Dropshipping Product Research#

Overview#

Dropshipping Product Research helps beginners and small operators evaluate whether a product is worth testing. It is a descriptive, non-API MVP focused on structured scoring, risk filtering, and clear go / test / reject decisions.

Trigger#

Use this skill when the user wants to:

• evaluate a product idea for dropshipping
• compare multiple product candidates
• estimate risk, margin, and creative fit
• build a weekly shortlist for testing

Example prompts#

• "Evaluate this product for dropshipping in the US"
• "Should I test a galaxy projector or pet grooming glove?"
• "Give me a go / test / reject recommendation"
• "Help me score 3 product ideas for my store"

Workflow#

1. Capture candidate, market, and positioning constraints.
2. Infer demand, competition, margin, creative angle, and risk.
3. Produce a viability score and recommendation.
4. Summarize why it may win, why it may fail, and what to test next.

Inputs#

• product name or keyword
• optional product link or niche
• target market
• price target or cost hints
• mode: single product / batch / trend scouting

Outputs#

• viability score
• sub-scores: demand, competition, margin, creative fit, risk
• recommendation: Go / Test / Reject
• memo with hypotheses and next steps

Usage Scenarios#

1. User input: "Score these 5 product ideas for a US-focused Shopify dropshipping store." → Expected output: 5-product scorecard — demand (Google Trends + Amazon BSR proxy), competition (ad-intensity check, review-count saturation), margin (cost-price vs. market-price with ad-cost breakeven), creative potential (video-ad suitability score), risk (shipping time, return rate, IP infringement check) — ranked with go/test/reject verdict.
2. User input: "I found a product on AliExpress with 10,000 orders. Is it too late to enter?" → Expected output: Market-saturation analysis — competition-velocity check, ad-auction heat (CPM trend), differentiation-gap assessment, and "late entrant" strategy options (niche-down, geo-target underserved region, content-first approach).
3. User input: "Build a weekly product-research workflow I can run in 3 hours every Sunday." → Expected output: Weekly research SOP — trend-scanning (30 min), criteria-scoring top candidates (90 min), supplier-vetting (45 min), creative-brainstorming (15 min) — with scoring spreadsheet template and decision-journal format.

Scenario 2: 在多多跨境找爆品的野路子#

User input: "我在Temu上做店群，但不知道选什么品好。有没有快速找到下一个爆品的方法？" Expected output: 拼多多/Temu选品方法论——第一步：关注抖音/小红书/快手带货直播间，看哪个品在密集推广但淘宝/拼多多上竞争还不激烈（搜索量上升但商家数还没暴涨的阶段）；第二步：在1688跨境专供频道按"新品"排序，找最近上架且供应商有现货的品；第三步：在Temu和SHEIN前台按"飙升"和"最新"排序，看哪些品突然涨起来但还没被刷屏；第四步：用Google Trends查关键词在目标国（美国/欧洲）的搜索趋势，找搜索量上升30%以上的品。关键工具：1688跨境专供+神鹰数据+Google Trends+Temu前台。

Safety#

• No marketplace scraping or real-time trend API access
• No guarantee of profit or compliance clearance
• Recommendations are heuristic and should be validated with real tests

Acceptance Criteria#

• Must output markdown
• Must include all five scoring dimensions
• Must include Go / Test / Reject recommendation
• Must include at least three risk or execution notes