The importance of credit unions measuring, managing, and acting upon member input cannot be overstated. That’s the only way to fully understand and maximize the member experience, for the benefit of the members themselves and the cooperatives they own.
Machine learning and artificial intelligence (AI) is continually making the available tools for this work more powerful and sophisticated, and it takes a partner focused on this technology to provide the information and resources to leverage member feedback for continuous improvement of the member experience.
Member Loyalty Group was created by six leading credit unions in 2008 to help credit unions understand, evaluate, and act on the core drivers of loyalty. MLG now has a roster of more than 185 cooperatives nationwide who continue to turn to their CUSO to help them grow.
Please provide a brief overview of your products and services.
Michelle Bloedorn: Our comprehensive MX platform gives credit unions 360-degree visibility across all member touchpoints, capturing meaningful information from every interaction. We employ feedback tools that collect member feedback during and after their experience with the credit union, and monitoring tools that collect and analyze detailed information from every digital or contact center interaction.
Our experience solutions include member experience, employee experience, digital experience, speech analytics, and more. We also provide our partner credit unions with customized benchmark reporting on a quarterly basis, as well as best practices to help them quickly ramp up their MX skills and knowledge.
How does AI help credit unions gain insights into member challenges and preferences beyond just surveys?
MB: AI is actively being used to monitor various interaction channels, including apps, websites, phone calls, emails, chats, and social media to gain knowledge about member journeys. By analyzing areas of friction as well as tone, language, and sentiment, these tools provide credit unions with insights into member challenges and preferences not captured by surveys alone.
What are some of the time-saving and high-effort tasks that AI can assist with in member experience management?
MB: Our AI tools create efficiencies and automate laborious, time-consuming tasks. They synthesize large volumes of written member feedback, call transcripts, and reviews into meaningful information that leaders can use to understand and improve member experiences. AI can quickly identify operational issues, points of friction, product feature dissatisfaction, and more. What used to take hours — and a team of analysts — can now be done in real time.
Building on AI-powered text analytics, intelligent alerting also helps identify members at risk of leaving, potential detractors, and others in need of immediate attention. By leveraging a member’s comments along with their score, a more accurate assessment of risk takes shape. This allows MX teams and frontline employees to respond to sensitive matters quickly and tailor follow-up actions.
How can AI help credit unions prioritize areas for improvement in their member experience efforts?
MB: AI helps identify the most actionable areas needing attention, so MX teams know where to focus. Basically, AI facilitates speed to action that wasn’t available before. Some points to consider:
- Themes show what members are talking about, eliminating assumptions and guesswork. Team members can click on emerging themes to get to the root cause quickly and easily, allowing them to address issues in real time and minimize negative impacts.
- AI can summarize the top and bottom issues impacting members, so credit unions confidently know where to prioritize efforts. It can also provide an impact score, showing the effect a particular issue is having on overall scores, either positive or negative.
- Members and employees are the greatest source of ideas to make a credit union better, and AI allows you to automatically discover suggestions and ideas within individual member and employee feedback. Our tools parse experience data for suggestions, ordering them by how actionable they are. Armed with this knowledge, credit unions can test new ideas at a faster pace and consistently improve their overall member experience.
Can you explain how Digital Experience Analytics powered by AI provides insights into online and mobile member journeys?
MB: Digital Experience Analytics (DXA) gives credit unions visibility into the day-to-day performance of their website and app. Credit unions are able to map, score, and see all of the journeys that members are taking across their digital channels, including their third-party vendor pages.
This allows credit union leaders to better evaluate the quality of the experience members are having when interacting with their digital services. The tool scores key aspects of every online and mobile journey including Engagement, Navigation, Frustration, Technical, and Forms. It also captures a wide variety of user behaviors like mouse movements, clicks, hovers and touches, scrolling, device rotations, data input and more.
DXA then applies AI to pinpoint the issues that are most impactful to the member experience. This enables credit unions to quickly identify negative digital journeys and the specific pages or processes that need attention.
What are the key benefits of using Speech Analytics for analyzing contact center conversations with members?
MB: Uncovering the meaningful pieces of information within thousands of contact center calls and chats can be a challenge. Speech Analytics can help identify issues, accelerate improvements, optimize operational efficiency, and improve performance of contact center representatives.
Call transcripts are full of information on the topics members call in about and why. Speech Analytics use AI-powered text analytics to identify trends and patterns within individual calls and across contact center interactions. For example, are members getting stuck during a specific application process? Are cards being declined? Could a self-service tool help with common requests? This data can then be automatically routed to the appropriate team(s) for action.
Beyond text analytics, what other capabilities does Speech Analytics offer to help improve contact center operations and agent performance?
MB: Through real-time analysis, Speech Analytics can also detect the most common reasons for member calls, allowing credit unions to streamline call routing and handle times effectively. They can also receive detailed information on how well their contact centers are operating against key performance indicators, such as first-contact resolution and average handle time, down to the agent level.
For agent performance, Speech Analytics assesses four key attributes throughout conversations with members: talk time, silence, overtalk, and emotion. These attributes, along with the ability to identify strengths and weaknesses via text analytics, allow managers to note areas of needed improvement and provide targeted training and coaching.
Please describe your current work with generative AI solutions and the current and future applications and impact it has on your clients’ credit union operations.
MB: The coming months will be exciting as we introduce new gen AI tools that add to our existing AI capabilities. These new solutions will allow teams to work more efficiently while providing more personalized experiences and deeper analytics.
These tools include an AI “assistant” that can answer questions based on a credit union’s own experience data, and what we call Smart Responses, a tool that will create a personalized response to member feedback. Intelligent summaries will automatically summarize details of an interaction like reasons for contact, issue resolution, and member satisfaction.
Lastly, we’ll introduce Generative Themes. Our existing solutions already incorporate themes, but this will surface even more granular trends, making it easier than ever to uncover what’s happening and respond quickly.
How can my credit union learn more about Member Loyalty Group and your AI-enhanced products and services?
MB: Visit our website at www.memberloyaltygroup.com, submit a contact request, or request a demo to see our programs in action.
— This article originally appeared on CreditUnions.com on April 15, 2024.
