Earlier this week, Boeing Employees Credit Union (BECU) and INETCO participated in a webinar hosted by ATM Marketplace titled, “Advice from the Trenches: BECU’s Approach to Customer Analytics” . During the webinar, BECU shared how they are turning transaction “big data” into powerful information about how members are using their ATM channel.
Our audience, made up of predominantly banks and credit unions, also shared some interesting information:
- 41% of the attendees who answered the poll questions are depending on various teams within their organizations to provide customer data. There is little or no direct, on-demand access to information when they need it most.
- 56% are currently prioritizing solutions or data that can help them understand their customers, while
- 38% are trying to gain access to data that helps them make better ATM placement choices.
We spent some time going through the various workbooks BECU is using within the INETCO Analytics customer analytics application. Audience ranking of the six use cases by interest were:
- Transactions by type and status
- Transaction performance analysis
- Customer use by ATM location
- ATM placement analysis
- Outage impact analysis
- On-demand cash inventory analysis
Overall, we were left with an understanding that there is a measurable business impact with real-time transaction monitoring and analytics solutions in internal processes such as:
- Customer analytics – Understand where, when and how your customers interact with your ATM Channel
- Research & troubleshooting – Improve ATM availability and reduce resolution times
- Reporting – Speed up reporting cycles, improve the quality of on-demand reporting
and produce ad hoc queries
We would love to hear how your financial service institution is currently accessing and utilizing rich customer transaction data. To learn more, you can also watch the recorded version of this webinar available on ATMMarketplace. BECU and INETCO will also be at the European ATMs Conference presenting a session, called “Mining ATM Big Data”, on Wednesday, June 17th at 11:30am.