The Challenge:
To better serve their entire member base and deliver low-effort experiences, TwinStar needed a way to capture insights from all service interactions across channels.
Listening to every member
TwinStar is committed to using voice-of-the-member data to understand its members' needs and mindfully serve them. However, its Channel Services leaders realized that between low survey response rates and a traditional QA process of listening to 5-7 agent calls per month, they weren’t getting the complete picture of the member experience.
“What we’ve found is that the people who take surveys either had a really good or bad experience,” says Aaron Mickelson, VP of Digital at TwinStar. “You never hear from the forgotten middle, which is the most important and largest group of your membership base.”
According to Mickelson, the danger of ignoring the “forgotten middle” is that these members will become increasingly dissatisfied over time but won’t tell the credit union via surveys or reviews. As their dissatisfaction builds, they become more likely to churn.
TwinStar implemented conversation intelligence platform Creovai to analyze every member conversation and uncover insights that it couldn’t get from surveys and reviews alone. “Why would I need to ask my members about their experience? They already told me about it in their conversation,” says Mickelson. “Being able to bring those insights forward with Creovai is so powerful.”
Today, TwinStar records every member conversation with Creovai. The insights the credit union uncovers with Creovai allow it to improve its service and member experience as it grows and builds for the future.
Improving agent performance with conversation insights
TwinStar uses Creovai to better understand how agent behavior impacts the member experience–and how Channel Services leaders can empower their agents to deliver the best possible service. For example, Creovai helped the credit union determine that agents using “powerless-to-help” language (e.g., “I’m not able to do that”) was one of the biggest drivers of member dissatisfaction, giving team leaders a new coaching opportunity. Channel Services also used Creovai to investigate the common topics or scenarios that led agents to use powerless-to-help language, ultimately allowing the department to make process changes or provide new resources to help their agents be more successful.
In 2023, TwinStar implemented custom QA scoring with Creovai. Using machine learning, Creovai automatically completes a QA scorecard for every member conversation. This adds more accountability for agents and helps managers customize coaching. TwinStar is already seeing positive results.
“Training agents to use acknowledgment language–expressing empathy–has always been challenging,” says Travis Amburgy, QA Manager at TwinStar. “But within our first month of using custom QA scoring, we saw our agents’ use of acknowledgment language go up 31%.”
The Channel Services department reports that they have also used Creovai to reduce negative agent behaviors. In their first month with custom QA scoring, they saw a 50% reduction in both rep confusion and powerless-to-help language, with these behaviors occurring in less than 4% of calls. “There have been strikes forward in agent performance as we continue to look at the full picture of our member conversations,” says Ian Boyle, Director of the Contact Center.
Optimizing self-service for a low-effort experience
In addition to using Creovai to improve the member experience over the phone, TwinStar uses the conversation intelligence platform to optimize its self-service channels. “Not everyone picks up the phone first to try to troubleshoot an issue,” says Mickelson. By giving members self-service options, TwinStar reduces the likelihood that a member will need to call their contact center. This reduces the contact center’s operational costs and gives members a low-effort experience.
TwinStar also uses conversation data from Creovai to continually improve its chatbot. The credit union isolates its best phone interactions with members and uses this data to train its bot, improving its responses to FAQs and reducing its unsure rate by 75%. “We’re able to pick out the needle in the haystack–the best responses from our best-in-class agents–and bring that forward in our chatbot,” says Mickelson.
Understanding the key drivers of the member experience
Creovai enables TwinStar to keep a pulse on its member experience–both at a high level and in specific interactions. “Two things with Creovai that really blew my mind were the ease of the dashboards and the quick-but-deep dives you can do with just a couple of searches,” says Boyle. The credit union uses Creovai to identify the factors impacting its member experience in near real-time. For example, if call volumes spike, the Channel Services department can uncover the causes in Creovai and quickly address them.
The Channel Services department also uses Creovai to understand how members feel about specific products or announcements. When the credit union announced an upcoming merger, it tracked mentions of the merger and the questions members were asking in Creovai. This allowed the Channel Services department to create FAQs to help members find the information they needed without calling the credit union.
“When you’re listening to a few calls a month, you’re not getting a true picture of member sentiment,” says Tricey Kruger, VP of Channel Services. “Creovai gives us a robust and automated way to gather member insights and share them. We have a holistic look at how our members feel about change.”
As TwinStar grows its member base and optimizes its digital channels, Creovai will continue to arm the credit union with the timely insights it needs to deliver an exceptional member experience.
