Understand and Define
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Country Delight addresses the challenge of providing fresh and unadulterated dairy and fresh, minimally processed food products directly to consumers. The company ensures that customers receive high-quality, natural products without the intervention of middlemen, reducing the risk of adulteration and ensuring freshness.

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​Vision

To revolutionise the way milk and fresh foods are delivered in India by providing consumers with pure, fresh, and unadulterated products and to become the most trusted and reliable brand for natural, minimally processed food essentials

​Mission

• To source milk and fresh produce directly from small and medium-sized farms across India, ensuring high quality and traceability
• To deliver farm-fresh milk, fruits, vegetables, and other kitchen staples to customers' doorsteps within 24-36 hours
• To build a full-stack supply chain model backed by technology to address industry challenges like adulteration and lack of transparent
• To empower local farming communities by providing sustainable livelihoods and fostering transparency in the supply chain

Channels

Country Delight operates through the following channels:

1. Direct-to-Consumer (D2C): Subscription-based deliveries through their mobile app and website. Offers a VIP program for regular customers to save up to 30% through upfront payment
2. General Trade Stores: Present in 30,000 general trade stores across India. Expanding presence to reach 10-15% market share in North India over the next 3 years.
3. Quick Commerce Platforms: Sells products through quick commerce platforms in addition to its own D2C channel.
4. International Markets: Exports some products to markets like Kuwait, Dubai, Maldives and Australia.

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Ideal Customer Profiles (ICPs)

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Jobs To Be Done (JTBD)

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Technical Breakdown​

Product Components​

Tech-stack​

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Database Understanding

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Understanding the Data Flow​

The data flow within the Country Delight app involves multiple layers that interact with each other to provide seamless service to users. Here's how different layers speak to each other:

1. User Interaction Layer (Presentation Layer):

• Interaction: Users interact with the mobile app or website to place orders, manage subscriptions, track deliveries, and access support.
• Data Flow:
• • Input: Users enter data such as order details, payment information, and feedback.
  • Output: The app displays order statuses, personalized recommendations, and product information.
    

2. Application Layer (Business Logic):

• Interaction: This layer processes requests from the user interface, applies business logic, and communicates with both the data layer and third-party APIs.
• Data Flow:
• • Order Processing: When an order is placed, the application layer processes the order details, checks inventory, and calculates the total cost.
  • Payment Processing: This layer handles payment requests by communicating with the payment gateway APIs.
  • Real-time Tracking: The application layer retrieves real-time GPS data from the mapping API and updates the user interface.
  • Recommendations: The AI/ML algorithms process user data and generate personalized recommendations.
  • Customer Support: Requests are routed through customer support APIs to handle inquiries and issues.
    

3. Data Management Layer (Data Layer):

• Interaction: This layer stores, retrieves, and manages data. It ensures data integrity and security while managing CRUD (Create, Read, Update, Delete) operations.
• Data Flow:
• • Data Storage: Stores user profiles, order history, payment transactions, product information, and support tickets.
  • Data Retrieval: Retrieves necessary data to display on the user interface, such as order history, subscription details, and product information.
  • Data Updates: Updates the database with new orders, subscription changes, and support resolutions.
    

4. Third-Party APIs:

• Interaction: Third-party APIs are called by the application layer to perform specific tasks that are outside the scope of the core application logic.
• Data Flow:
• • Payment Gateway: Securely processes payments and returns transaction statuses.
  • GPS/Mapping: Provides real-time tracking information for deliveries.
  • Analytics: Collects data on user interactions for reporting and analysis.
  • Customer Support: Manages support tickets and provides resolution data.
  • AI/ML APIs: Delivers personalised recommendations based on user data.
    

Flow of Information

1. User Interaction (Presentation Layer): The user interface is where users interact with the app by placing orders, managing subscriptions, tracking deliveries, and contacting support.
2. Application Layer (Business Logic): This layer processes the user's actions, applying business rules and logic to handle orders, payments, subscriptions, and support requests.
3. Data Layer (Database): The data layer stores all relevant information, such as order history, user profiles, product details, and support tickets, ensuring the data is up-to-date and secure.
4. Third-Party APIs: The application layer interacts with third-party APIs for specific functions like payment processing, delivery tracking, and customer support, integrating these services into the app's workflow.

Flow chart

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Capabilities to Build

Personalised Nutrition-Based Order Quantity Smart Suggestions

Aim: This feature aims to provide users with personalised portion size recommendations based on their nutritional needs, preferences, and health goals.

1. JTBD for the feature
2. • Job To Be Done (JTBD): Users want personalised recommendations for portion sizes that align with their health goals (e.g., weight loss, muscle gain) and dietary preferences. The goal is to make it easier for users to prepare balanced meals without guesswork.
     
3. What are the components required?
   
4. • User Profile Setup:
   • • A questionnaire to gather information about the user’s age, weight, health goals, dietary restrictions, and preferences.
   • Nutritional Database:
   • • A comprehensive database containing nutritional information for various food items, including macronutrient breakdowns and portion sizes.
   • Recommendation Engine:
   • • Algorithms that analyse user data and dietary guidelines to generate smart portion size suggestions.
   • Mobile App Interface:
   • • A user-friendly interface to display personalised portion size recommendations and allow users to adjust their preferences.
   • Feedback Mechanism:
   • • A system for users to provide feedback on the recommendations, allowing the app to refine suggestions over time.
       
5. How many tech layers do you require?
   
6. • Presentation Layer:
   • • User interface for displaying portion size recommendations and gathering user inputs.
   • Application Layer:
   • • Business logic for processing user data, generating recommendations, and managing feedback.
   • Data Layer:
   • • Database modifications to store user profiles, nutritional data, and feedback.
       
7. Functionality of all the layers:
   
8. • Presentation Layer:
   • • Displays personalised portion size recommendations based on user input and preferences. Allows users to adjust their dietary goals and preferences.
   • Application Layer:
   • • Processes user data and generates tailored portion size suggestions using algorithms. Manages user feedback to refine recommendations.
   • Data Layer:
   • • Stores user profiles, nutritional data, and feedback, ensuring quick access and retrieval for the application layer.

Nuances and trade-offs​

Technology Stack Breakdown

Properties at Each Stage

Data Flow

The data flow for the Personalized Nutrition-Based Quantity Smart Suggestions feature involves several stages:

1. User Interaction:
2. • Users input their preferences, health goals, and dietary restrictions during profile setup.
3. Data Submission:
4. • User inputs are sent to the application layer via API calls.
5. Application Layer Processing:
6. • The application processes the user data, retrieves relevant nutritional information, and generates personalised portion size recommendations.
7. Database Operations:
8. • The application retrieves and stores data in the database:
   • • User Data: Updates user profiles and preferences.
     • Nutritional Data: Stores and retrieves food items and their nutritional information.
9. Feedback Collection:
10. • Users provide feedback on the recommendations, which is sent back to the application layer for processing.
11. Analytics and Refinement:
12. • User interactions and feedback are tracked for analysis, helping improve user experience and app performance.

Data Flow Diagram​

Nuances and Trade-offs

User Experience vs. Security

• Trade-off: Implementing robust security measures, such as multi-factor authentication, may complicate user access to personalised nutrition features.
• Nuance: While enhancing security is critical for protecting sensitive health information, it’s essential to maintain a seamless user experience. Techniques like risk-based authentication can ensure that security measures do not hinder usability, allowing users to easily access their personalized recommendations.

Third-party vs. In-house Nutritional Database

• Trade-off: Utilising a third-party nutritional database can accelerate development but may limit customisation and alignment with Country Delight's specific needs.
• Nuance: Third-party databases, like USDA FoodData Central, can provide extensive nutritional data quickly, but may not fully support tailored recommendations based on user preferences or local food availability. In-house solutions offer greater control and customisation but require significant resources for development and maintenance.

Caching Strategy

• Trade-off: Engineers may choose to cache frequently accessed data (e.g., popular food items) to enhance performance, but this could lead to serving outdated information.
• Nuance: Effective caching can improve load times and user experience, but it’s vital to ensure that personalised recommendations reflect the most current user data. Implementing a strategy that combines static caching for general data and dynamic updates for personalized information can help maintain accuracy.

Limitations of Current Tech Stack​

• The current tech stack may struggle with real-time data processing as the user base grows, leading to potential latency issues in delivering personalised recommendations.
• Limited support for advanced analytics may hinder the ability to derive insights from user feedback and dietary patterns.

Unique Benefits

• The existing stack is cost-effective, allowing for rapid feature development and deployment.
• Its modular architecture supports easy integration of new capabilities, such as the **Personalized Nutrition-Based Quantity Smart Suggestions**, without requiring significant overhauls.

Main Objectives Behind Making Trade-offs

1. Ensure that the feature is intuitive and provides meaningful, actionable recommendations without overwhelming users.
2. Leverage existing tools and frameworks to expedite the development of the new feature while maintaining high quality.
3. Implement necessary security measures to protect user data while ensuring a smooth and engaging user experience.

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