UX Research: Credit Card Terminology Study
Ashley Bragg
Conducted for a leading credit card company, our research study explored how users interpret certain credit card terms, revealing various connotations and expectations associated with each. As we analyzed the data, it became evident that the language used has a significant impact on user expectations of product positioning and organization. Our study included both qualitative and quantitative research methods to gain a deeper understanding of these nuances.
Understanding user perspective of the terms “Starter” & “Building”
Our research delved into the nuances of how users interpret these terms, revealing diverse connotations and expectations associated with each. As we navigated through the data, it became evident that the choice between “starter” and “building” carries profound implications for user expectations of product positioning and organization.
Purpose
Learn insights on how credit users perceive “Starter” and “Building” in order to deliver relevant content and products that align with their needs and preferences.
Outcomes
Data-backed recommendations on how to best use the terms “Starter card” and “Building card” on the Client's Card Site. This report builds these suggestions from SEO data, quantitative research, and qualitative user interviews.
Future decisions informed by user insight
New or reorganized categories that match user expectations - Improving credit card categorization helps users find suitable options and make faster decisions, reducing frustration and increasing the likelihood of discovering ideal products.
Copy that aligns with users understanding of card categories - When card descriptions are clear and match user expectations, people can make better decisions, save time, and avoid frustration while selecting a card that meets their particular needs and financial goals.
Site-wide implications for terminology usage - Consistent terminology creates familiarity and clarity, making it easier to understand content and enhancing the overall experience. Therefore, maintaining consistent terminology use is crucial to provide a seamless experience for users.
Why It Matters
Users find being rejected from a card application to be a negative experience that impacts their view of the brand. By improving card language, users can better self-identify a card that works for them and have a lower chance of rejection. This leads to an improved user experience, stronger brand advocacy, and more successful new card applications.
Meet the Team
Rashida Prattis - Lead UX Designer
Ashley Bragg - Senior UX Designer
Caleb McAlister - Tech SEO Lead
Process
From data collection to analysis, this methodology ensured we unearthed valuable nuggets of understanding.
Search Volume Research - Monthly search volume data is key to understanding online user behavior, empowering data-driven decision-making.
Qualitative IDI Interviews - In-depth interviews (IDIs) offer a window into the human experience: thoughts, emotions, perceptions, and stories.
Quantitative Tree Test Study - We explored credit card associations and navigation, which provided insight on how users intuitively seek “starter” and “builder” cards.
Prepare Key Findings - Analyzing our key findings is the heart of our research, empowering us to delve into the core of user perceptions and behaviors.
Tools
Maze
Dovetail
Figma
FigJam
Zoom
Respondent
Qualitative User Interviews
In-depth interviews offer a window into the human experience: the thoughts, emotions, perceptions, and stories.
10 Participants
A mix of genders, ages (18 to 65), and abilities
A mix of education levels and incomes
Participants who have the appropriate credit scores
Excluded users in marketing, tech, design, and financial industries to prevent bias
Virtual In-Depth Interviews
Lead Designer, Rashida and I asked open-ended questions, listened to responses, and followed up with further questions to learn more in these virtual hour long interview sessions.
Topics covered:
Credit card searching habits
Personal financial history
Ideal credit search experience
Impressions of credit scores
Pain points of getting a credit card
Closed Cloze Test
During the interview we also conducted a cloze test where we provided a paragraph with blanks for users to fill in with a list of words to choose from. This took place as the user thought out loud and expanded on their selection within the Maze test. See the example text below:
Word Association Exercise
Finally we presented three credit card descriptions, with brand names removed. The user then described the cards in their own words and matched them to the terms.
Terms matched:
Starter Card
Building Card
Beginner Card
Quantitative Survey
We explored credit card associations and navigation which provided insight on how users intuitively seek “starter” and “building” cards.
67 Participants
A mix of genders, ages (18 to 65), and abilities
A mix of education levels and incomes
Survey Design
Tree Test
Tree testing involves asking users to find certain items based on website organization and language. This online test is designed to remove any clutter and only display navigation links. We chose this method to better understand where users tend to look for "starter" and "builder" cards. Our goal is to gain a deeper understanding of what types of cards users associate with these terms.
Navigation categories pulled from then current compare all cards filters on the client's website:
Credit Level
Card Type
Rewards
Generative AI Questions
Harnessing the capabilities of GPT-4, we used the AI Follow-up question to explore deeper insights from testers' answers, similar to a moderated session. It starts with an initial open-ended question. From there, the AI assistant generates an additional follow-up question, based on each tester’s initial response.
Questions asked:
What do you think of when you hear the term "Starter" credit card?
What kind of person would benefit from a "Starter" card?
What do you think of when you hear the term "Building" credit card?
What kind of person would benefit from a "Building" card?
Key Findings
Analyzing our key findings is the heart of our research. Empowering us to delve into the core of user perceptions and behaviors.
Our approach
Interview Review and Tagging - We organized interview data, filtered with tags, tracked topic frequency, and created visuals for insights. This analysis leads to informed decisions and user satisfaction.
Affinity Mapping - Our team collected data and used virtual sticky notes to organize them. By labeling the notes into clusters based on common patterns and themes, we were able to identify key trends and insights.
Survey Report Review - We collected, cleaned, and grouped survey responses to identify recurring themes and trends, drawing conclusions from these patterns.
Final Report
The following shows the key insights gleaned form the study. Along with this data we shared audio clips from the user interviews which brought the sentiments to life and illustrated the emotions that were connected to credit card language. Additionally, SEO search metrics specific to the client's data was also included in the final report. For privacy reasons for both the client and users the clips and search data were excluded from the findings below.
Insights answering the client's original questions:
Starter cards are for students
Starter cards are typically associated with students. They can also fit individuals not in school who lack credit history such as young adults and those who have experienced life circumstances such as divorce or immigration.
Recommendation: Use the term "starter" for both student credit cards and those accessible to individuals without a credit history.
59.1% thought of a “Starter card” for students or young adults starting their credit journey
9/10 users chose the Student card for the term “Starter card”
The difference between Rebuilding & Building
“Rebuilding” was identified as a well-understood term for improving a poor credit score, while “Building” had a broader definition which included building from scratch and improving established credit history.
Recommendation: Use "Rebuild" for cards aiding credit recovery and "Building" as a term to describe what users can do with Student and cards for fair credit.
23% selected the category “rebuilding” When prompted to look for a “building” card
“Starter” is better than “Beginner”
Users saw the terms “Starter” and “Beginner” as the same thing but would use the term “Starter” more often in conversation and favored it in the matching activities.
Recommendation: Use the term “Starter” instead of “Beginner.”
28% referenced “beginner” when asked to describe a starter card
10/10 users chose the same card for the term “Starter card” and the “Beginner card”
They aren’t Up Market or Good Credit cards
Neither “Starter cards” nor “Building cards” were associated with Excellent or Good Credit cards. Only student cards and fair credit cards fit their expectations.
Recommendation: Use the term “Starter” and “Building” for Student and Fair Credit cards; not Excellent or Good Credit cards.
10/10 users agreed that the good credit card was not a “Building card”
9/10 users agreed that the Good Credit card was not a “Starter card”
Additional insights discovered in the research process:
Progressing terminology
Users tended to see terms in a timeline of a credit journey. “Starter” came first with no credit history, then “Building” that credit, and, if there was a credit score slip up, they had to take a step back to “Rebuilding.”
Recommendation: Use “Starter” for no credit history, “Building” for some credit history, and “Rebuilding” for repairing credit history.
Credit score, credit level, and credit history
When organizing credit cards, users tend to prioritize credit history over credit level. Specifically, they used two categories - "no credit history" and "poor credit history." Credit scores and levels brought confusion.
Recommendation: Avoid relying on credit level as a self-sorting option as users don’t intuitively know what they mean.
Tree Test Activity: “What category would you find a credit card for someone with no credit history?”:
Preference for simple language
Users preferred terms that were simple and positive. They noted that there was a lot to read in the card search process thought and simple language made that easier.
Recommendation: Avoid over complicated terminology. Instead opt for a conversational tone.
Search habits start with Google and end with people
Users started their credit card search process on Google but would then seek opinions from friends, reviews and experts to validate their findings.
Recommendation: Consider improving the review experience on the card site. If this owned asset is optimized, then it could be an additional crowdsourcing resource in the user’s decision making process.
Top resources used when searching for a new credit card:
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Posted Feb 20, 2024
Conducted for a leading credit card company, our research study explored how users interpret certain credit card terms, revealing various connotations.
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