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• Understanding E-commerce Analytics Fundamentals: This unit covers the basics of e-commerce analytics, including key performance indicators (KPIs), data collection methods, and data visualization techniques. It lays the groundwork for more advanced topics and helps students develop a solid understanding of the field.
• Data Analysis and Interpretation: In this unit, students learn how to collect, organize, and analyze data from various sources, including website analytics tools, customer feedback, and social media. They develop skills in data interpretation, including identifying trends, patterns, and correlations.
• E-commerce Analytics Tools and Software: This unit introduces students to popular e-commerce analytics tools and software, such as Google Analytics, Adobe Analytics, and Mixpanel. Students learn how to set up and use these tools to collect and analyze data, and how to interpret the results.
• E-commerce Strategy and Planning: In this unit, students learn how to use e-commerce analytics to inform business strategy and planning. They develop skills in creating data-driven marketing plans, setting goals and objectives, and measuring the effectiveness of marketing campaigns.
• E-commerce Data Visualization: This unit focuses on the importance of data visualization in e-commerce analytics. Students learn how to create effective visualizations using tools like Tableau, Power BI, and D3.js, and how to communicate insights and recommendations to stakeholders.
• E-commerce Customer Segmentation: In this unit, students learn how to segment e-commerce customers based on demographics, behavior, and preferences. They develop skills in creating customer personas, identifying target audiences, and developing marketing strategies to reach and engage with these audiences.
• E-commerce A/B Testing and Experimentation: This unit covers the principles and best practices of A/B testing and experimentation in e-commerce. Students learn how to design and execute experiments, analyze results, and make data-driven decisions to improve website conversion rates and customer engagement.
• E-commerce Personalization and Recommendation Systems: In this unit, students learn how to use e-commerce analytics to create personalized customer experiences and recommend products to customers. They develop skills in building recommendation systems, creating content recommendations, and using machine learning algorithms to improve personalization.
• E-commerce Social Media Analytics: This unit focuses on the importance of social media analytics in e-commerce. Students learn how to collect and analyze social media data, measure the effectiveness of social media campaigns, and develop strategies to improve social media engagement and conversion rates.
• E-commerce Career Development and Professional Certifications: In this final unit, students learn how to leverage their e-commerce analytics skills to advance their careers and achieve professional certifications. They develop skills in creating a personal brand, networking with industry professionals, and staying up-to-date with the latest trends and technologies in e-commerce analytics.