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Allergy Detect

!!!Brief introduction to the project and the problem it is intended to solve!!!

UX Team Members

• Jake Baartman - Phase I: Executive Summary, Introduction, Methods. Phase II: Executive Summary, Introduction, Findings.
• Kenai Toledo - Phase I: Findings sections
• Jacob Buhler - Phase II: Conclusion
• Abram Jimenez - Phase II: Methods and Caveats

User-Centered Design Artifacts

• Personas and Scenarios
• Sketches and Diagrams
• Wireframes - Coming Soon
• Prototype - Coming Soon

Phase I: Analyzing Users, Competitors, and Initial Designs

Executive Summary

• Competitive analysis showed that most of our competitors have the same core features, but they vary a lot in how clearly they handle may contain or cross-contamination and how quickly they get users to a decision.

• Heuristic evaluation of a close competitor showed a major weaknesses in clarity under time pressure, especially around system status during scanning, uncertain results, and any possible errors when using the app, like using the wrong profile for a scan.

• Users of AllergyDetect will want an experience that is streamlined and extremely fast, that's because many decisions can happen in an aisle with only a few minutes to spare.

• Clear confirmation and an undo button for important actions will be important for trust and handling errors.

• Personas and scenarios helped us with these findings: users seem to want

  • a very simple, easy to use scanner

  • results that feel trustworthy and explainable

  • an app that works anywhere and anytime with quick access and minimal steps.

• Sketches and early diagrams show our group's priorities by giving an example of its workflow: scan → deduce → make your choice. Focusing on reducing unnecessary buttons, and adding features like an easy rescan, quick profile edits from the result screen, and handling of outcomes.

Full phase I report

Phase II: Refining Interaction and Designing Wireframes

Executive Summary

• Cognitive walkthroughs with other UX participants showed that AllergyDetect’s overall workflow makes sense to first time users, especially because the allergy profile setup is straightforward and the large SCAN button clearly signals the next action.

• The walkthroughs also revealed that the scanning step needs stronger system feedback so users feel confident the app is working. Clear status cues like “scanning,” “loading,” and “product found/not found” can reduce hesitation and prevent users from second guessing themselves.

• It was also noted that the results screen is the most important point in the experience. SAFE and NOT SAFE are easy to interpret when displayed, but UNCLEAR might make people hesitate unless the app explains why the result is uncertain and gives a clear next step.

• Informal feedback from the classroom demo confirmed that users want AllergyDetect to be fast, direct, and readable at a glance. A good idea for the app would be to prioritize the verdict and avoid overwhelming users with nutrition labels, while still showing the reason, such as what ingredient or warning caused the flag.

• Feedback also suggested an addition for supporting intolerances. Instead of labeling intolerance results as simply “SAFE,” AllergyDetect could use a color coded scale, such as green, yellow, or red to better communicate risk levels and avoid sending mixed signals.

• Overall, Phase II findings influenced updates to our wireframes by improving scan feedback, simplifying the results screen, and including how intolerances are communicated.

Full phase II report

Phase III: Prototypes and User Testing

Executive Summary

!!!Put phase II Executive Summary here!!!

Full phase III report