should be offered an incentive to move recurring payments over.
Joint Member Added Look up wedding registry Send a congratulations gift or item from their registry. Follow-up with credit union guide to budgeting for newlyweds etc. It might also be a time where the couple begins looking for a house.
DMV Charge Watch for a local DMV payment Trigger information on how to change your address or other life stage events.

We are getting down to the end of the “Almost 99 Small Data Credit Union hacks” guide. The next two posts will be on “how to tell a member is leaving” and “how to get more “A” members” so stay tuned!

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 seventh post in a 9 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.

Click here for part six of the data analytics series. 

 

Credit Union Data Analytics: Risk Awareness

As we continue the Credit Union 2.0 “Almost 99 Small Data Hacks for Credit Unions – guide” series, today we are covering risk items for internal consumption only. While many of our hacks are targeted at proactive marketing, these hacks are key insights you can gather internally from your member data.

This is the fifth post in a 9 part series. If you can’t wait for next week and want the full “Almost 99 Credit Union Small Data Hacks Guide” click here!

Credit Union 2.0 – A Guide for Helping Credit Unions Compete in the Digital Age 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:

  1. Digital Analytics – Desire
  2. Profitability – Fit
  3. Wallet Share – Depth
  4. Transaction – Triggers
  5. Design Data – Predictive
  6. Execution – IFTT (if this than that)

This list is by no means comprehensive and Credit Union 2.0 does not offer any compliance advice for any state or federal laws on the impact of using this information.

Risk Analytic Where to find it? Potential Conclusions
Minimum Payments Credit Card Data If you see members reducing their payments over time on their credit card payments, this may indicate an increased risk of default or challenging cash flow situation for your member.
Member locks themselves out Online Banking Proactively reach out if the member locks themselves out. Call their phone on record, don’t just wait for the member to call in. A frustrated member will appreciate this.
Duplicate Addresses Monthly Report of more than one member with the same address Could indicate a stolen identity
Duplicate SSNs Monthly Report of more than one member with the same SSN Could indicate a stolen identity
Duplicate Driver’s License Monthly Report of more than one member with same Driver’s License Could indicate a stolen identity
Delinquent Loans by Indirect Lender Loan System Could indicate an indirect auto dealer encouraging members to lie about income
Loans without payments Monthly report of loans with new payments Possible indication of fraudulent loans
Loans with payments made at the teller line Loan payments by teller/channel Possible indication of fraudulent activity
Loan types and dollar consistencies by MSR Loan applications by channel and person Possible indication of fraudulent activity

 

Have an idea or risk related data algorithm? Submit it to the Credit Union 2.0 team today by emailing us at info@cu-2.com and help us improve this post!

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 fifth post in a 9 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.

Predictive Analytics for Credit Union: Member Limits

In the first several posts in this series, we covered key insights that can be gathered from address changes, payroll changes, and fees as part of our “Almost 99 Small Data Hacks for Credit Unions” series. Next up, we will dive into credit union services and limits that can sometimes negatively impact your relationship with a member.

This is the fourth post in a 9 part series. If you can’t wait for next week and want the full guide “Almost 99 Credit Union Small Data Hacks Guide” click here!

Credit Union 2.0 – A Guide for Helping Credit Unions Compete in the Digital Age 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:

  1. Digital Analytics – Desire
  2. Profitability – Fit
  3. Wallet Share – Depth
  4. Transaction – Triggers
  5. Design Data – Predictive
  6. Execution – IFTT (if this than that)

Most credit unions have several potentially confusing service limits and fees. Exposing some of these can cause undue fraud and sometimes even compliance risk. Consequently, credit unions may want to leverage this data behind the scenes and highly personalized it so as not to broadcast key risks or vulnerabilities to the world.

We explore several of these below.

Service or Limits What could happen? What should you do?
Remote Deposit Capture Setting a low limit universally will frustrate your top members. Design a multi-tiered profile based on key risk data and ensure that you give your best members higher limits.

 

When a member hits a limit, trigger an outbound email explaining how the limit was set and what they can do to change it.

ATM Limits Member is forced to make multiple trips to the ATM to get their business done…frustrating. If you see a member make the same size transaction multiple days in a row, send them a guide on how to request an increase and the pros and cons of doing so.
Change of Address You change it one account, but in a different system you forgot to update. Make a checklist of all of the locations you store addresses and make sure you clean them up everywhere at once.
Check holds Member forgets a hold came off. Ask members if they want to know when holds expire in an email. Offer them a one-click enroll in this option and then send them an email if a hold is removed.
No retirement savings Member struggles to retire Offer easy savings strategy series to members. Provide weekly tips or ideas to help your members save.
Fraudulent ACH Member is confused If a member reports fraud, trigger an outbound email that links back to an overview of how the credit union will help them troubleshoot and resolve the fraud. Update the member at agreed upon times during the investigation/resolution of the issue.
Fraudulent Check Member is confused If a member reports fraud, trigger an outbound email that links back to an overview of how the credit union will help them troubleshoot and resolve the fraud. Update the member at agreed upon times during the investigation/resolution of the issue.
Fraudulent Credit/Debit Member is confused If a member reports fraud, trigger an outbound email that links back to an overview of how the credit union will help them troubleshoot and resolve the fraud. Update the member at agreed upon times during the investigation/resolution of the issue.
Declined Transaction Member is confused and/or annoyed Have guides and information outlined on when and how transactions are declined. Include key troubleshooting strategies to resolve the issue for legitimate transactions. When the decline happens, send an outbound email to the member with a link to the guide.

As in our earlier post on turning negative fees into more positive experience, service limits are a similar opportunity. Anytime your credit union can change confusing non-transparent service items into positive transparent items, you build trust and loyalty from members.

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 fourth post in a 9 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.