bakery-ia/ONBOARDING_UNIFICATION_PLAN.md

Unified Onboarding Wizard - Master Plan

Executive Summary

This document outlines the strategy to merge the existing AI-powered onboarding (sales data upload + ML training) with the new comprehensive setup wizard (suppliers, inventory, recipes, quality, team) into a single, intelligent, personalized onboarding experience.

---

1. Current State Analysis

1.1 Existing Onboarding (Smart Inventory Path)

Flow:

Registration → Tenant Setup → Sales Upload → AI Classification →
Inventory Creation → ML Training → Completion

Strengths: ✅ AI-powered product recommendations (85%+ confidence) ✅ Real-time ML training with WebSocket progress ✅ Multi-format data import (CSV, JSON, Excel) ✅ Smart inventory creation from sales data ✅ Backend progress persistence

Weaknesses: ❌ No supplier management (auto-completed) ❌ No recipe creation ❌ No quality standards ❌ No team management ❌ No bakery type personalization ❌ Limited to finished products only

1.2 New Setup Wizard (Manual Path)

Flow:

Welcome → Suppliers → Inventory → Recipes → Quality → Team →
Review → Completion

Strengths: ✅ Comprehensive data entry (all entities) ✅ Template system for quick setup ✅ Smart defaults and auto-suggestions ✅ Detailed review before completion ✅ Engaging completion experience

Weaknesses: ❌ No AI assistance ❌ No sales data integration ❌ No ML training ❌ No bakery type personalization ❌ More time-consuming for users with existing data

---

2. Gap Analysis

2.1 Missing Features

Feature	Existing	New Wizard	Priority
Bakery Type Selection	❌	❌	🔴 Critical
AI Product Recommendations	✅	❌	🔴 Critical
Sales Data Upload	✅	❌	🔴 Critical
Supplier Management	❌ (auto)	✅	🟡 High
Recipe Creation	❌	✅	🟡 High
Quality Standards	❌	✅	🟢 Medium
Team Management	❌	✅	🟢 Medium
ML Training	✅	❌	🔴 Critical
Spanish i18n	⚠️ Partial	❌	🔴 Critical
Analytics Tracking	❌	❌	🟡 High
Guided Tours	❌	❌	🟢 Medium

2.2 Bakery Type Impact

Different bakery types need different onboarding paths:

Bakery Type	Needs Recipes	Needs Suppliers	Primary Inventory	Production
Production Bakery	✅ Yes	✅ Yes	Raw ingredients	Full production
Retail/Finishing	❌ No*	✅ Yes	Finished/par-baked	Simple baking
Mixed	✅ Yes	✅ Yes	Both	Both

*Retail bakeries need production processes (simpler than recipes) for par-baked items

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3. Unified Wizard Architecture

3.1 High-Level Flow

┌─────────────────────────────────────────────────────────────────┐
│                    PHASE 1: DISCOVERY                            │
│  1. Welcome & Bakery Type Selection                             │
│  2. Data Source Choice (AI-assisted vs Manual)                  │
└─────────────────────────────────────────────────────────────────┘
                            ↓
              ┌─────────────┴─────────────┐
              ↓                           ↓
┌──────────────────────────┐  ┌──────────────────────────┐
│   AI-ASSISTED PATH       │  │   MANUAL PATH            │
│                          │  │                          │
│ 3. Upload Sales Data     │  │ 3. (Skip to Core)        │
│ 4. AI Analysis           │  │                          │
│ 5. Review Suggestions    │  │                          │
└──────────────────────────┘  └──────────────────────────┘
              ↓                           ↓
              └─────────────┬─────────────┘
                            ↓
┌─────────────────────────────────────────────────────────────────┐
│                    PHASE 2: CORE SETUP                           │
│  6. Suppliers Setup                                              │
│  7. Inventory Setup (enhanced with AI if available)             │
│  8. Recipes Setup (if Production/Mixed) OR                      │
│     Production Processes (if Retail/Finishing)                   │
└─────────────────────────────────────────────────────────────────┘
                            ↓
┌─────────────────────────────────────────────────────────────────┐
│                  PHASE 3: ADVANCED FEATURES                      │
│  9. Quality Standards (optional)                                 │
│  10. Team Members (optional)                                     │
└─────────────────────────────────────────────────────────────────┘
                            ↓
┌─────────────────────────────────────────────────────────────────┐
│                  PHASE 4: ML & FINALIZATION                      │
│  11. ML Training (real-time progress, skippable after 2min)    │
│  12. Review & Summary                                            │
│  13. Completion & Next Steps                                     │
└─────────────────────────────────────────────────────────────────┘

3.2 Step Definitions

Phase 1: Discovery (NEW)

Step 1: Welcome & Bakery Type Selection

• Welcome message explaining the wizard
• Bakery type selector (new requirement):
  • 🥖 Production Bakery - "Producimos desde cero"
  • 🛒 Retail/Finishing Bakery - "Recibimos productos terminados/semi-elaborados"
  • 🏭 Mixed Bakery - "Producción + Venta de productos terminados"
• Explain what each type means
• Store in tenant metadata
• Determines conditional steps

Step 2: Data Source Choice

• Option A: Upload sales data (AI-assisted)
  • "Tengo datos históricos de ventas"
  • Faster setup (~5 min)
  • AI recommendations
• Option B: Start from scratch (Manual)
  • "Empezar manualmente"
  • More control
  • Use templates

Phase 2a: AI-Assisted Path (IF user uploads data)

Step 3: Upload Sales Data (from existing onboarding)

• Upload CSV/JSON/Excel
• Show preview
• Validate format
• Component: UploadSalesDataStep (reuse existing)

Step 4: AI Analysis & Recommendations (from existing onboarding)

• Show loading animation
• AI classifies products
• Display suggestions with confidence scores
• Component: Part of UploadSalesDataStep (reuse existing)

Step 5: Review & Confirm Products (from existing onboarding)

• User reviews AI suggestions
• Can edit names, categories, quantities
• Select which items to create
• Component: Part of UploadSalesDataStep (reuse existing)

Phase 2b: Core Setup (Common for all paths)

Step 6: Suppliers Setup (enhanced from new wizard)

• Add supplier information
• Enhancement: Pre-populate supplier suggestions based on inventory
• Component: SuppliersSetupStep (from new wizard)
• Minimum: 1 supplier

Step 7: Inventory Setup (enhanced from new wizard)

• If AI path: Show AI-created items + ability to add more
• If manual path: Show templates + manual entry
• Conditional based on bakery type:
  • Production: Ingredients (flour, yeast, etc.)
  • Retail: Finished products (croissants, bread, etc.)
  • Mixed: Both
• Component: InventorySetupStep (from new wizard, enhanced)
• Minimum: 3 items

Step 8a: Recipes Setup (IF Production or Mixed)

• Create production recipes
• Recipe templates (baguette, croissant, etc.)
• Link ingredients to finished products
• Component: RecipesSetupStep (from new wizard)
• Minimum: 1 recipe

Step 8b: Production Processes (IF Retail/Finishing)

• NEW COMPONENT NEEDED
• Simple transformation processes for par-baked products
• Example: "Hornear a 180°C durante 15 minutos"
• No complex recipes, just baking instructions
• Component: ProductionProcessesStep (new)
• Minimum: 1 process

Phase 3: Advanced Features (Optional)

Step 9: Quality Standards (from new wizard, optional)

• Define quality check templates
• Component: QualitySetupStep (from new wizard)
• Skippable

Step 10: Team Members (from new wizard, optional)

• Add team member emails and roles
• Component: TeamSetupStep (from new wizard)
• Skippable

Phase 4: ML & Finalization

Step 11: ML Training (from existing onboarding)

• Auto-start training
• Real-time progress via WebSocket
• Skip option after 2 minutes
• Component: MLTrainingStep (reuse existing)
• Required for AI features

Step 12: Review & Summary (from new wizard)

• Show all configured data
• Stats and metrics
• Component: ReviewSetupStep (from new wizard)
• Always shown

Step 13: Completion (from new wizard, enhanced)

• Celebration
• Next steps
• Guided tour option
• Component: CompletionStep (from new wizard)
• Final step

---

4. Conditional Step Logic

4.1 Step Visibility Matrix

Step	Production	Retail	Mixed	AI Path	Manual
1. Welcome & Type	✅	✅	✅	✅	✅
2. Data Choice	✅	✅	✅	✅	✅
3. Upload Data	✅	✅	✅	✅	❌
4. AI Analysis	✅	✅	✅	✅	❌
5. Review Products	✅	✅	✅	✅	❌
6. Suppliers	✅	✅	✅	✅	✅
7. Inventory	✅	✅	✅	✅	✅
8a. Recipes	✅	❌	✅	✅	✅
8b. Processes	❌	✅	⚠️*	✅	✅
9. Quality	✅	✅	✅	✅	✅
10. Team	✅	✅	✅	✅	✅
11. ML Training	✅	✅	✅	✅	✅**
12. Review	✅	✅	✅	✅	✅
13. Completion	✅	✅	✅	✅	✅

*Mixed bakeries can optionally add production processes **Manual path users can skip ML training if no sales data uploaded

4.2 Implementation Strategy

interface WizardContext {
  bakeryType: 'production' | 'retail' | 'mixed';
  dataSource: 'ai' | 'manual';
  hasSalesData: boolean;
  aiSuggestions?: ProductSuggestion[];
}

const getVisibleSteps = (context: WizardContext): StepConfig[] => {
  const steps = [
    welcomeStep,
    dataChoiceStep,
  ];

  if (context.dataSource === 'ai') {
    steps.push(uploadStep, aiAnalysisStep, reviewProductsStep);
  }

  steps.push(suppliersStep, inventoryStep);

  if (context.bakeryType === 'production' || context.bakeryType === 'mixed') {
    steps.push(recipesStep);
  }

  if (context.bakeryType === 'retail' || context.bakeryType === 'mixed') {
    steps.push(productionProcessesStep);
  }

  steps.push(qualityStep, teamStep);

  if (context.hasSalesData) {
    steps.push(mlTrainingStep);
  }

  steps.push(reviewStep, completionStep);

  return steps;
};

---

5. Implementation Phases

Phase 6: Foundation & Integration (Week 1-2)

Tasks:

1. ✅ Analyze existing onboarding (COMPLETE)
2. Create BakeryTypeSelectionStep component
3. Create DataSourceChoiceStep component
4. Create ProductionProcessesStep component (for retail bakeries)
5. Create wizard context system for conditional logic
6. Merge step dependencies in backend
7. Update progress tracking to support conditional steps

Deliverables:

• New step components (3)
• Wizard context provider
• Conditional step visibility logic
• Updated backend dependencies

Phase 7: Spanish Translations (Week 2)

Tasks:

1. Create comprehensive Spanish translations for ALL steps
2. Translate existing onboarding strings
3. Translate new setup wizard strings
4. Add translation keys for new components
5. Test language switching
6. Update default language to Spanish

Files to Update:

• /frontend/public/locales/es/setup_wizard.json
• /frontend/public/locales/es/onboarding.json
• /frontend/public/locales/es/common.json
• /frontend/public/locales/es/inventory.json
• /frontend/public/locales/es/recipes.json
• /frontend/public/locales/es/quality.json

Deliverables:

• Complete Spanish translation files (1000+ strings)
• Language switcher in wizard
• RTL support (future-proofing)

Phase 8: Analytics & Tracking (Week 3)

Tasks:

1. Create analytics tracking service
2. Track wizard start/completion events
3. Track step-by-step progress
4. Track drop-off points
5. Track time spent per step
6. Create analytics dashboard
7. Implement A/B testing framework

Events to Track:

// Wizard level
- wizard_started { bakery_type, data_source }
- wizard_completed { duration, steps_completed }
- wizard_abandoned { last_step, duration }

// Step level
- step_started { step_name, timestamp }
- step_completed { step_name, duration }
- step_skipped { step_name }

// Interaction level
- template_used { template_name, step }
- ai_suggestion_accepted { product_name, confidence }
- ai_suggestion_rejected { product_name, confidence }

Backend:

• New table: wizard_analytics
• New API endpoints for tracking
• Dashboard queries for metrics

Deliverables:

• Analytics tracking service
• Dashboard with metrics
• Reports: completion rate, avg time, drop-off analysis

Phase 9: Guided Tours (Week 3-4)

Tasks:

1. Create tour system (similar to demo tour)
2. Define tour steps for each major feature
3. Create tour triggers (post-onboarding)
4. Add "skip tour" option
5. Store tour completion state
6. Create tour manager component

Tours to Create:

1. Dashboard Tour - Overview of main dashboard
2. Production Tour - How to create production batches
3. Inventory Tour - Managing stock levels
4. Recipes Tour - Creating and editing recipes
5. Analytics Tour - Understanding reports

Technology:

• Reuse existing demo tour infrastructure
• Use react-joyride or similar library
• Store state in localStorage + backend

Deliverables:

• Tour system framework
• 5 feature tours
• Tour completion tracking

Phase 10: Enhanced Features (Week 4-5)

Tasks:

10.1 Smart Inventory Enhancement

• Show AI-suggested items prominently if AI path
• Allow editing AI suggestions before creation
• Show confidence scores
• Pre-fill costs based on sales data

10.2 Supplier Suggestions

• Based on inventory categories, suggest suppliers
• "For your flour, you might need a grain supplier"
• Pre-fill common suppliers in region

10.3 Recipe Templates Enhancement

• Add more recipe templates (20+ recipes)
• Categorize by bakery type
• Show only relevant templates

10.4 Production Processes

• Create library of common processes
• "Bake croissants", "Proof bread", "Glaze pastries"
• Simple time/temp instructions

Deliverables:

• Enhanced inventory step with AI integration
• Supplier suggestion system
• Expanded recipe library
• Production processes library

Phase 11: Testing & Polish (Week 5-6)

Tasks:

1. End-to-end testing all paths
2. Test conditional logic
3. Test AI integration
4. Test ML training flow
5. Performance optimization
6. Accessibility audit
7. Mobile responsiveness testing
8. Spanish translation review
9. User acceptance testing
10. Bug fixes and polish

Test Scenarios:

• Production bakery + AI path
• Production bakery + Manual path
• Retail bakery + AI path
• Retail bakery + Manual path
• Mixed bakery + AI path
• Mixed bakery + Manual path

Deliverables:

• Test results report
• Bug fixes
• Performance improvements
• Final polish

---

6. Technical Specifications

6.1 New Components

BakeryTypeSelectionStep.tsx

interface BakeryType {
  id: 'production' | 'retail' | 'mixed';
  name: string;
  description: string;
  icon: ReactNode;
  features: string[];
  examples: string[];
}

const bakeryTypes: BakeryType[] = [
  {
    id: 'production',
    name: 'Panadería de Producción',
    description: 'Producimos desde cero usando ingredientes',
    icon: <BreadIcon />,
    features: [
      'Gestión de recetas',
      'Control de ingredientes',
      'Producción completa'
    ],
    examples: ['Pan artesanal', 'Bollería', 'Repostería']
  },
  {
    id: 'retail',
    name: 'Panadería de Reventa/Acabado',
    description: 'Recibimos productos terminados o semi-elaborados',
    icon: <StorefrontIcon />,
    features: [
      'Gestión de productos terminados',
      'Procesos de horneado simple',
      'Gestión de proveedores'
    ],
    examples: ['Hornear precocidos', 'Venta de productos terminados']
  },
  {
    id: 'mixed',
    name: 'Panadería Mixta',
    description: 'Combinamos producción propia y reventa',
    icon: <HybridIcon />,
    features: [
      'Todas las funcionalidades',
      'Máxima flexibilidad',
      'Gestión completa'
    ],
    examples: ['Producción + Reventa']
  }
];

DataSourceChoiceStep.tsx

interface DataSource {
  id: 'ai' | 'manual';
  name: string;
  description: string;
  duration: string;
  icon: ReactNode;
  benefits: string[];
}

const dataSources: DataSource[] = [
  {
    id: 'ai',
    name: 'Subir datos de ventas (Recomendado)',
    description: 'Sube tus datos históricos y deja que la IA configure tu inventario',
    duration: '~5 minutos',
    icon: <AIIcon />,
    benefits: [
      'Configuración automática',
      'Recomendaciones inteligentes',
      'Análisis de ventas',
      'Más rápido'
    ]
  },
  {
    id: 'manual',
    name: 'Configuración manual',
    description: 'Configura todo desde cero usando plantillas',
    duration: '~15 minutos',
    icon: <ManualIcon />,
    benefits: [
      'Control total',
      'Sin datos históricos necesarios',
      'Plantillas incluidas'
    ]
  }
];

ProductionProcessesStep.tsx

interface ProductionProcess {
  id: string;
  product_id: string;
  process_name: string;
  description: string;
  steps: ProcessStep[];
  duration_minutes: number;
  temperature_celsius?: number;
}

interface ProcessStep {
  order: number;
  instruction: string;
  duration_minutes: number;
  temperature_celsius?: number;
}

// Example processes
const processTemplates = [
  {
    name: 'Hornear Croissants Precocidos',
    steps: [
      { order: 1, instruction: 'Precalentar horno a 180°C', duration_minutes: 10 },
      { order: 2, instruction: 'Hornear croissants', duration_minutes: 15, temperature_celsius: 180 },
      { order: 3, instruction: 'Enfriar', duration_minutes: 5 }
    ],
    duration_minutes: 30,
    temperature_celsius: 180
  }
];

6.2 Wizard Context System

interface WizardContext {
  // Discovery
  bakeryType?: 'production' | 'retail' | 'mixed';
  dataSource?: 'ai' | 'manual';

  // AI Path
  salesDataUploaded: boolean;
  aiSuggestions: ProductSuggestion[];
  selectedSuggestions: string[];

  // Setup Data
  suppliers: Supplier[];
  inventory: InventoryItem[];
  recipes: Recipe[];
  processes: ProductionProcess[];
  qualityTemplates: QualityTemplate[];
  teamMembers: TeamMember[];

  // ML
  mlTrainingJobId?: string;
  mlTrainingStatus?: 'pending' | 'in_progress' | 'completed' | 'failed';
  mlTrainingProgress?: number;
}

const WizardContextProvider: React.FC = ({ children }) => {
  const [context, setContext] = useState<WizardContext>({
    salesDataUploaded: false,
    aiSuggestions: [],
    selectedSuggestions: [],
    suppliers: [],
    inventory: [],
    recipes: [],
    processes: [],
    qualityTemplates: [],
    teamMembers: []
  });

  return (
    <WizardContext.Provider value={{ context, setContext }}>
      {children}
    </WizardContext.Provider>
  );
};

6.3 Backend Changes

New API Endpoints:

# Bakery type
PUT /api/v1/tenants/{tenant_id}/settings
Body: { bakery_type: 'production' | 'retail' | 'mixed' }

# Production processes (new)
POST /api/v1/tenants/{tenant_id}/production/processes
GET /api/v1/tenants/{tenant_id}/production/processes
PUT /api/v1/tenants/{tenant_id}/production/processes/{id}
DELETE /api/v1/tenants/{tenant_id}/production/processes/{id}

# Analytics
POST /api/v1/analytics/wizard/event
Body: { event_type, step_name, metadata }

GET /api/v1/analytics/wizard/metrics
Response: { completion_rate, avg_duration, drop_off_points }

New Database Tables:

-- Bakery type in tenants
ALTER TABLE tenants ADD COLUMN bakery_type VARCHAR(50);
ALTER TABLE tenants ADD COLUMN data_source VARCHAR(50);

-- Production processes
CREATE TABLE production_processes (
    id UUID PRIMARY KEY,
    tenant_id UUID REFERENCES tenants(id),
    product_id UUID REFERENCES inventory_items(id),
    process_name VARCHAR(200),
    description TEXT,
    steps JSONB,
    duration_minutes INTEGER,
    temperature_celsius INTEGER,
    created_at TIMESTAMP,
    updated_at TIMESTAMP
);

-- Wizard analytics
CREATE TABLE wizard_analytics (
    id UUID PRIMARY KEY,
    user_id UUID REFERENCES users(id),
    tenant_id UUID REFERENCES tenants(id),
    event_type VARCHAR(100),
    step_name VARCHAR(100),
    metadata JSONB,
    created_at TIMESTAMP
);

CREATE INDEX idx_wizard_analytics_user ON wizard_analytics(user_id);
CREATE INDEX idx_wizard_analytics_event ON wizard_analytics(event_type);

6.4 Translation Structure (Spanish)

File: /frontend/public/locales/es/setup_wizard.json

{
  "steps": {
    "bakery_type": {
      "title": "Tipo de Panadería",
      "description": "Selecciona el tipo de panadería que tienes",
      "production": "Panadería de Producción",
      "retail": "Panadería de Reventa/Acabado",
      "mixed": "Panadería Mixta"
    },
    "data_choice": {
      "title": "Fuente de Datos",
      "description": "¿Cómo quieres configurar tu inventario?",
      "ai": "Subir datos de ventas (IA)",
      "manual": "Configuración manual"
    },
    "suppliers": {
      "title": "Proveedores",
      "description": "Tus proveedores de ingredientes y materiales",
      "add_supplier": "Agregar Proveedor",
      "minimum_required": "Mínimo 1 proveedor requerido"
    }
    // ... 500+ more strings
  }
}

---

7. Success Metrics

7.1 Completion Rate Targets

Metric	Current	Target	Timeline
Wizard Start Rate	N/A	90%	Phase 6
Wizard Completion Rate	~60%	85%	Phase 11
AI Path Success Rate	~75%	90%	Phase 10
Manual Path Success Rate	~50%	70%	Phase 10
Avg Completion Time (AI)	N/A	5-7 min	Phase 10
Avg Completion Time (Manual)	N/A	10-15 min	Phase 10
Drop-off at ML Training	~30%	<10%	Phase 11

7.2 Analytics Dashboard

Metrics to Track:

• Total wizards started
• Total wizards completed
• Completion rate by bakery type
• Completion rate by data source
• Average time per step
• Drop-off points (heatmap)
• Most used templates
• AI suggestion acceptance rate
• ML training completion rate

Visualizations:

• Funnel chart (step-by-step completion)
• Time series (completions over time)
• Heatmap (drop-off points)
• Bar chart (bakery type distribution)
• Pie chart (AI vs Manual)

---

8. Timeline & Resources

Overall Timeline: 6 weeks

Phase	Duration	Dependencies	Resource Needs
Phase 6: Foundation	2 weeks	Analysis complete	1 senior dev, 1 mid dev
Phase 7: i18n	1 week	Phase 6	1 mid dev, 1 translator
Phase 8: Analytics	1 week	Phase 6	1 senior dev
Phase 9: Tours	1 week	Phase 6	1 mid dev
Phase 10: Enhancement	1 week	Phase 6, 7	1 senior dev, 1 mid dev
Phase 11: Testing	1 week	All phases	1 QA, 1 dev

Parallel Work:

• Phase 7 & 8 can run in parallel
• Phase 9 can start after Phase 6
• Phase 10 can start after Phase 7

Critical Path: Phase 6 → Phase 10 → Phase 11

---

9. Risk Analysis

9.1 Technical Risks

Risk	Probability	Impact	Mitigation
Backend API changes break existing flow	Medium	High	Comprehensive regression testing
WebSocket issues in ML training	Low	Medium	HTTP polling fallback (already exists)
Conditional logic complexity	Medium	Medium	Thorough unit testing, clear documentation
Translation quality issues	High	Low	Professional translator, native speaker review
Performance degradation	Low	Medium	Code splitting, lazy loading

9.2 User Experience Risks

Risk	Probability	Impact	Mitigation
Users confused by too many options	Medium	High	Clear UI, tooltips, guided help
AI path users miss manual options	Low	Medium	Always show "customize" option
Retail bakeries confused about recipes	Medium	High	Clear bakery type explanation, skip recipes
Users abandon during ML training	High	High	Skip option after 2 min (already exists)

---

10. Recommendations

10.1 Immediate Actions (Phase 6)

1. ✅ Start with bakery type selection - This is the foundation for everything
2. ✅ Reuse existing AI components - Don't reinvent the wheel
3. ✅ Create production processes step - Critical for retail bakeries
4. ✅ Build wizard context system - Enables conditional logic
5. ✅ Update backend dependencies - Support new step flow

10.2 Quick Wins

1. Spanish translations (Phase 7)

   • High impact, relatively easy
   • Primary language for target market
   • Can be done in parallel with Phase 6

2. Analytics tracking (Phase 8)

   • Essential for measuring success
   • Simple to implement
   • High value for product decisions

3. Guided tours (Phase 9)

   • Reduces support tickets
   • Improves user engagement
   • Can reuse existing demo tour code

10.3 Long-term Enhancements

1. Multi-language support - English, French, Portuguese
2. Video tutorials - Embedded help videos
3. Industry-specific templates - By region, bakery size
4. Advanced AI - Image recognition for products
5. Mobile app - Native mobile onboarding
6. Voice guidance - Accessibility feature

---

11. Next Steps

For Development Team:

1. Review this plan with stakeholders
2. Approve/adjust phases based on priorities
3. Assign resources (2 devs minimum)
4. Set up project tracking (Jira/Linear/etc.)
5. Create detailed tickets for Phase 6
6. Start Phase 6 implementation immediately

For Product Team:

1. Validate bakery type categories with users
2. Review analytics requirements with stakeholders
3. Prioritize translation quality (hire native speaker)
4. Plan user acceptance testing for Phase 11
5. Prepare marketing materials for launch

For Design Team:

1. Create mockups for new steps
2. Design bakery type selection UI
3. Design data source choice UI
4. Design production processes UI
5. Review Spanish translations for UX copy

---

12. Conclusion

The unified onboarding wizard will provide:

✅ Personalized experience based on bakery type ✅ AI-powered efficiency for users with sales data ✅ Manual control for users who prefer it ✅ Comprehensive setup covering all entities ✅ ML training integration for predictive features ✅ Spanish-first interface for primary market ✅ Analytics tracking for continuous improvement ✅ Guided tours for feature discovery

Estimated Impact:

• 85% completion rate (up from 60%)
• 5-15 min setup time (depending on path)
• 90% user satisfaction (measured via NPS)
• 40% reduction in support tickets (via guided tours)

This unified wizard will be a competitive advantage and a delightful user experience that sets the product apart in the market.

---

Document Version: 1.0 Last Updated: 2024-01-01 Author: Claude (AI Assistant) Status: Ready for Review