Skill: no7dw/ecomm-new-products (version 0.1.0)

# Skill: E-commerce New Product Research & Development ## Overview This skill provides an end-to-end workflow for **new product research and development across e-commerce platforms** (e.g., Amazon, Shopee, SHEIN). It covers: * Category data analysis * Target segment identification * Competitive and feature analysis * Market gap discovery * Product definition * Validation and launch strategy This framework is **category-agnostic** and applicable to both **private label and branded product development**. --- ## Inputs Required | Input | Description | Example | | ----------------------- | ---------------------------------------------------- | ----------------------------- | | Category export file | Product data export from research tools or platforms | `.xlsx / .csv` export | | Target price range | Desired selling price band | `$20 – $40` | | Material / positioning | Target quality tier and audience | `mid-tier / premium / budget` | | SKU count goal | Number of products to develop | `2–5 SKUs` | | Sample specs (optional) | Prototype dimensions and features | `size, weight, components` | --- ## Supported Data Sources This workflow supports export files from: * **Amazon tools**: Sorftime, Helium10, Jungle Scout, SIF * **Shopee tools**: Shopdora, platform exports * **SHEIN tools**: SHEIN selection assistant * Any structured dataset containing product-level metrics --- ## Workflow Steps --- ### Step 1 — Category Overview Parse the export file and produce: * Total monthly and annual unit volume * Seasonality trends (monthly demand peaks) * Price distribution (bucketed by intervals) * Top brands / sellers by SKU count and sales **Typical fields to extract:** ``` Monthly Sales, Annual Sales, Price, Gross Profit, Margin, Category Rank, Subcategory, Listing Age (days), Review Count, Rating, Brand / Seller, Bullet Points / Description, Dimensions, Weight ``` --- ### Step 2 — Target Segment Deep Dive Filter products by: * Target price range * Positioning (quality tier / material / use case) Analyze: * SKU count per sub-price band * Average monthly sales per SKU * Average margin per band * Brand concentration per band **Decision rule:** Select the segment where: * High average sales per SKU * Low brand dominance / fragmentation → This indicates a **potential opportunity zone** --- ### Step 3 — Competitor & Feature Analysis #### Brand Landscape * Identify top brands by SKU count * Analyze their pricing patterns * Understand positioning (budget vs premium vs niche) #### Feature / Attribute Analysis Extract recurring attributes from titles, bullets, or descriptions: Group into: * Functional attributes (performance, utility) * Design attributes (style, form factor) * Usage attributes (scenarios, convenience) For each attribute: * Count number of SKUs * Calculate average sales **Interpretation:** * High sales + low SKU count → opportunity * High sales + high SKU count → competitive but validated * Low sales → weak demand signal --- ### Step 4 — Market Gap Identification Identify 3–5 opportunities using: | Gap Type | Criteria | Signal | | --------------- | ----------------------------------------------------- | ------------------------ | | Attribute gap | High demand attribute with low SKU presence | Underdeveloped niche | | Positioning gap | Missing tier (e.g. mid-tier between budget & premium) | Pricing imbalance | | Format gap | Inefficient or outdated product formats | Optimization opportunity | | Trend gap | Emerging trend not yet saturated | Early mover advantage | --- ### Step 5 — Product Definition (per SKU) For each recommended SKU: ``` Product Name (working title) Suggested Price: $XX.XX Why this opportunity exists: [Data-backed reasoning] Positioning: [Target audience + tier] Core Specifications: - Dimensions: - Weight: - Key components: - Structure / format: Variants: [Color / style / version options] Key Differentiation: [Clear advantage vs competitors] Estimated Margin: ~$XX (~XX%) Launch Timing: [Quarter / season] ``` --- ### Step 6 — Sample / Prototype Validation If prototype or spec sheet is available: #### Dimension Validation * Confirm size aligns with intended use case * Benchmark against top competitors * Check compatibility with primary usage scenarios #### Feature Feasibility * Validate physical feasibility of components * Ensure no over-complexity or cost inefficiency * Confirm manufacturability #### Scoring (1–5 scale) * Use-case fit * Competitive differentiation * Feature completeness * Cost vs value balance * Margin viability --- ### Step 7 — Social Proof Validation Validate demand using external signals: #### Platforms * Reddit (category discussions, sentiment) * Google Trends (search demand over time) * Media / blogs (trend mentions) * Social platforms (indirect trend signals) #### Validation Criteria * At least one product with strong sales performance in niche * Evidence of growing or stable search demand * Community or media discussion indicating awareness --- ### Step 8 — Keyword Advertising Framework #### Tier 1 — Awareness * Broad category and attribute keywords * Goal: traffic discovery #### Tier 2 — Conversion * Specific long-tail keywords * Use-case driven queries * Goal: improve conversion rate #### Tier 3 — Competitor Targeting * Competitor brand + product type * Goal: capture high-intent traffic --- #### Campaign Structure | Campaign | Type | Goal | | -------------- | -------------- | ------------------- | | Auto discovery | Automated ads | Keyword discovery | | Core keywords | Manual broad | Ranking | | Long-tail | Phrase / exact | Conversion | | Competitor | Exact | Traffic capture | | Retargeting | Display | Conversion recovery | --- ### Step 9 — Launch Timeline ``` Phase 1: Initial launch (test demand) Phase 2: Optimization (ads + listing improvements) Phase 3: Expansion (variants / additional SKUs) ``` --- ### Pre-launch Checklist * Supplier validation * Sample approval (quality, usability) * Listing assets (images, descriptions) * Pricing and promotion strategy * Advertising budget allocation * Review acquisition process --- ## Output Format The workflow should produce: 1. Market Overview 2. Target Segment Analysis 3. Competitive Landscape 4. Market Gaps 5. Product Recommendations 6. Sample Validation (if applicable) 7. Social Proof Summary 8. Keyword Strategy 9. Launch Plan


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)