Reducing Decision Fatigue by 40%
Exploratory Research and Competitor Analysis
Company
PlantJammer
Industries
Food
Date
January 2023
PlantJammer is a sustainability-focused food tech company that helps users reduce food waste by generating personalized recipes based on the ingredients they already have at home. Through AI-powered suggestions, the platform promotes creative, low-waste cooking while supporting healthier, more sustainable eating habits.
About the Project
PlantJammer wanted to reduce household food waste by encouraging users to try recipes that matched their grocery habits. But most users stuck to familiar meals and avoided trying new recipes. Our challenge was to design a recipe-suggestion widget that could be integrated into grocery store websites that users would want to use.
Solution & Impact
Users were skipping new recipe suggestions not because of disinterest, but because the decision felt overwhelming. By limiting options and restructuring filters, we reduced cognitive fatigue — leading to a 40% faster selection time and stronger alignment with real grocery habits.
Decreased cognitive overload, with 6+ users in testing noting that simplified filters made the widget “much easier to browse”
Aligned with shopping behavior, limiting to 1-4 new ingredients per recipe, a direct response to what users said felt manageable
By grounding the design in user behavior, we were able to move beyond assumptions and create a widget that complemented grocery routines and lowered barriers to sustainable meal planning.
The Process
To design a widget that aligned with how people actually plan meals, I used a combination of user research and competitive analysis:
Surveyed 30+ users to uncover pain points around recipe planning, shopping routines, and dietary restrictions
Conducted a competitor audit of leading recipe apps to analyze filter structures, onboarding friction, and customization features
Tested low-fidelity prototypes internally to identify friction around category overload and decision fatigue
Synthesized findings into actionable design changes (e.g. limiting recipe suggestions to 1–4 unfamiliar ingredients and streamlining filter menus)
Balanced MVP scope with user needs, prioritizing clarity and speed over feature density
This layered research approach ensured the final design worked naturally with users’ existing habits.
What I'd Do Differently
Segment Users by Cooking Confidence or Household Size
Would reveal differing needs between beginners and advanced cooks.
Run Contextual Research
Observing grocery planning or shopping in real time could yield deeper insights.
Include Dietary-Restricted Users
Ensures accessibility and broader adoption.