Data Science For Marketing & E-commerce Training Course: Optimize Campaigns & Cx

Introduction

Drive growth and enhance customer engagement with our Data Science for Marketing and E-commerce Training Course. This program is designed to equip you with the essential skills to optimize marketing campaigns and customer experience, enabling you to leverage data-driven insights for strategic decision-making. In today's digital landscape, mastering data science is crucial for creating personalized marketing strategies, improving conversion rates, and maximizing customer lifetime value. Our marketing data science training course offers hands-on experience and expert guidance, empowering you to implement cutting-edge data-driven solutions.

This e-commerce data science training delves into the core concepts of marketing and e-commerce analytics, covering topics such as customer segmentation, predictive modeling, and campaign optimization. You'll gain expertise in using industry-standard libraries and tools to optimize marketing campaigns and customer experience, meeting the demands of modern digital businesses. Whether you're a marketing analyst, data scientist, or e-commerce professional, this Data Science for Marketing & E-commerce course will empower you to build powerful data-driven marketing and e-commerce strategies.

Target Audience:

• Marketing Analysts
• E-commerce Professionals
• Data Scientists
• Digital Marketing Managers
• Product Managers
• CRM Specialists
• Anyone needing marketing and e-commerce data science skills

Course Objectives:

• Understand the fundamentals of data science for marketing and e-commerce.
• Master customer segmentation techniques for targeted marketing.
• Utilize predictive modeling for customer behavior analysis.
• Implement campaign optimization strategies with data science.
• Design and build personalized customer experience models.
• Optimize marketing and e-commerce models for conversion and ROI.
• Troubleshoot and address complex marketing data challenges.
• Implement model evaluation and validation techniques for marketing.
• Integrate data science into real-world marketing and e-commerce systems.
• Understand how to handle customer data ethically and compliantly.
• Explore advanced data science techniques for marketing (e.g., natural language processing for sentiment analysis).
• Apply real world use cases for data science in marketing and e-commerce.
• Leverage marketing data libraries for efficient model implementation.

Duration

10 Days

Course content

Module 1: Introduction to Data Science for Marketing and E-commerce

• Fundamentals of data science for marketing and e-commerce.
• Overview of customer segmentation, predictive modeling, and campaign optimization.
• Setting up a marketing and e-commerce data science development environment.
• Introduction to marketing data libraries and tools.
• Best practices for marketing data science.

Module 2: Customer Segmentation

• Implementing customer segmentation techniques (RFM analysis, clustering).
• Utilizing demographic and behavioral data for segmentation.
• Designing and building customer segmentation models.
• Optimizing segmentation for targeted marketing campaigns.
• Best practices for customer segmentation.

Module 3: Predictive Modeling for Customer Behavior

• Implementing predictive models for customer churn and lifetime value.
• Utilizing machine learning for purchase prediction.
• Designing and building customer behavior prediction systems.
• Optimizing models for customer insights.
• Best practices for predictive modeling.

Module 4: Campaign Optimization

• Implementing campaign optimization strategies with data science.
• Utilizing A/B testing and multivariate testing.
• Designing and building campaign optimization pipelines.
• Optimizing campaigns for conversion and ROI.
• Best practices for campaign optimization.

Module 5: Personalized Customer Experience Models

• Designing personalized customer experience models.
• Implementing recommendation systems and personalization algorithms.
• Utilizing customer feedback and reviews.
• Optimizing experiences for customer satisfaction.
• Best practices for personalization.

Module 6: Model Optimization for Conversion and ROI

• Optimizing marketing and e-commerce models for conversion and ROI.
• Utilizing hyperparameter tuning for marketing models.
• Implementing model validation and cross-validation.
• Designing scalable marketing and e-commerce data solutions.
• Best practices for model optimization.

Module 7: Troubleshooting Marketing Data Challenges

• Debugging complex marketing data issues.
• Analyzing model performance and errors.
• Utilizing troubleshooting techniques for model improvement.
• Resolving common marketing data challenges.
• Best practices for troubleshooting.

Module 8: Model Evaluation and Validation for Marketing

• Implementing evaluation metrics for marketing tasks.
• Utilizing lift and gain charts for campaign evaluation.
• Designing and building model validation pipelines.
• Optimizing model evaluation strategies.
• Best practices for model evaluation.

Module 9: Integration with Real-World Systems

• Integrating data science models into real-world marketing and e-commerce systems.
• Utilizing APIs and deployment tools for marketing data.
• Implementing real-time marketing analytics.
• Optimizing models for deployment environments.
• Best practices for integration.

Module 10: Handling Customer Data Ethically and Compliantly

• Implementing ethical considerations for customer data.
• Utilizing privacy-preserving techniques for marketing data.
• Designing and building secure data handling pipelines.
• Optimizing data handling for regulatory compliance.
• Best practices for ethical handling.

Module 11: Advanced Data Science Techniques for Marketing

• Implementing natural language processing (NLP) for sentiment analysis.
• Utilizing social network analysis for influencer marketing.
• Designing and building advanced marketing data models.
• Optimizing advanced techniques for specific applications.
• Best practices for advanced techniques.

Module 12: Real-World Use Cases

• Implementing data science for personalized email marketing.
• Utilizing data science for dynamic pricing and promotions.
• Implementing data science for customer journey optimization.
• Utilizing data science for social media campaign analysis.
• Best practices for real-world applications.

Module 13: Marketing Data Libraries Implementation

• Utilizing scikit-learn and pandas for marketing data analysis.
• Implementing marketing models with TensorFlow and PyTorch.
• Designing and building marketing data pipelines with libraries.
• Optimizing library usage for efficient implementation.
• Best practices for library implementation.

Module 14: Model Interpretability for Marketing

• Implementing model interpretability techniques for marketing models.
• Utilizing visualization tools for understanding marketing predictions.
• Designing and building interpretable marketing models.
• Optimizing model transparency for stakeholder understanding.
• Best practices for interpretability.

Module 15: Future Trends in Data Science for Marketing and E-commerce

• Emerging trends in data science for marketing and e-commerce.
• Utilizing AI for personalized customer experiences.
• Implementing federated learning for privacy-preserving marketing data.
• Best practices for future applications.

Training Approach

This course will be delivered by our skilled trainers who have vast knowledge and experience as expert professionals in the fields. The course is taught in English and through a mix of theory, practical activities, group discussion and case studies. Course manuals and additional training materials will be provided to the participants upon completion of the training.

Tailor-Made Course

This course can also be tailor-made to meet organization requirement. For further inquiries, please contact us on: Email: info@skillsforafrica.org, training@skillsforafrica.org  Tel: +254 702 249 449

Training Venue

The training will be held at our Skills for Africa Training Institute Training Centre. We also offer training for a group at requested location all over the world. The course fee covers the course tuition, training materials, two break refreshments, and buffet lunch.

Visa application, travel expenses, airport transfers, dinners, accommodation, insurance, and other personal expenses are catered by the participant

Certification

Participants will be issued with Skills for Africa Training Institute certificate upon completion of this course.

Airport Pickup and Accommodation

Airport pickup and accommodation is arranged upon request. For booking contact our Training Coordinator through Email: info@skillsforafrica.org, training@skillsforafrica.org  Tel: +254 702 249 449

Terms of Payment: Unless otherwise agreed between the two parties’ payment of the course fee should be done 7 working days before commencement of the training.