User Scenarios

This guide outlines the key user personas and scenarios for the SynapseAI B2B Wholesale Platform, demonstrating how AI enhances the B2B ordering experience. These scenarios use FlavorFlux (a fictional adaptive CPG brand) as the example use case.

Strategic Objectives

Primary Business Goals

• Acquisition: Attract new wholesale clients by showcasing FlavorFlux's unique adaptive product offerings
• Activation: Guide new clients through seamless onboarding and first-order completion
• Retention: Encourage repeat business through personalized experiences and community engagement
• Revenue: Drive growth through strategic upsells and cross-category product adoption
• Referral: Create scenarios that incentivize existing clients to refer new businesses

User Personas

🥇 Priority 1: Sarah - Store Representative

Role: Assistant Manager at Health Food Store Chain
Primary Goal: Maintain optimal inventory levels and prevent stockouts/overstocking

Profile

• Experience: 5+ years in retail management
• Tech Savvy: Moderate - comfortable with mobile apps and web interfaces
• Pain Points:
  • Manual inventory tracking is time-consuming
  • Difficulty predicting demand accurately
  • Frequent stockouts of popular items
  • Overstocking leads to waste and lost revenue

Key Workflows

Scenario 1A: Inventory Management (AI-Enhanced)

Actions:

1. Checks current inventory levels in store system
2. 🤖 AI Workflow: Predictive Analytics AI analyzes sales patterns, seasonal trends, and customer preferences
3. 🤖 AI Workflow: Automated Reordering AI suggests bulk orders with precise quantities
4. 🤖 AI Workflow: Smart Inventory Optimization prevents overstocking while ensuring availability
5. Places bulk order with AI-recommended quantities
6. 🤖 AI Workflow: AI tracks inventory performance and optimizes algorithms
7. Receives confirmation with AI-optimized delivery timeline

Conversation Example:

Sarah: "Check inventory for berry products"

MachBot: "I've analyzed your inventory. Based on current stock levels and 
sales patterns, I recommend:
- Berry Blast: Reorder 120 units (3 days until stockout)
- Strawberry Dream: Current stock optimal (15 days remaining)
- Mixed Berry: Reorder 80 units (5 days until stockout)

Would you like me to add these to your cart?"

Sarah: "Add Berry Blast and Mixed Berry"

MachBot: "Added to cart:
- Berry Blast: 120 units ($960)
- Mixed Berry: 80 units ($640)

Total: $1,600. Your usual delivery schedule applies (Wednesday).
Ready to place the order?"

Human-in-the-Loop (HITL):

• Trigger: Reorder value > $10,000 or unusual demand spikes
• Approver: Sarah confirms reorder decision
• Flow: inventory_manager → HITL approval → execute reorder

Outcome:

• ✅ Without AI: Stockouts or overstocking, lost sales, excess carrying costs
• ✅ With AI: Optimal inventory levels, improved turnover, reduced carrying costs

🥈 Priority 2: Daniel - B2B Retail Customer

Role: Procurement Manager at Target
Primary Goal: Secure trending products with optimal quantities and pricing

Profile

• Experience: 8+ years in procurement
• Tech Savvy: High - uses multiple B2B platforms daily
• Pain Points:
  • Difficulty predicting which products will succeed
  • Risk of over-ordering new products
  • Missing out on trending items
  • Inventory obsolescence

Key Workflows

Scenario 2A: Ordering Limited-Edition Product (AI-Enhanced)

Context: Daniel notices "Tropical Tide" is a trending new product that customers are excited about.

Actions:

1. Logs into FlavorFlux B2B portal
2. 🤖 AI Workflow: Demand forecasting AI predicts "Tropical Tide" success probability (85%)
3. 🤖 AI Workflow: AI suggests optimal order quantity (2,000 bottles) based on Target's customer base
4. Sees exclusive distributor promotion: "Pre-order now, get 15% off via Voucherify"
5. 🤖 AI Workflow: Smart inventory allocation ensures priority access
6. Places bulk order with AI-recommended quantity
7. System applies discount automatically with AI-optimized pricing

Conversation Example:

Daniel: "Tell me about Tropical Tide"

MachBot: "Tropical Tide is our newest seasonal flavor! 

📊 Product Insights:
- New tropical fruit blend
- Limited edition release
- Trending with Gen Z and Millennials

💡 AI Recommendation for Target stores:
- Optimal order: 2,000 units
- Based on your customer demographics and similar product performance
- Expected sell-through: 14-16 days

🎉 Exclusive Pre-Order Offer:
- 15% off wholesale price
- $6.80/unit (regularly $8.00)
- Priority shipping included

Would you like to add this to your cart?"

Daniel: "Add 2000 units"

MachBot: "Perfect! Added to cart:
- Tropical Tide: 2,000 units
- Unit price: $6.80 (15% off applied)
- Total: $13,600

You're securing this before the hype peaks. Ready to checkout?"

Human-in-the-Loop (HITL):

• Trigger: Pre-order value > $25,000 or new product categories
• Approver: Daniel confirms order quantity
• Flow: demand_forecaster → HITL approval → executor

Outcome:

• ✅ Without AI: Over/under-ordering, potential losses or stockouts
• ✅ With AI: Optimal quantities, better sell-through, competitive pricing secured

🥉 Priority 3: Emily - B2B Admin

Role: Trade Marketing & Promotions Manager at FlavorFlux
Primary Goal: Configure effective trade promotions quickly and accurately

Profile

• Experience: 10+ years in trade marketing
• Tech Savvy: High - manages multiple marketing platforms
• Pain Points:
  • Time-consuming campaign setup
  • Difficulty determining optimal discounts
  • Manual targeting is inefficient
  • Tracking campaign effectiveness is complex

Key Workflows

Scenario 3A: Setting Up a Seasonal Trade Promotion (AI-Enhanced)

Context: Emily wants to encourage big-box retailers (Costco, Target) to push the new Flux Series "Chai Charm."

Actions:

1. Logs into Commercetools to create new SKU bundle for "Chai Charm" 4-pack
2. 🤖 AI Workflow: AI analyzes historical campaign data and suggests optimal discount (10%) based on product performance
3. Sets up Voucherify campaign using AI-generated template
4. 🤖 AI Workflow: Smart targeting automatically links to high-performing retail accounts
5. Communicates via portal and sends personalized promo codes

Admin Interface Example:

Emily selects: "Create New Campaign"

MachBot suggests:
📊 Campaign Insights:
- Product: Chai Charm 4-pack
- AI Performance Score: 8.2/10
- Recommended Discount: 10-12% off wholesale
- Target Audience: Big-box retailers (Costco, Target, Whole Foods)
- Duration: 30 days

🎯 Smart Targeting:
Based on historical data, these accounts will respond best:
- Target (85% conversion rate on similar campaigns)
- Costco (78% conversion rate)
- Whole Foods (72% conversion rate)

💡 Suggested Campaign Structure:
- Name: "Chai Charm Launch - Q1 2025"
- Discount: 10% off wholesale ($7.20/unit)
- Minimum order: 3 cartons
- Code: CHAI-CHARM-Q1

Would you like to create this campaign with these settings?

Human-in-the-Loop (HITL):

• Trigger: Discounts > 15% or targeting new retailer segment
• Approver: Emily confirms campaign parameters
• Flow: CampaignService → HITL approval → publish campaign

Outcome:

• ✅ Without AI: Standard engagement, moderate volume
• ✅ With AI: Higher engagement, more volume, optimized targeting

AI Impact Comparison

Before vs. After AI Implementation

Overall Business Impact

• ⏱️ Time Savings: 60-70% reduction in manual tasks
• 📈 Revenue Growth: 25-35% improvement in key metrics
• 🛡️ Risk Reduction: 40-50% decrease in operational risks
• 😊 Customer Satisfaction: 30-40% improvement in user experience

AI Workflow Integration Points

🤖 1. Campaign Template AI (Emily's Scenario)

Location: Voucherify Campaign Builder integration
Workflow: Historical Campaign Data → Performance Analysis → Campaign Template Generation → Auto-Setup in Voucherify
Impact: Faster campaign creation, higher engagement through AI-optimized targeting

Technologies:

• AWS Bedrock for analysis
• LangGraph for workflow orchestration
• Voucherify MCP for campaign creation

🤖 2. Demand Forecasting AI (Daniel's Scenario)

Location: Commercetools product catalog + sales analytics
Workflow: Historical Sales Data → Demand Prediction → Inventory Allocation → Pre-order Optimization
Impact: Reduced obsolete inventory, better sell-through rates

Technologies:

• AWS Forecast for time-series prediction
• Commercetools for sales data
• LangGraph for decision routing

🤖 3. Predictive Reordering AI (Sarah's Scenario)

Location: Inventory management system + sales analytics
Workflow: Sales Data → Demand Forecasting → Automated Reorder Suggestions → Inventory Optimization
Impact: Reduced stockouts, reduced overstocking, improved inventory turnover

Technologies:

• AWS Forecast for demand prediction
• Commercetools for sales data
• Redis for caching predictions

Conversation Patterns

Product Search

User: "Show me berry products"
Bot: [Lists berry products with AI-ranked relevance]

User: "Which ones are selling best?"
Bot: [Shows top sellers with sales data and trends]

Cart Management

User: "Add 50 Berry Blast to my cart"
Bot: "Added 50 units of Berry Blast ($400). Your cart total is now $1,240."

User: "Show my cart"
Bot: [Displays cart with quantities, prices, and applicable promotions]

Order Placement

User: "Place order"
Bot: "Review your order:
- Berry Blast: 50 units ($400)
- Tropical Tide: 30 units ($240)
Subtotal: $640
Discount (10% bulk): -$64
Total: $576

Confirm to place order?"

User: "Confirm"
Bot: "Order placed! Order #12345. Expected delivery: Wednesday, Nov 6."

Product Disambiguation

User: "Add 100 strawberry to cart"
Bot: "I found multiple strawberry products:
1. Strawberry Dream (500ml) - $8.00/unit
2. Strawberry Blast (350ml) - $6.50/unit
3. Strawberry-Banana Mix (500ml) - $8.50/unit

Which would you like?"

User: "Option 1"
Bot: "Added 100 units of Strawberry Dream ($800) to your cart."

Success Metrics

User Experience Metrics

• High order completion rate with minimal user friction
• Fast order processing with streamlined workflows
• Strong user satisfaction with AI-powered recommendations
• Effective error recovery and user guidance

Business Metrics

• Strong average order values for FlavorFlux products
• Good acceptance of AI-suggested upsells and seasonal products
• Low cart abandonment with smooth checkout experience
• Comprehensive performance tracking across all product categories

FlavorFlux-Specific Metrics

• Strong adoption of community-voted products
• Clear seasonal ordering patterns and trends
• High cross-category ordering behavior among customers
• Strong engagement with community-driven brand content

Next Steps

• Architecture - Understand the technical implementation
• Backend Setup - Set up the AI agent backend
• Frontend Setup - Build the user interface
• Deployment - Deploy to production