Multi-Platform Cross-Border E-Commerce Product Selection
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About this skill
Problem Solved
Cross-border product research often breaks down on data comparability: platform commissions, currencies, data sources, and anti-scraping rules differ across SHEIN, Amazon, Shopee, Temu, Lazada, and TikTok Shop. SHEIN, Amazon, and Temu are often USD-based; Shopee and Lazada are often PHP-based. Temu is marked as 0% commission under managed operations, while SHEIN/Amazon are 15%, Shopee 6%, Lazada 4%, and TikTok Shop 5%. Directly scraping product pages is unstable and can trigger risk controls, while relying on one tool makes it hard to compare category competition. This skill is intended to structure category market research for selected platforms and generate a reviewable competitive report.
How It Works
The skill follows a no direct scraping approach and avoids using Playwright/Selenium to crawl platform pages. The overall path is: agent-reach multi-source collection → data cleaning → analysis engine → HTML report.
- Multi-source collection: use platform-specific sources such as Google Trends, Keepa, Jungle Scout, Helium10, Similarweb, Kalodata, or public APIs to collect SKU size, price ranges, active sellers, Top10/Top50 concentration, monthly new-listing volume, and feature-attribute coverage.
- Analysis engine: clean the data, then compute price-band distribution, competition density, new-product trends, top concentration, and platform profit estimates.
- Report output: produce a core metric panel, price-band bar charts, concentration pie charts, a feature-attribute matrix, blue-ocean opportunity cards, and recommendations, with dark/light theme support.
Boundaries
It is better used as a market-research workflow than a real-time scraping API. Output quality depends on the connected data sources; cross-platform profit comparison still requires manual calibration of FX, logistics, returns, and ad costs. For exact sales, inventory, or competitor pricing, validate with third-party selection tools, official platform data, or seller dashboards.
Use Cases
- An operations analyst evaluates SHEIN and Amazon in the same category by comparing SKU count, price bands, and top-seller concentration.
- A category manager compares Shopee and Lazada commission, currency, and competition density to shortlist viable feature attributes.
- A buyer uses Temu and TikTok Shop data to review monthly new-product trends and profit estimates before deciding on inventory.
- An analyst cleans multi-source selection data and generates an HTML report for the team to review blue-ocean opportunity cards.
Best For
- Cross-border e-commerce category operators: need comparable category reports across SHEIN, Amazon, and other platforms.
- Product selection managers: need price bands, new-product trends, and top concentration to decide which features to prioritize.
- Procurement leads: need Temu/TikTok Shop profit estimates and attribute coverage to evaluate stocking and pricing.
- Data analysts: need to clean Keepa, Jungle Scout, and other sources into an HTML competitive report.
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