Use Case: Retail Operations

Overview

This use case describes how retail stores use Plings identifiers to manage inventory, prevent loss, enhance customer service, and optimize operations. The system works for both small boutiques and large chain stores.

Business Value

  • Loss Prevention: Reduce shrinkage by 30-50% through better tracking
  • Inventory Accuracy: Real-time location of every item
  • Customer Experience: Instant product information and availability
  • Operational Efficiency: Automate routine tasks and audits

User Stories

Primary Stories

  • As a store manager, I want to track product movement so that I can prevent theft and optimize layout
  • As a sales associate, I want to instantly find products so that I can serve customers quickly
  • As a customer, I want to scan products for information so that I can make informed decisions

Supporting Stories

  • As loss prevention, I want to detect unauthorized movement so that I can prevent theft
  • As a buyer, I want to analyze product flow so that I can optimize purchasing
  • As operations, I want to automate inventory counts so that I can reduce labor costs

Retail Scenarios

Scenario 1: Opening Procedures

Time: 8:00 AM, Store Opening Actor: Sarah, Store Manager

Traditional Process: Manual visual inspection, paper checklists

With Plings:

  1. Entrance Scan: Manager badge activates “opening mode”
  2. Automated Inventory: ``` System Status Dashboard:
    • Total Items: 3,847
    • In Correct Location: 3,589 (93%)
    • Misplaced: 201 (5%)
    • Missing Since Close: 57 (2%) ```
  3. Misplacement Report: ``` Priority Fixes:
    • 12 items in wrong department
    • 23 items in back, should be on floor
    • 45 items on floor, should be in back ```
  4. Quick Fixes: Staff scan and move items
  5. Shrinkage Alert: System flags suspicious patterns

Scenario 2: Customer Self-Service

Actor: Jennifer, Shopping for Running Shoes

Customer Journey:

  1. Browse: Picks up Nike running shoe
  2. Scan: Points phone at Plings QR tag
  3. Instant Info: 
    Nike Air Zoom Pegasus
Price: $130
⭐⭐⭐⭐☆ (847 reviews)
   
Available Sizes:
7 ✓ | 8 ✓ | 9 ✗ | 10 ✓
   
Color Options: [Black] [White] [Blue]
   
Features:
- Zoom Air cushioning
- Breathable mesh upper
- 10mm heel drop
  4. Comparison: “Compare with similar shoes”
  5. Locate Size: “Size 8 location: Stockroom A-7”
  6. Reviews: Reads customer experiences

Scenario 3: Inventory Optimization

Time: End of Day Analysis Actor: Regional Manager reviewing 10 stores

Plings Analytics Dashboard:

Daily Movement Patterns:
- High Traffic: Women's Accessories (847 scans)
- Low Traffic: Men's Formal (92 scans)
- Conversion: 23% scan-to-purchase

Hot Zones:
- Entrance Display: 2,341 interactions
- Sale Rack: 1,893 interactions
- Fitting Rooms: 967 items tried

Shrinkage Patterns:
- Peak Loss Time: 2-4 PM Saturdays
- High Risk Items: Small electronics
- Suspicious Patterns: 3 detected today

Actions Taken:

  • Reposition high-scan, low-conversion items
  • Add staff to peak shrinkage times
  • Move small electronics behind counter

Scenario 4: Smart Fitting Rooms

Actor: Mark, trying on clothes

Fitting Room Experience:

  1. Entry: Brings 4 items to fitting room
  2. Auto-Detection: Mirror display shows: ``` Your Items:
    1. Levi’s 511 Jeans - Size 32
    2. Nike T-Shirt - Size M
    3. Adidas Hoodie - Size L
    4. Columbia Jacket - Size L ```
  3. Recommendations: “Others also tried…”
  4. Size Request: Tap to request different size
  5. Purchase: “Send to register” for checkout

Scenario 5: Loss Prevention

Time: 3:47 PM, Busy Saturday Actor: Security System (Automated)

Suspicious Pattern Detection:

  1. Alert Generated: 
    ⚠️ LOSS PREVENTION ALERT
Time: 3:47 PM
Location: Men's Accessories
   
Pattern Detected:
- 5 items removed from display
- No corresponding fitting room entry
- Items moving toward exit
- Speed: Faster than normal shopping
  2. Staff Notification: Manager app alerts
  3. Camera Integration: Links to video feed
  4. Response: Staff intercepts politely
  5. Resolution: Customer was gathering for bulk purchase

Technical Implementation

Store Infrastructure

Entry/Exit Points

Equipment:
- Plings portal scanners (like EAS gates)
- Integration with POS systems
- Staff notification system
- Customer counter

Functions:
- Detect all Plings tags passing through
- Check payment status
- Alert on unpaid items
- Log legitimate exits

In-Store Scanners

Types:
1. Fixed Scanners:
   - Fitting room entrances
   - Department transitions
   - Stockroom doors

2. Mobile Scanners:
   - Staff smartphones
   - Dedicated handhelds
   - Customer kiosks

3. Smart Shelves:
   - RFID/NFC readers
   - Weight sensors
   - Movement detection

Data Architecture

Real-Time Tracking

Object Location Update:
{
  "identifier": "8.15.3.2024.10847",
  "location": {
    "store": "NYC-001",
    "zone": "Womens-Shoes",
    "fixture": "Display-Wall-3",
    "shelf": "B-4"
  },
  "timestamp": "2024-01-15T14:32:00Z",
  "event": "customer_interaction"
}

Analytics Pipeline

Scan Event → Location Update → Pattern Analysis → Action Trigger
     ↓             ↓                ↓                 ↓
  Customer     Inventory       Loss Prevention    Staff Alert
   Display      Database         Algorithm         System

Integration Points

POS Integration

  • Auto-populate scanned items
  • Verify authenticity at purchase
  • Update ownership records
  • Generate digital receipts

Inventory Management

  • Real-time stock levels
  • Automated reorder triggers
  • Transfer between stores
  • Vendor integration

Customer Apps

  • Store-specific features
  • Loyalty point integration
  • Wishlist synchronization
  • Purchase history

Business Rules

Privacy Compliance

  • Customer scans are anonymous
  • Movement patterns aggregated
  • Opt-in for personalization
  • GDPR/CCPA compliant

Loss Prevention Ethics

  • No customer profiling
  • Pattern-based, not person-based
  • Staff training on approach
  • False positive procedures

Inventory Accuracy

  • Daily reconciliation required
  • Monthly full counts
  • Variance investigation
  • Shrinkage reporting

ROI Metrics

Loss Prevention

  • Shrinkage Reduction: 30-50%
  • Recovery Rate: 75% of suspected theft
  • False Positives: <5%
  • ROI Timeline: 6-12 months

Operational Efficiency

  • Inventory Count Time: -80%
  • Product Location Time: -90%
  • Stock Accuracy: 99.5%
  • Labor Savings: 20-30%

Customer Experience

  • Find Product: <30 seconds
  • Information Access: Instant
  • Satisfaction Score: +15-20%
  • Conversion Rate: +5-10%

Implementation Rollout

Phase 1: High-Value Items (Month 1-2)

  • Electronics, jewelry, leather goods
  • Basic tracking and alerts
  • Staff training focus
  • ROI measurement

Phase 2: Full Store (Month 3-6)

  • All merchandise tagged
  • Analytics dashboard
  • Customer features
  • Process optimization

Phase 3: Chain-Wide (Month 7-12)

  • Multi-store deployment
  • Central analytics
  • Supply chain integration
  • Advanced features

Success Stories

Case Study: Fashion Retailer

  • Problem: 5% shrinkage rate, $2M annual loss
  • Solution: Full Plings deployment
  • Result: 2.1% shrinkage, $1.2M saved
  • ROI: 240% first year

Case Study: Electronics Store

  • Problem: Customer service delays
  • Solution: Scan-for-info system
  • Result: 50% fewer staff questions
  • Bonus: 8% conversion increase