Paola Amparan

Company: [Leading Financial Institution]
Role: Senior UX Strategist
Duration: January 2023
Tools and Methods: Figma, Grouping, Empathy Mapping, UX Data Narratives

Overview

In an effort to deepen customer understanding and improve user engagement, I led the creation of a demographic segmentation model for a leading financial institution. The project involved transforming extensive raw user data from various qualitative and quantitative studies into clear, actionable segments. By developing distinct personas for the bank's primary demographic groups, we laid the groundwork for targeted UX enhancements aimed at boosting user satisfaction and conversion rates.

The Challenge

1. Fragmented User Data from Multiple Sources

Data Complexity: The bank had amassed a wealth of raw data from internal studies and external reports, but it lacked a cohesive narrative tying the information together.
Segment Diversity: The customer base included a wide range of demographics with varying banking needs—from Affluent Retirees to Young Professionals and Underbanked Individuals.
Actionable Insights Deficit: Without a unified approach, stakeholders struggled to derive actionable insights to meet specific user needs effectively.

2. Lack of a Unified User Segmentation Framework

Inconsistent Data Narratives: Varying focuses and depths across data sources led to inconsistent insights.
Missing Customer Journey Context: The absence of segment-specific journey mapping made it difficult to identify key motivations, pain points, and preferences within the user experience.

My Role and Approach

1. Data Collection and Consolidation

Source Analysis: Analyzed and consolidated data from internal baseline studies, segmentation research, and external banking persona reports.
Research Methods: Utilized both generative research to understand broader segment characteristics and evaluative research to gauge specific pain points and preferences.

2. Segment Development through Data Expansion and Grouping

Data Expansion and Grouping: Categorized key data points into primary attributes like age, income, education, marital status, values, and pain points.
Empathy Mapping: Created empathy maps for each segment to visualize user-specific concerns, motivations, and daily routines.
UX Narratives: Constructed compelling narratives for each demographic, ensuring profiles were actionable and relatable.

3. Identifying Pain Points and Motivations

For each segment, I detailed core motivations, anxieties, and specific banking pain points:

Affluent Retirees: Desire simple digital interfaces; concerned about digital literacy and complex platforms.
Young Professionals: Seek financial stability; sensitive to fees and frustrated by subpar digital experiences.
Underbanked Individuals: Need low-fee, accessible banking; face challenges with credit building due to limited financial literacy.
Working Retirees: Value personalized customer service; require clear information due to limited digital familiarity.

4. Providing Segment-Specific Recommendations

Using the synthesized data, I offered targeted recommendations:

Enhanced Digital Experiences: For Young and Affluent Professionals, prioritize seamless mobile banking, budgeting tools, and robust security features.
Accessible Solutions: For Working and Affluent Retirees, improve online interfaces with user-friendly designs and ensure accessible customer support.
Cost-Effective Services: For Underbanked Individuals, emphasize affordable products, financial literacy resources, and accessible credit options.

The Solution

Synthesizing User Data into Actionable Segments

To address these challenges, I synthesized the raw data into a cohesive segmentation framework, resulting in five primary demographic groups with detailed profiles:

1. Affluent Retirees

Characteristics: Predominantly white, married or widowed, no children under 18, assets between $100k - $2MM.
Needs and Motivations: Security, personal fulfillment, desire to leave a legacy.
Banking Priorities: No account minimums, fraud protection, personalized services.

2. Young Professionals

Characteristics: Under 40, college-educated, dual-income or high-earning singles.
Needs and Motivations: Career growth, financial stability, autonomy.
Banking Priorities: Online banking features, overdraft protection, easy credit access.

3. Affluent Professionals

Characteristics: Ages 35-65, highly educated, household income above $150k.
Needs and Motivations: Career advancement, security, lifestyle enhancements.
Banking Priorities: Private banking, wealth management, digital security.

4. Underbanked Individuals

Characteristics: Typically younger, household incomes under $50k, some college education, often renters.
Needs and Motivations: Stability, affordability, financial education.
Banking Priorities: Free checking, debit card access, cost-effective online banking.

5. Working Retirees

Characteristics: Aged 65+, moderate income, continue working part-time.
Needs and Motivations: Financial stability, personal growth, social connections.
Banking Priorities: Live customer service, easy branch access, assistance with retirement savings.

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Results and Impact

1. Established Clear, Data-Backed Segments

Provided the bank with five well-defined user segments reflecting accurate motivations, needs, and pain points.
Created a foundation for ongoing UX improvements and a user-centered framework for service enhancements.

2. Delivered Actionable Insights

Informed UX Design: Enabled designers to tailor online experiences to meet diverse user needs.
Data-Driven Marketing: Allowed for personalized outreach, highlighting relevant services for each segment.

3. Enhanced Cross-Functional Alignment

Fostered a shared understanding of the customer base across UX, marketing, and customer support teams.
Ensured consistent, segment-focused communication and service strategies.

Reflection and Learnings

1. The Power of Data-Driven Segmentation

Reinforced the importance of leveraging data to identify actionable insights and align strategies closely with customer needs.

2. Impact of Empathy Mapping

Transformed raw data into relatable user stories, making segments' needs and challenges accessible for design and business teams.

3. Benefits of Catering to Diverse Segments

Addressing specific needs enhanced overall engagement and equipped the bank to provide personalized, impactful solutions.

Conclusion

By converting fragmented user data into clear, actionable demographic segments, we empowered the bank to better understand and serve its diverse customer base. This project not only provided a foundational tool for ongoing optimization initiatives but also enhanced user engagement through targeted improvements in accessibility, usability, and personalization. The success of this segmentation model underscores the critical role of user-centered design and data-driven strategies in the financial services industry.

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Demographic Segments for a Financial Institution