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Filtering Overload

Disorganized filtering options confused users seeking suitable cards, making it difficult to refine their search effectively.

2

Offer Relevance

Inaccurate credit range filters misled users, offering irrelevant cards leading to denials despite approval hints.

3

Partnership Emphasis

An overwhelming focus on partnerships undermined trust in offers, deterring users from engaging fully.

Credit Explorer (New User)

Demographics: Young adult, typically aged 20-35, new to credit management, casually explores financial options.

Goals/Needs: Discover beginner-friendly cards with clear score impact previews, seeking to grasp credit basics and find suitable options.

Pain Points: Overwhelmed by scattered options in the marketplace; distrusts aggressive promotions; seeks simplicity to avoid confusion.

Behaviors: Scans for quick matches eagerly, responds to high approval odds indications with interest.

Design Influence: Inspired a bold, rebranded layout with intuitive previews.

Credit Strategist (Seasoned User)

Demographics: Mature user, typically aged 40-55, credit-savvy, actively managing multiple cards with background in managing credit profiles.

Goals/Needs: Identify premium cards using detailed score-range analysis, seeking tools for suitable options.

Pain Points: Limited customization in the marketplace; lacks multi-range data for in-depth analysis; wary of excessive upsells and distracting promotions.

Behaviors: Dives deep into filters; values precision in tailored and personalized offers.

Design Influence: Shaped advanced, organized filters and rebranding alignment for personalization.

Early Findings

During the discovery phase, I assessed key credit card platforms like Capital One, Discover, Chase, and American Express, focusing on their own offers, and credit monitoring marketplaces such as Credit Karma and Credit Sesame, all facing challenges with score-based previews. This review uncovered gaps in filtering relevance, application flow, and personalization, noting limited customization, lengthy processes, and outdated accuracy.

Leading Competitors: Credit Karma, Credit Sesame and Capital One

Journey Flow for User Paths

A journey flow/decision tree was created to map out various edge cases and paths for both free/non-signed-in users and registered signed-in users, guiding design choices for seamless transitions and identifying areas needing adjustments to support diverse user paths.

Initial Wireframes for Market Insights

Initial wireframes were created to gather insights from stakeholders and users, refining the layout to address scattered filtering and enhance score-based previews, while exploring data visualization with score tracking via interactive visuals and card offer comparisons. These wireframes helped inform various visual and interaction types that shaped the final design, boosting user engagement and card partnerships.

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Discovery Approach

Discovery began with user research and competitor analysis, engaging 3-5 users with wireframes to assess initial reactions to the marketplace.