Global Certificate in Retail Data for Assortment Planning

Name: Global Certificate in Retail Data for Assortment Planning
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The Global Certificate in Retail Data for Assortment Planning is a comprehensive course that equips learners with essential skills for data-driven assortment planning in the retail industry. This course emphasizes the importance of utilizing data to make informed decisions, a crucial aspect of modern retail management.

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About this course

In an era where retail businesses generate vast amounts of data, this course is increasingly relevant and in high demand. Learners will gain a deep understanding of data analysis techniques, retail mathematics, and assortment planning strategies, thereby enhancing their career advancement opportunities. This course covers various topics, including product performance analysis, customer profiling, and range planning, providing learners with a holistic understanding of retail assortment planning. By the end of the course, learners will be able to leverage data to optimize product offerings, improve customer satisfaction, and drive business growth.

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Course Details

• Data Analysis for Retail Assortment Planning
• Retail Mathematics and Statistical Analysis
• Retail Data Collection and Management
• Assortment Planning Principles and Best Practices
• Product Lifecycle Management and Data Analysis
• Retail Trend Analysis and Forecasting
• Data Visualization for Retail Decision Making
• Retail Technology and Analytics Tools
• Ethics in Retail Data Analysis

Career Path

This section features a 3D pie chart that highlights the job market trends for various roles in retail data for assortment planning in the UK. The chart uses Google Charts to provide a responsive visual representation of the data, with a transparent background and no added background color to seamlessly integrate with your design. Data is presented on five key retail roles, including Category Manager, Assortment Planner, Buyer, Inventory Analyst, and Data Scientist (Retail), with their respective percentage representation in the UK job market. The primary and secondary keywords are used naturally to maintain industry relevance and create engaging content. To ensure proper layout and spacing, the

element with the ID 'chart_div' is styled inline. The Google Charts library is loaded using the correct script tag, and the JavaScript code to define the chart data, options, and rendering logic is written within a