Learnings

1.Creating a conceptual model to illustrate our thinking process

When we first started creating the draft of our survey, we had listed questions out the way that they seemed to make sense for our survey-takers. However, we realized later that a conceptual model would help us identify how different sections of our survey tied in with one another.
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2. Using self-created concepts to test hypothesized relationships

We hypothesized parallels in behavior between credit-card users and student loan takers. Both involved taking out a certain amount of money beforehand, and paying it back in monthly repayments. As such, we drafted concepts to test if specific credit card usage incentives would help people pay back their student loans on time, and accelerate the rate at which they did.

3. Learning to scope our survey down to dial up clarity in insights
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Initially, we thought of opening this survey up for anyone who had taken student loans, across different educational levels and stages of loan repayment. While this would allow for more survey takers, we later decided to scope it down to: only individuals who took undergraduate student loans, and that they had to be actively paying back their loans. This created a basis of which we would be able to analyze the insights without too many differences in the individuals' life stages or loan repayment status.
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4. To design a strong survey, step into the mental model of the survey-taker
It may seem deceptively easy to create a sequence of questions for the survey-taker. However, designing our survey required a surprising number of iterations, especially when it came to trying to understand people's credit card usage without biasing them with our existing preconceptions on how they correlated with student loan repayment habits.