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System Overview (v0.1)

Purpose

Dynamic Drink Market (DDM) is a system designed to simulate a dynamic pricing market applied to a drink menu.

The goal is to allow product prices to change in real time based on demand, creating an interactive and behavior-driven experience.

Problem

In traditional systems, product prices are static and do not reflect real-time changes in demand.

This limits:

  • Revenue optimization
  • User interaction with the system
  • Exploration of dynamic market behavior

DDM introduces a model where prices respond directly to user activity.

Approach

The system is built around a dynamic pricing engine that:

  1. Records drink orders
  2. Calculates demand in real time
  3. Adjusts prices based on defined rules
  4. Reflects price changes immediately

This approach enables a simulated real-time market environment.

System Flow

The system operates through the following sequence:

  1. A user places an order
  2. The system records the order
  3. Demand for the product is updated
  4. The pricing engine recalculates the price
  5. The new price is stored
  6. The system returns the updated price

Core Components

The system is composed of the following modules:

1. Order Module

Responsible for registering each user order.

2. Pricing Engine

Calculates dynamic prices based on demand.

3. Data Model

Defines the structure of drinks, orders, and metrics.

4. Storage System (Optional in v0.1)

Handles persistence of historical data.

5. Interface (Optional in v0.1)

Displays prices and system state to users.

Scope (v0.1)

The initial version of the system includes:

  • Basic order simulation
  • Dynamic price calculation
  • In-memory data handling
  • No required database persistence
  • No advanced user interface

The primary goal is to validate the pricing model.

Future Evolution

The system may evolve to include:

  • Database integration for persistence
  • Real-time updates (e.g. WebSockets)
  • Data visualization and analytics
  • Administrative dashboard
  • Multi-user simulation

Key Considerations

  • The system must balance stability and dynamism
  • Pricing logic should be predictable but not trivial
  • Performance should support fast updates
  • Architecture should allow future scalability