Employee Benefit Program
  • Preface
  • #1: Research
    • Design Brief
    • Research Methods
      • Stakeholder-map
      • Brand Research
      • Data Analysis
      • Participant Observations
      • Customer Journey
      • Survey - Consumer Behaviour Car Industry
      • Competitive Analysis
      • Literature Studies
        • Designing A Perfect Responsive Configurator
        • Meyer Brigs Type Indicator
        • Don't Make Me Think
        • Persuasion
        • BJ-Fogg Model
        • '21 Best Practices for E-Commerce Configurators'
      • MBTI Persona's
    • Research questions
  • #2: Conceptualisation
    • Concept Ideas
    • Feedback Frenzy
  • #3: Prototyping
    • Q&Onboarding Development
      • Q&Onboarding V1
        • Q&Onboarding V1 Tests
      • Q&Onboarding V2
        • Q&Onboarding V2 Tests
      • Q&Onboarding V3
        • Q&Onboarding V3 Tests
    • Configurator Development
      • User Flow
      • Sketches
      • Styleguide
      • High Fidelity Prototype
      • High fidelity Prototype V2
      • Expert Review
  • #4 Follow up research
    • Greenlight Presentation
    • Interviews
      • Interview #1 customer-service employee at PICNIC
      • Interview #2 - Freelance product designer
      • Interview #3 Project Manager at Ymere
    • Q&Onboarding V4.1 & V4.2 Development
      • Tests Q&Onboarding V4.1 & V4.2
    • Scenarios
    • Q&Onboarding Final
  • ∞: Requirement list
  • Literature
  • Design Brief
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  1. #3: Prototyping
  2. Q&Onboarding Development
  3. Q&Onboarding V1

Q&Onboarding V1 Tests

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Last updated 5 years ago

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Tests

When I finished the design, I particularly wanted users to test the phrasing of the questions. Because I didn’t know yet how users would react on the questions, and what they think the questions would generate, I only wanted to know if the questions were clear. Throughout the first tests, I already encountered the first problem. The problem occurred at the first question about the monthly budget. The user stated that whenever an indication about a monthly budget is given a user automatically limits themselves about the possible outcomes. This is because a cheap model with a lot of features can have a similar price of an expensive basic model. This information was enormously valuable because now I knew that a question about money is way too complicated. One might be satisfied with a small full packed model, whereas the other prefers a bigger car with basic options. As there are dozens of combinations within different models and variants, users are simply not able to choose based on the given budget.

During the second test, the user gave a decisive insight. One that told me I did not had to continue developing this version. Namely, the user found out that with the answer option this questionnaire could compose the ideal car. As the questionnaire asks for which amount of pollution a user wants or for example what level over consumption, everyone would answer this question with the most beneficial answer. An SUV with energy label ‘A’, the most little consumption level and the highest speed ratio would be an ideal car for everyone. However, every car is bound to their own characteristics and people have to choose between certain preferences. From this point, I directly decided to throw away the phrasing of the question and move on to the next version.

Link to the first prototype:

https://invis.io/Y3RMPZCEHWP