Michigan State University Federal Credit Union’s external virtual agent does the equivalent work of 60 full-time employees.

●      98% resolution rate

●      620% increase in intent library

●      Over 200,000 member conversations

Michigan State University Federal Credit Union (MSUFCU) used boost.ai to implement an internal virtual agent, Gene, as well as a member-facing virtual agent Fran.

Member behavior doesn’t follow the nine-to-five schedule, nor does it consider the capacity of the service team. MSUFCU needed an external agent to increase their responsiveness both inside and outside of standard business hours, while ensuring accuracy in replies.

Upon deployment, they were able to provide 24/7 support for their members, expediting common questions, and providing more relevant responses and services for everyday demand.

MSUFCU's AI trainer team has continued to expand Fran's knowledge and optimize the virtual agent's knowledge, increasing its resolution rate to 98%. This has dramatically improved member experience and allows agents to focus on more nuanced support and service inquiries.

Questions to Determine Fit

Situational Questions:

1. What are the main channels your customers use to contact your support team (e.g., phone, email, chat, social media)?
2. How do you ensure people convert when they visit your website?
3. Are you currently using any AI or machine learning technologies in your customer service operations?
4. What kind of investment is your company making in its larger digital presence?

Pain Questions:

1. Are your customers experiencing long wait times, and do your support agents frequently handle repetitive queries?
2. Do you find managing customer interactions during peak times overwhelming?
3. Are there specific tasks that you wish to automate (e.g., FAQs, booking) to improve efficiency?
4. How do you handle customer support during off-hours or weekends?