Recommendation Engine
Personalized dish recommendations based on preferences, allergies, and health goals

About the Project
We built a sophisticated recommendation engine that suggests dishes tailored to individual user preferences, dietary restrictions, allergies, and health goals. The system learns from user behavior and feedback to continuously improve its recommendations, driving higher customer satisfaction and increased revenue through personalized upselling.
Challenges & Solutions
Key obstacles we addressed and the innovative solutions we delivered.
Challenge
Pain Point
Our Solution
Generic recommendations
One-size-fits-all suggestions led to low engagement and frequent customer complaints about irrelevant options
Developed multi-factor recommendation model considering taste preferences, dietary needs, and contextual signals
Allergy safety
Manual allergen tracking was error-prone, creating liability risks and limiting options for customers with restrictions
Built comprehensive ingredient database with automatic allergen flagging and safe alternative suggestions
Cold start problem
New users received poor recommendations until sufficient data was collected, causing early churn
Implemented smart onboarding flow and collaborative filtering to provide quality recommendations from day one
Generic recommendations
Pain Point
One-size-fits-all suggestions led to low engagement and frequent customer complaints about irrelevant options
Our Solution
Developed multi-factor recommendation model considering taste preferences, dietary needs, and contextual signals
Allergy safety
Pain Point
Manual allergen tracking was error-prone, creating liability risks and limiting options for customers with restrictions
Our Solution
Built comprehensive ingredient database with automatic allergen flagging and safe alternative suggestions
Cold start problem
Pain Point
New users received poor recommendations until sufficient data was collected, causing early churn
Our Solution
Implemented smart onboarding flow and collaborative filtering to provide quality recommendations from day one
Results
Measurable outcomes that demonstrate the impact of our work.
20%
Higher Customer Satisfaction
15%
Revenue Increase
35%
Higher Engagement
<100ms
Response Time
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