Fix industry field extraction to show actual industries

- Add explicit **Industry:** field to all project READMEs (Days 1-10)
- Update README updater to extract from **Industry:** field instead of stakeholder role
- Replace stakeholder roles with actual industry sectors:
  * Day 01: Marketing/Advertising (not "Marketing consultant")
  * Day 02: Creator Economy/Social Media
  * Day 03: Legal/Compliance (not "Legal/Compliance Team")
  * Day 04: Crypto/Blockchain (not "Blockchain/Crypto Analyst")
  * Day 05: Cultural Heritage/Museums (not "Data Analyst")
  * Day 06: SaaS/Software (not "C-level")
  * Day 07: Hospitality/Travel (not "Pousada Owner")
  * Day 08: SaaS/Software (not "MBA, Strategy")
  * Day 09: Hospitality/Property Management (not "Property Manager")
  * Day 10: Wealth Management/Finance (not "Wealth Planning Specialist")

Result: Main README now displays actual industry sectors for better portfolio categorization.

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>

Author: raphaela-nawa

README.md

@@ -23,16 +23,16 @@ Each one ships with full code and documentation.
 
 | Day | Pillar | Project | Industry | Status | Code |
 |-----|--------|---------|----------|--------|------|
-| 1 | Ingestion | GA4 + Google Ads → BigQuery Pipeline | Marketing consultant | ✅ Complete | [Day 01](./day01) |
-| 2 | Ingestion | Creator Intelligence System | TBD | ✅ Complete | [Day 02](./day02) |
-| 3 | Ingestion | GDPR Lead Ingestion Pipeline | Legal/Compliance Team | ✅ Complete | [Day 03](./day03) |
-| 4 | Ingestion | Cardano Blockchain Transparency Pipeline | Blockchain/Crypto Analyst | ✅ Complete | [Day 04](./day04) |
-| 5 | Ingestion | Museu Ipiranga Cultural Data Pipeline | Paula (Cultural Data Analyst) | ✅ Complete | [Day 05](./day05) |
-| 6 | Modeling | SaaS Health Metrics Foundation | SaaS Executive (C-level) | ✅ Complete | [Day 06](./day06) |
-| 7 | Modeling | Hospitality LTV & Cohort Model | Carol (Pousada Owner) | ✅ Complete | [Day 07](./day07) |
-| 8 | Modeling | SaaS Growth Funnel & Cohort Analysis (dbt) | Patrick (MBA, Strategy) | ✅ Complete | [Day 08](./day08) |
-| 9 | Modeling | Property Operations Data Warehouse (dbt) | Jo (Independent Property Manager) | ✅ Complete | [Day 09](./day09) |
-| 10 | Modeling | Family Office Asset Management Data Warehouse | Rafael (Cross-Border Wealth Planning Specialist) | ✅ Complete | [Day 10](./day10) |
+| 1 | Ingestion | GA4 + Google Ads → BigQuery Pipeline | Marketing/Advertising | ✅ Complete | [Day 01](./day01) |
+| 2 | Ingestion | Creator Intelligence System | Creator Economy/Social Media | ✅ Complete | [Day 02](./day02) |
+| 3 | Ingestion | GDPR Lead Ingestion Pipeline | Legal/Compliance | ✅ Complete | [Day 03](./day03) |
+| 4 | Ingestion | Cardano Blockchain Transparency Pipeline | Crypto/Blockchain | ✅ Complete | [Day 04](./day04) |
+| 5 | Ingestion | Museu Ipiranga Cultural Data Pipeline | Heritage/Museums | ✅ Complete | [Day 05](./day05) |
+| 6 | Modeling | SaaS Health Metrics Foundation | SaaS/Software | ✅ Complete | [Day 06](./day06) |
+| 7 | Modeling | Hospitality LTV & Cohort Model | Hospitality/Travel | ✅ Complete | [Day 07](./day07) |
+| 8 | Modeling | SaaS Growth Funnel & Cohort Analysis (dbt) | SaaS/Software | ✅ Complete | [Day 08](./day08) |
+| 9 | Modeling | Property Operations Data Warehouse (dbt) | Hospitality/Property Management | ✅ Complete | [Day 09](./day09) |
+| 10 | Modeling | Family Office Asset Management Data Warehouse | Wealth Management/Finance | ✅ Complete | [Day 10](./day10) |
 | 11 | Orchestration | TBD | TBD | 🚧 Planned | [Day 11](./day11) |
 | 12 | Orchestration | TBD | TBD | 🚧 Planned | [Day 12](./day12) |
 | 13 | Orchestration | TBD | TBD | 🚧 Planned | [Day 13](./day13) |

common/utils/update_readme.py

@@ -134,20 +134,12 @@ def scan_project(self, day: int) -> ProjectInfo:
 
                 # Extract industry (look for various patterns)
                 industry_patterns = [
-                    # Pattern 1: **For:** Role/Industry | (highest priority, new template format)
-                    r'\*\*For:\*\*\s*(.+?)\s*\|',
-                    # Pattern 2: **For:** Name (Role/Industry)
-                    r'\*\*For:\*\*\s*[^(]+\(([^)]+)\)',
-                    # Pattern 3: **Stakeholder:** Name - Role/Industry
-                    r'\*\*Stakeholder:\*\*\s*[^-]+-\s*([^(]+?)(?:\s+who\s+|$)',
-                    # Pattern 4: **Industry:** or **Industry **
-                    r'\*\*Industry[:\s]+\*\*\s*(.+)',
-                    # Pattern 5: **Built For:** ... **Role/Context:**
-                    r'\*\*Built For[:\s]+\*\*[^\n]*\n\*\*Role/Context[:\s]+\*\*\s*(.+)',
-                    # Pattern 6: Table format
+                    # Pattern 1: **Industry:** Explicit field (highest priority)
+                    r'\*\*Industry:\*\*\s*([^|\n]+)',
+                    # Pattern 2: **For:** ... | **Industry:** ...
+                    r'\*\*Industry:\*\*\s*(.+?)\s*\|',
+                    # Pattern 3: Table format
                     r'\|\s*\d+\s*\|\s*\w+\s*\|\s*[^|]+\|\s*(.+?)\s*\|',
-                    # Pattern 7: One-line pitch or business problem with industry context
-                    r'\*\*Business Problem:\*\*\s*([^.]+)',
                 ]
                 for pattern in industry_patterns:
                     industry_match = re.search(pattern, readme_content, re.IGNORECASE)

day01/README.md

@@ -2,6 +2,7 @@
 
 **Project 1A - Ingestion Pillar**
 **Stakeholder:** Daud - Marketing consultant who needs automated GA4 + Google Ads reports for agency clients
+**Industry:** Marketing/Advertising
 
 ## 📋 Overview
 

day02/README.md

@@ -2,6 +2,8 @@
 
 **Instagram Business Analytics & Growth Intelligence Platform**
 
+**Industry:** Creator Economy/Social Media
+
 An end-to-end analytics system for Instagram creators, built to help a 100K-follower account reach 200K in 6 months through data-driven insights and AI-powered recommendations.
 
 ---

day03/README.md

@@ -14,7 +14,7 @@
 
 **Business Impact:** Automated compliance enforcement reduces legal risk and ensures 100% of leads have documented consent status and retention dates.
 
-**For:** Legal/Compliance Team | **Time:** 3 hours | **Status:** ✅ Complete
+**For:** Legal/Compliance Team | **Industry:** Legal/Compliance | **Time:** 3 hours | **Status:** ✅ Complete
 
 ---
 

day04/README.md

@@ -14,7 +14,7 @@
 
 **Business Impact:** Enables data-driven verification of blockchain values - decentralization proof (3000 pools vs Bitcoin's 5), accessibility proof (avg $0.17 fees vs Ethereum's $5-50), and real adoption metrics.
 
-**For:** Blockchain/Crypto Analyst | **Time:** 3 hours | **Status:** ✅ Complete
+**For:** Blockchain/Crypto Analyst | **Industry:** Crypto/Blockchain | **Time:** 3 hours | **Status:** ✅ Complete
 
 ---
 

day05/README.md

@@ -27,7 +27,7 @@
 
 **Business Impact:** Reduced artifact research time from 4+ hours of manual listening to 5 minutes of querying structured data, enabling cultural metadata enrichment and content-catalog linking.
 
-**For:** Paula (Cultural Data Analyst) | **Time:** 3 hours | **Status:** ✅ Complete
+**For:** Paula (Cultural Data Analyst) | **Industry:** Cultural Heritage/Museums | **Time:** 3 hours | **Status:** ✅ Complete
 
 ---
 

day06/README.md

@@ -27,7 +27,7 @@
 
 **Business Impact:** Reduced monthly reporting time from 4 hours (manual Excel) to 5 minutes (automated SQL queries), enabling weekly instead of quarterly reviews of key SaaS metrics.
 
-**For:** SaaS Executive (C-level) | **Time:** 3 hours | **Status:** ✅ Complete
+**For:** SaaS Executive (C-level) | **Industry:** SaaS/Software | **Time:** 3 hours | **Status:** ✅ Complete
 
 ---
 

day07/README.md

@@ -8,7 +8,7 @@
 
 **Business Impact:** Identified that top 10% of guests generate 3-5x more revenue, with winter cohorts showing 25% higher retention than summer cohorts. System enables data-driven decisions on marketing budget allocation and VIP engagement.
 
-**For:** Carol (Pousada Owner) | **Time:** 3 hours | **Status:** ✅ Complete
+**For:** Carol (Pousada Owner) | **Industry:** Hospitality/Travel | **Time:** 3 hours | **Status:** ✅ Complete
 
 ---
 

day08/README.md

@@ -27,7 +27,7 @@
 
 **Business Impact:** Automated cohort analysis reduces weekly reporting time from 4 hours (manual SQL + spreadsheets) to 2 minutes (single dbt run), enabling daily instead of weekly growth reviews.
 
-**For:** Patrick (MBA, Strategy) | **Time:** 3 hours | **Status:** ✅ Complete
+**For:** Patrick (MBA, Strategy) | **Industry:** SaaS/Software | **Time:** 3 hours | **Status:** ✅ Complete
 
 ---