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Discount Definitions

The discount system supports multiple discount types and complex targeting rules for flexible pricing strategies. Discounts can be applied automatically or manually, with support for various value types and application scopes.

Discount Types​

1. Fixed Amount Discount​

type: "FIXED_AMOUNT"
value: 100          // Fixed amount in INR
valueType: "AMOUNT"
scope: "PRODUCT" | "ORDER"

Example: ₹100 off on selected products or entire order.

2. Percentage Discount​

type: "PERCENTAGE"
value: 20           // 20% discount
valueType: "PERCENTAGE"
scope: "PRODUCT" | "ORDER"

Example: 20% off on selected products or entire order.

3. Buy X Get Y Discount​

type: "BUY_X_GET_Y"
value: 50           // 50% off on Y items
valueType: "PERCENTAGE"
scope: "PRODUCT"
buyQuantity: 2      // Buy 2 items
getQuantity: 1      // Get 1 item at discount

Example: Buy 2, Get 1 at 50% off.

4. Tiered Discount​

type: "TIERED"
valueType: "PERCENTAGE" | "AMOUNT"
scope: "PRODUCT" | "ORDER"
tieredRules: [
  { minQuantity: 1, value: 10 },  // 10% off for 1+ items
  { minQuantity: 5, value: 20 },  // 20% off for 5+ items
  { minQuantity: 10, value: 30 }  // 30% off for 10+ items
]

Example: Quantity-based progressive discounts.

5. Cart Level Discount​

type: "CART_LEVEL"
value: 500          // ₹500 off
valueType: "AMOUNT"
scope: "ORDER"
minCartValue: 2000  // Minimum cart value ₹2000

Example: ₹500 off on orders over ₹2000.

Application Types​

Automatic Discounts​

  • Applied automatically during checkout
  • No customer action required
  • Based on cart contents and rules

Manual Discounts​

  • Applied by customer using discount code
  • Requires explicit code entry
  • Can have usage limits and restrictions

Value Types​

Amount-based​

  • Fixed monetary value (₹100 off)
  • Consistent across all products
  • Simple calculation

Percentage-based​

  • Percentage of product/order price
  • Scales with product value
  • More flexible for different price points

Scopes​

Product Scope​

  • Discount applies to individual products
  • Can target specific products, categories, collections
  • Supports quantity-based rules

Order Scope​

  • Discount applies to entire order
  • Cart-level discounts
  • Order minimum requirements

Targeting Rules​

Product Targeting​

// Target specific products
productIds: ["product-1", "product-2"]

// Target product categories
categoryIds: ["category-1", "category-2"]

// Target collections (planned)
collectionIds: ["collection-1", "collection-2"]

// Target by tags (planned)
tagIds: ["summer", "clearance"]

Customer Targeting (Future)​

// Target specific customers
customerIds: ["customer-1", "customer-2"]

// Target customer groups
customerGroupIds: ["vip", "wholesale"]

// Geographic targeting
regions: ["IN", "US"]

Usage Limits​

Per Customer​

usageLimit: 1        // One use per customer
usageCount: 0        // Current usage count

Total Usage​

totalUsageLimit: 100  // Maximum total uses
totalUsageCount: 0    // Current total uses

Time Limits​

startsAt: "2025-01-01T00:00:00Z"
endsAt: "2025-12-31T23:59:59Z"

Discount Stacking​

Priority System​

  • Discounts sorted by priority (lower number = higher priority)
  • Higher priority discounts applied first
  • Lower priority discounts applied to remaining amount

Stackability Rules​

  • Some discounts can stack
  • Others are mutually exclusive
  • Configurable stacking behavior

Example Stacking​

// Discount A: 10% off (priority: 1)
// Discount B: ₹100 off (priority: 2)
// Final price: Apply 10% first, then ₹100 off remaining

Validation Rules​

Business Rules​

  • Code Uniqueness: Each discount code must be unique
  • Date Validation: End date must be after start date
  • Value Limits: Percentage discounts ≤ 100%
  • Quantity Logic: Buy quantity ≥ get quantity for BOGO
  • Target Consistency: At least one targeting rule required

Technical Validation​

  • Type Consistency: Value type matches discount type
  • Scope Compatibility: Application scope matches discount type
  • Target Existence: Referenced products/categories must exist

Calculation Engine​

Discount Resolution​

  1. Filter Applicable Discounts: Based on targeting rules
  2. Sort by Priority: Lower priority number first
  3. Calculate Impact: Apply each discount in order
  4. Handle Conflicts: Resolve stacking conflicts
  5. Update Totals: Recalculate order totals

Complex Scenarios​

// Scenario: Multiple discounts on same product
Product Price: ₹1000
- Discount A: 20% off (priority 1) → ₹800
- Discount B: ₹100 off (priority 2) → ₹700
- Final: ₹700

// Scenario: BOGO + percentage
Buy 2 Pay 1: Buy 2×₹500 = ₹1000, Get 1×₹500 at 50% = ₹250
Total: ₹1000 + ₹250 = ₹1250 (instead of ₹1500)

API Examples​

Create Fixed Amount Discount​

POST /admin/discounts
Content-Type: application/json

{
  "code": "SAVE100",
  "name": "Save ₹100",
  "description": "₹100 off on orders over ₹500",
  "type": "FIXED_AMOUNT",
  "value": 100,
  "valueType": "AMOUNT",
  "scope": "ORDER",
  "applicationType": "AUTOMATIC",
  "minCartValue": 500,
  "startsAt": "2025-01-01T00:00:00Z",
  "endsAt": "2025-12-31T23:59:59Z",
  "priority": 10
}

Create Buy X Get Y Discount​

POST /admin/discounts
Content-Type: application/json

{
  "code": "BUY2GET1",
  "name": "Buy 2 Get 1 Free",
  "description": "Buy 2 items, get 1 free",
  "type": "BUY_X_GET_Y",
  "value": 100,
  "valueType": "PERCENTAGE",
  "scope": "PRODUCT",
  "applicationType": "AUTOMATIC",
  "buyQuantity": 2,
  "getQuantity": 1,
  "productIds": ["product-1", "product-2"],
  "startsAt": "2025-01-01T00:00:00Z",
  "endsAt": "2025-12-31T23:59:59Z",
  "priority": 5
}

Create Tiered Discount​

POST /admin/discounts
Content-Type: application/json

{
  "code": "BULK10",
  "name": "Bulk Discount",
  "description": "10% off for 3+, 20% off for 5+",
  "type": "TIERED",
  "valueType": "PERCENTAGE",
  "scope": "PRODUCT",
  "applicationType": "AUTOMATIC",
  "tieredRules": [
    { "minQuantity": 3, "value": 10 },
    { "minQuantity": 5, "value": 20 }
  ],
  "categoryIds": ["category-1"],
  "startsAt": "2025-01-01T00:00:00Z",
  "endsAt": "2025-12-31T23:59:59Z",
  "priority": 15
}

Performance Considerations​

Caching Strategy​

  • Discount Rules: Cached in Redis for fast access
  • Targeting Data: Pre-computed product relationships
  • Calculation Results: Cached for repeated calculations

Database Optimization​

  • Indexes: On frequently queried fields (code, dates, status)
  • Relationships: Optimized foreign key constraints
  • Bulk Operations: Batch discount calculations

Monitoring​

  • Usage Tracking: Real-time discount usage analytics
  • Performance Metrics: Calculation time and success rates
  • Business Metrics: Revenue impact and conversion rates

Integration Points​

Cart System​

  • Real-time discount calculation during cart updates
  • Automatic discount application based on rules
  • Cart validation with discount constraints

Checkout Process​

  • Discount validation before payment
  • Final price calculation with all applicable discounts
  • Order total updates with discount details

Order Management​

  • Historical discount tracking on orders
  • Refund calculations considering discounts
  • Analytics and reporting on discount effectiveness

Product Management​

  • Product-specific discount targeting
  • Category and collection-based discounts
  • Dynamic pricing with discount integration

Best Practices​

Discount Design​

  1. Clear Naming: Descriptive discount names and codes
  2. Logical Priority: Consistent priority numbering
  3. Reasonable Limits: Appropriate usage limits and time bounds
  4. Target Precision: Specific targeting to avoid unintended applications

Business Rules​

  1. Stacking Logic: Clear rules for discount combinations
  2. Minimum Requirements: Appropriate cart/order minimums
  3. Exclusion Rules: Prevent conflicting discount applications
  4. Communication: Clear discount terms for customers

Technical Implementation​

  1. Validation: Comprehensive input validation
  2. Testing: Thorough testing of edge cases
  3. Monitoring: Track discount performance and errors
  4. Maintenance: Regular cleanup of expired discounts