Sustainability Communications Framework

A strategic approach to translating complex sustainability compliance into actionable seller communications

Project Overview

This repository demonstrates a systematic approach to developing effective communications for sustainability compliance requirements, specifically designed for e-commerce marketplaces and selling partner ecosystems.

Problem Statement: Sustainability regulations like Extended Producer Responsibility (EPR) create complex compliance requirements that need to be communicated clearly to diverse, global seller communities.

Solution: A framework that combines content strategy, stakeholder analysis, and automated content optimisation to create scalable, personalised communications.

Course Learning Integration

As of February 17 2026, this repository is being enhanced through an official INAEM Environmental Management course (CEOE Aragón, 430 hours).

Learning documentation: See COURSE_PROGRESS.md for timeline and learning/ for detailed course notes and applied improvements to the framework.

Goal: Transform course knowledge into stronger, more technically-grounded sustainability communications solutions.

Project Status

Implemented & Maintained

• ✅ src/content_analyzer.py — Text analysis and complexity scoring (fully functional)
• 📚 learning/ — Course learning documentation & framework improvements (in progress during INAEM course)

In Development (Feb-Jun 2026)

• 🔄 src/stakeholder_mapper.py — Being developed based on course learnings
• 🔄 src/compliance_tracker.py — Being developed based on course learnings
• 🔄 src/message_optimizer.py — Planned for later phase
• 📋 /docs/ — To be populated with implementation learnings and case studies

Scaffolding / Planned

• 📋 /examples/ — Real-world case studies (pending practice placement)
• 📋 /data/ — To be enhanced with regulatory intelligence and personas
• 📋 requirements.txt — Will be updated as new dependencies are added

See COURSE_PROGRESS.md for detailed development timeline and milestone tracking.

Repository Structure

sustainability-communications-framework/
│
├── README.md                          # This file
├── requirements.txt                   # Python dependencies
│
├── src/
│   ├── content_analyzer.py           # Text analysis and complexity scoring
│   ├── stakeholder_mapper.py         # Seller segmentation and persona mapping
│   ├── message_optimizer.py          # Content adaptation and personalisation
│   └── compliance_tracker.py         # Regulation monitoring and alert system
│
├── data/
│   ├── sample_regulations/            # Example EPR texts for analysis
│   ├── seller_personas.json          # Stakeholder segmentation data
│   └── communication_templates/       # Base message templates
│
├── examples/
│   ├── epr_communication_strategy.md # Complete EPR communication plan
│   ├── crisis_response_framework.md  # Crisis communication templates
│   └── stakeholder_journey_map.md    # Seller communication touchpoint analysis
│
├── learning/                          # NEW- Environmental management course documentation 
│   ├── README.md                      # Learning index
│   ├── course_overview.md             # Course and objectives summary
│   ├── modules/
│   │   ├── MF1971_3_policies.md     # Normative and internal policies
│   │   ├── MF1972_3_specs.md         # Enviromental aspects
│   │   ├── MF1973_3_systems.md      # Management systems
│   │   ├── MF1974_3_prevention.md    # Risk prevention
│   ├── applied_learnings/             # How this course connects with this framework
│   │   ├── content_analyzer_improvements.md
│   │   ├── stakeholder_insights.md
│   │   └── regulatory_depth.md
│   └── work_in_progress/              # Daily notes, prompt ideas and learning reflections
│
├── docs/
│   ├── methodology.md                 # Strategic communication framework
│   ├── implementation_guide.md       # How to deploy in an enterprise environment
│   └── success_metrics.md           # KPIs and measurement framework
│
└── tests/
│   ├── test_content_analyzer.py
│   ├── test_stakeholder_mapper.py
│   └── test_message_optimizer.py
│
└── COURSE_PROGRESS.md                # Main timeline and milestone tracker
└── LICENSE                            # MIT License

Core Modules

1. Content Analyser (content_analyzer.py)

• Complexity Scoring: Analyses regulatory text for reading level, technical density
• Key Concept Extraction: Identifies critical compliance points requiring emphasis
• Translation Readiness: Flags content requiring localization considerations

2. Stakeholder Mapper (stakeholder_mapper.py)

• Seller Segmentation: Creates personas based on business size, category, experience level
• Communication Preferences: Maps preferred channels and content formats per segment
• Risk Assessment: Identifies high-risk sellers requiring priority communication

3. Message Optimiser (message_optimizer.py)

• Content Adaptation: Tailors message complexity and format to the audience segment
• Channel Optimisation: Adapts content for different communication channels
• Personalisation Engine: Creates targeted messaging based on seller profile

4. Compliance Tracker (compliance_tracker.py)

• Regulation Monitoring: Tracks changes in sustainability regulations across EU markets
• Impact Analysis: Assesses which seller segments are affected by new requirements
• Alert Prioritization: Creates tiered communication urgency levels

Strategic Framework

Phase 1: Discovery & Analysis

1. Regulatory Landscape Mapping

   • Identify current and upcoming sustainability requirements
   • Map regulatory complexity and seller impact
   • Create a compliance timeline and milestone tracking

2. Stakeholder Analysis

   • Segment seller base by compliance readiness and business characteristics
   • Identify communication preferences and channel effectiveness
   • Map seller journey from awareness to compliance

Phase 2: Content Strategy Development

1. Message Architecture

   • Core value proposition for compliance participation
   • Tiered messaging for different complexity levels
   • Cross-cultural adaptation guidelines

2. Channel Strategy

   • Omnichannel approach optimised for seller preferences
   • Crisis communication escalation protocols
   • Feedback loop integration for continuous improvement

Phase 3: Implementation & Optimisation

1. Campaign Development

   • Personalised communication sequences
   • A/B testing framework for message effectiveness
   • Performance tracking and sentiment analysis

2. Scale Management

   • Automated content generation for routine communications
   • Human oversight protocols for complex or sensitive situations
   • Integration with existing seller support systems

Key Innovation Features

AI-Assisted Content Creation

• Regulatory Text Simplification: Automatic translation of complex legal language
• Multilingual Optimization: Culture-aware content adaptation
• Dynamic Personalisation: Real-time message customisation based on seller behaviour

Predictive Communication Planning

• Compliance Risk Modeling: Identify sellers likely to face challenges
• Proactive Engagement: Initiate communications before issues arise
• Success Probability Scoring: Optimize resource allocation for maximum impact

Crisis Response Integration

• Automated Escalation: Trigger crisis protocols based on sentiment analysis
• Rapid Response Templates: Pre-approved messaging for common scenarios
• Stakeholder Coordination: Cross-functional team communication frameworks

Success Metrics & KPIs

Awareness Metrics

• Reach: Number of sellers receiving communications
• Engagement: Open rates, click-through rates, content interaction
• Comprehension: Survey scores on regulatory understanding

Action Metrics

• Compliance Adoption: Percentage of sellers taking required actions
• Timeline Performance: Seller compliance vs. regulatory deadlines
• Support Reduction: Decrease in compliance-related support tickets

Experience Metrics

• Sentiment Analysis: Seller feedback on communication quality
• Channel Effectiveness: Performance comparison across communication methods
• Satisfaction Scores: Post-communication seller satisfaction ratings

Implementation Timeline

Weeks 1-2: Stakeholder analysis and regulatory mapping Weeks 3-4: Content strategy development and template creation
Weeks 5-6: Technical implementation and testing Weeks 7-8: Pilot campaign with select seller segments Weeks 9-10: Full rollout with continuous optimisation

Technical Requirements

• Python 3.8+ for text analysis and automation
• Natural Language Processing libraries (spaCy, NLTK)
• Data Visualisation tools (matplotlib, plotly)
• API Integration capabilities for platform connectivity
• Machine Learning frameworks for personalisation (scikit-learn)

Getting Started

1. Clone the repository

   git clone https://github.com/[username]/sustainability-communications-framework
   cd sustainability-communications-framework

2. Install dependencies

   pip install -r requirements.txt

3. Run analysis examples

   python src/content_analyzer.py --input data/sample_regulations/epr_example.txt

4. Review methodology

   open docs/methodology.md

Contributing

This framework is designed to be adapted for different regulatory environments and seller ecosystems. Contributions are welcome in the following areas:

• Additional regulatory analysis modules
• Enhanced personalisation algorithms
• Cross-platform integration capabilities
• Performance optimisation improvements

License

This project is licensed under the MIT License - see the LICENSE file for details.

Author

Begoña Penón
Digital Communications Strategist specialising in complex content translation and stakeholder engagement.

"Transforming regulatory complexity into clear, actionable communications that drive compliance and enhance seller experience."

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Contact: begopenong@gmail.com | LinkedIn | GitHub