Meeting Changing Member Expectations with Data Insights

Meeting changing member expectations with data insights

Evolution of Member Expectations: Lessons from The Past

As the financial landscape evolves, credit unions must continuously adapt to meet changing member expectations. The financial services industry has undergone significant transformations in response to changing member needs:

  • The online banking revolution: The shift from branch-only banking to online platforms in the early 2000s was a pivotal moment. Members’ demand for convenience drove widespread adoption of online account management.
  • Rise of mobile banking apps: The introduction of mobile apps further raised the bar for accessibility. Members embraced the ability to check balances, transfer funds and pay bills from their smartphones, prompting credit unions to prioritize mobile-first strategies.
  • 24/7 service expectations: The rise of AI-powered chatbots and virtual assistants addressed members’ need for around-the-clock support, proving that adaptability to innovative technology can significantly enhance service quality.

These milestones highlight the speed at which member expectations evolve and the importance of agility in responding to them.

Understanding Changing Member Expectations

Understanding past trends can help credit unions to anticipate future demands and maintain strong member relationships. Today’s credit union members continue to expect increased convenience, value and innovation, such as:

  1. Personalization: Members want financial advice and product offerings tailored to their life stages, goals and preferences. A one-size-fits-all approach no longer resonates.
  2. Integrated experience: Seamless, intuitive banking experiences across channels are non-negotiable. From mobile apps, online banking, physical branches and call centers, members demand convenience and satisfaction.
  3. Proactive engagement: Members value institutions that anticipate their needs. For instance, credit unions can demonstrate foresight and care by suggesting debt consolidation options before financial strain becomes a concern.

The Role of Data in Meeting Member Expectations

Data is the cornerstone of understanding and meeting these evolving demands. Here’s how credit unions can harness it effectively:

  1. Data analytics tools: These tools allow credit unions to analyze member behavior and preferences. For example, mining payment transactional data can reveal spending habits, enabling institutions to create a digital member profile that can dramatically improve the relevancy of recommended financial products or services.
  2. Dashboards for real-time insights: Interactive dashboards provide credit unions with a comprehensive view of their members’ activities. By monitoring trends and anomalies, credit unions can quickly identify opportunities and address potential issues.
  3. Predictive analytics: Predictive models use historical data, machine learning algorithms and generative AI capabilities and play a key role in helping the financial institution to identify macro and micro trends that not only forecast future member behaviors but also create personalized offers to each member. With such advanced data analytics tools, credit unions can anticipate needs such as upcoming loan applications or savings goals and create a personalized message increasing the campaign success rate.
  4. Behavioral segmentation: Data allows credit unions to segment members based on their behaviors, preferences and financial goals. This segmentation can be used to deliver highly personalized product recommendations, such as specific savings plans for young professionals or retirement solutions for older members. By grouping members with similar behaviors, credit unions can design targeted campaigns that resonate more effectively with each segment.
  5. Marketing automation: Automation tools use data to send relevant offers to members at the most opportune times. For example, a member nearing the end of a car loan term might receive an automated message offering competitive refinancing options. These timely, data-driven communications not only improve engagement but also enhance the member experience by providing solutions when they’re most needed.
  6. Member feedback analysis: Surveys, reviews and other feedback channels provide invaluable insights into member satisfaction and pain points. Analyzing this feedback through data tools enables credit unions to identify areas for improvement and prioritize changes. For instance, if multiple members highlight issues with mobile app functionality, the credit union can act promptly to enhance the user experience, ensuring member concerns are addressed effectively.

Roadmap for Implementation

Implementing a data-driven strategy requires a structured approach to ensure success, but it’s important to remember that this is a journey, not a one-time project. Organizations don’t need to implement everything at once—small, incremental steps can still yield significant benefits over time. By following a clear roadmap, credit unions can harness the power of data to meet evolving member expectations and drive organizational growth. The following steps outline a framework for effective implementation.

  1. Audit your data: Assess current data and systems to identify gaps and opportunities. Determine data accuracy, completeness and relevance to member needs and organizational goals.
  2. Set clear goals: Align data strategy with member expectations and business objectives. Define key performance indicators (KPIs) and success metrics to measure progress effectively.
  3. Invest in tools: Implement dashboards, CRMs and analytics platforms to centralize data management and improve accessibility. Ensure tools integrate with existing systems and support data-driven decision-making.
  4. Build skills: Train teams in data-driven decision-making by providing workshops, certifications and hands-on training. Develop a culture where data literacy is prioritized across all departments.
  5. Monitor & optimize: Continuously improve using feedback and data insights. Establish regular review cycles to assess data performance and adjust strategies and tools as needed.

Data Success Stories

Several credit unions have been highly successful in leveraging data to exceed member expectations. For example, Michigan Schools and Government Credit Union (MSGCU) partnered with a leading data analytics provider to identify those who qualified and provided a credit line increase to almost 30,000 members. The goal of the credit line increase program was a lift in balances of $10 million. The result 90 days after the program implementation was a lift of more than $21 million, demonstrating the members’ need for additional credit. Using data analytics, MSGCU proactively provided for their members while increasing their credit card balances—a win–win.

Another example of how credit unions can successfully use data to meet members’ needs and improve their business performance was demonstrated by MSU Federal Credit Union (MSUFCU). To boost its liquidity ratio, MSUFCU launched a targeted campaign promoting share certificates. By leveraging a next best product AI predictive model, they identified members most likely to invest. The campaign delivered outstanding results: $7.4M in new liquidity from 160 new certificates, far surpassing the $0.6M and 53 certificates achieved through a traditional marketing approach.

A Foundation for The Future

The only constant in the financial services industry is change. Building a solid foundation of data is essential to ensure credit unions remain agile and prepared to adapt. By investing in data infrastructure and fostering a culture of continuous learning and improvement, credit unions can position themselves to not only react to change but to lead it. This proactive approach ensures they are always ready to deliver exceptional value to their members, no matter what the future holds.

By integrating data into their strategic operations, credit unions can not only meet but exceed the evolving expectations of their members. Credit unions that actively listen to their members and leverage data-driven insights will be best positioned to thrive in the evolving financial landscape.

Key Takeaways

Embrace data-driven decision-making: Data-driven decision-making involves more than just collecting data; it requires a comprehensive strategy to analyze and act upon it. By utilizing tools such as data analytics platforms and predictive models, credit unions can identify trends, forecast member needs and tailor their services accordingly. For example, understanding spending patterns can enable proactive outreach for financial planning or personalized loan recommendations, ensuring members feel valued and understood.

Enhance omnichannel member experiences: In today’s demanding environment, convenience and consistency are paramount. Credit unions can use data to refine their platforms, ensuring that every interaction is smooth, efficient and intuitive, regardless of the delivery channel. This could involve optimizing mobile banking apps for user-friendly navigation, integrating AI-powered chatbots for real-time assistance or personalizing communications based on member preferences. Enhanced experiences not only meet members’ expectations but also strengthen their loyalty to the institution.

Mandy Zubrick is the Director of Strategic Consulting Member Experience at Trellance. 

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