Many cross-border practitioners entering Amazon commonly fall into operational pitfalls: relying entirely on personal intuition for product selection, failing to study market peak and off-season patterns, randomly piling up keywords when listing, blindly following trends in pricing, and spending recklessly on advertising without conversions, resulting in long-term lack of traffic, severe inventory backlog, and continuously draining investment costs. This Amazon practical course is built on a data-driven and refined operations mindset, fully covering the entire chain of hands-on content from early-stage market research and product development to Listing optimization, advertising placement, and product marketing.

In the product selection module, the course distinguishes between two systems: experience-based product selection and data-driven product selection. It systematically breaks down industry-wide peak and off-season patterns and category competitive environments, explains in detail the full process of multi-platform benchmark product selection, data scraping, analysis, and product launch decision-making, and includes a practical case study in the apparel category to ground abstract product selection logic in real products. The listing optimization section focuses on the core of traffic acquisition, teaching you differentiated layout approaches for titles and keywords, techniques for screening and combining high-traffic head terms and high-conversion long-tail terms, and also covers main and secondary image planning, three pricing logics, and competitor price range analysis.

The link operations section integrates both experience-based optimization and data-driven optimization approaches, including product unboxing video production and refined operations based on user personas. It analyzes consumers from multiple angles such as region, spending budget, shopping habits, and repurchase data, and builds an integrated data operations model covering impressions, clicks, conversions, and inventory. Paid advertising is the focus of the course, using a conversion funnel model to break down CPC placement logic, with hands-on teaching covering bid adjustment, four-quadrant ad group screening, keyword addition and removal, match types, and negative keyword settings. Finally, it supplements two marketing approaches: on-site review operations and offline brand brochure promotion.

The course is entirely practice-oriented with no empty theory, suitable for cross-border beginners starting from zero and established store merchants looking to optimize their existing operations. After completing the course, you will be able to independently conduct market research, make scientific product selections, optimize listings with precision, improve advertising ROI, establish a data-driven store operations model, and steadily increase your store's profit potential.

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• 1.Amazon Cross-Border E-Commerce Operations Winning Introductory Course
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• 2.Explanation of the Basic Logic of Amazon Product Selection
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• 3.Category Macro Market Analysis (Peak and Off-Season Analysis) and Micro Product Analysis
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• 4.Methods for Analyzing Effective Impression Capacity of Different Keywords
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• 5.Differences Between Experience-Based Product Selection and Data-Driven Product Selection
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• 6.Experience-Based Product Selection Method: Multi-Platform Comparison Method
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• 7.Data Scraping Methods for Data-Driven Product Selection
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• 8.Data Analysis Methods for Data-Driven Product Selection
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• 9.Product Decision-Making Methods for Data-Driven Product Selection
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• 10.Case Study: Apparel Category Product Selection Methods Explained
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• 11.The Primary Principle of Listing: Gaining Traffic
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• 12.Differences Between Keyword and Title Optimization When Listing Products
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• 13.Methods for Selecting Head Traffic Terms in Listing Keywords
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• 14.Methods for Selecting Long-Tail Conversion Terms in Listing Keywords
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• 15.How to Combine Head Traffic Terms and Long-Tail Terms in Keywords
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• 16.Key Points for New Product Image Optimization: Choosing Image Types
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• 17.Three Pricing Methods: Cost-Based Pricing, Competitor-Based Pricing, etc.
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• 18.Product Price Range and Competitiveness Assessment
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• 19.Experience-Based and Data-Driven Operations Approaches for Listings
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• 20.Experience-Based Optimization Methods for Product Listings
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• 21.Video Methods for Product Listings: Unboxing and Unbagging Videos
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• 22.The Sharp Tool of Data-Driven Operations: User Personas
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• 23.User Regional Distribution Analysis and Application of Regional Data
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• 24.User Price Sensitivity Analysis and Application
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• 25.User shopping habit analysis and application of shopping habit data
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• 26.User repurchase rate analysis and application
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• 27.Data-driven operations model: impressions, traffic, clicks, conversions
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• 28.Data-driven decision-making method for conversion rates
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• 29.Data-driven inventory optimization method
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• 30.On-platform CPC advertising impression-traffic-conversion funnel model
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• 31.CPC advertising cost-per-click bid optimization method
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• 32.Multi-ad group screening method: four-quadrant analysis
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• 33.Keyword selection and optimization method for a single ad group
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• 34.Selection of ad matching types and use of negative keywords
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• 35.Online marketing: Detailed explanation of Review techniques
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• 36.Offline marketing: Detailed explanation of brand brochure marketing methods
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💡 Learning Tip: Tutorial content is based on industry practices at time of publication; please verify against current platform rules when learning.