# Product Selection

> Product selection workflow: industry research → consumer research → product selection → supplier matching. Evidence-first, multi-source validation. Use when user wants to select products, find trending items, analyze categories, discover follow-sell opportunities, or asks "what to sell", "which products", "hot products". Works with product-supplier-sourcing skill.

- Skill: `veritasian/product-selection` (Agent Skill, multi-file: 2 files)
- Install (CLI): `npx skillmds@latest add veritasian/product-selection`
- Raw SKILL.md: https://api.skillmd.com/api/skills/veritasian/product-selection/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Research & Search
- Author: veritasian (https://skillmd.com/u/veritasian)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/veritasian/product-selection

---


# Product Selection

Comprehensive **product selection workflow** with evidence-first methodology. Guides you through industry analysis, consumer research, product discovery, and supplier matching based on user's starting point.

## When to Use

- User wants **product selection**, **trending products**, **category analysis**, or **follow-sell opportunities**
- Questions like: "what to sell", "which products are trending", "how to choose a category", "find hot products for [market]"
- User asks about **selection methodology** or **data sources**
- Coordinates with `product-supplier-sourcing` skill for concrete product/supplier retrieval

---

## Execution Flow (start point depends on context)

| User's Starting Point | Action |
|----------------------|--------|
| **No industry specified** | Start from **Step1** (Industry Research) + **Step2** (Consumer Research) → then Step3 |
| **Industry specified, no specific category** | Start from **Step2** (Consumer Research) → then Step3 — even with industry, consumer insights are needed to select specific product categories |
| **Industry + Category specified** | Jump to **Step3** (Product Selection) |
| **Product(s) identified + supplier request** | Execute **Step4** (Supplier Matching) — only when explicitly requested |

**Key Rules**: 
- Step2 (consumer research) is critical for category selection within an industry — skip only if user specifies both industry AND specific category
- Step4 (supplier) runs **ONLY** when user explicitly mentions "supplier", "factory", "manufacturer", or "sourcing". Terms like "find products" or "hot products" do NOT trigger Step4.

---

## Core Principles

1. **User intent overrides skill**: Follow user's specific requirements (platform, market, timeframe, format) even if they differ from this guide
2. **Evidence first**: Every conclusion needs data support; cite sources and methods
3. **Multi-source validation**: Use ≥2 data source types for trend/industry conclusions (e.g., platform data + third-party tools + social/reviews)
4. **Explicit data gaps**: State what data is missing and suggest next collection steps instead of guessing

---

## Step1: Industry Research

**Trigger**: User has NOT specified industry/category.

**Goal**: Identify promising industries/categories for product selection.

### Selection Criteria (priority order)

| Criterion | What to Look For | Why It Matters |
|-----------|-----------------|----------------|
| **Traffic trend** | Growing traffic (faster than sales growth = room for new sellers) | Indicates market demand is expanding |
| **Sales trend** | Increasing sales volume/GMV | Validates monetization potential |
| **Competition intensity** | Low concentration (no monopoly by top 10 sellers) | Entry barrier for new sellers |
| **New listing rate** | Moderate new product rate (10-20% annually) | Shows innovation space without saturation |
| **Compliance** | No policy/legal restrictions | Risk mitigation |

### Data Sources

| Dimension | Common Tools/Sources |
|-----------|---------------------|
| Traffic trends | SimilarWeb, Jungle Scout, Helium 10 |
| Sales trends | Amazon Brand Analytics, ecommerceDB, Statista |
| Concentration | Manual calculation from marketplace data |
| New listings | Platform analytics (Seller Central insights) |

**Output Format**:
```
Industry: [Category Name]
Conclusion: [Promising/Not Recommended]
Evidence:
  - Traffic: [Trend data + source]
  - Sales: [Trend data + source]
  - Concentration: [Top 10 share + source]
  - New listings: [Rate + source]
Data Gaps: [List any missing data points]
```

---

## Step2: Consumer Research

**Trigger**: 
- **Required** when industry is not pre-specified (pairs with Step1)
- **Also required** when industry is specified but specific product category is not — consumer insights guide category selection within the industry

**Goal**: Identify consumer pain points, unmet needs, and product opportunities to guide category/product selection.

### Research Method

1. **Extract complaints/needs** from:
   - E-commerce reviews (Amazon, eBay, Walmart, etc.)
   - Social discussions (Reddit, Facebook groups, TikTok comments)
   - Q&A platforms (Quora, specialized forums)
   - App reviews (for digital/smart products)

2. **Use specialized skills for review analysis**:
   - **`review-summarizer` skill**: For scraping and summarizing reviews from Amazon, Google, Yelp, TripAdvisor
     - Generates sentiment analysis, pros/cons, complaint frequency
     - Supports multi-platform comparison
   - **`review-analyst-agent` skill**: For deep analysis and prioritization
     - Identifies top complaints with frequency/severity
     - Extracts feature requests
     - Provides actionable improvement recommendations
     - Use when you need structured analysis with priority matrix

3. **Categorize pain points**:
   - Quality issues (durability, materials, craftsmanship)
   - Design/functionality gaps (missing features, poor UX)
   - Price sensitivity (overpriced, poor value perception)
   - Delivery/service problems (shipping, returns, support)
   - Safety/compliance concerns

4. **Map to product opportunities**:
   - **Improvement opportunities**: Better quality/features than existing products
   - **Gap-filling opportunities**: Unmet needs in the market
   - **Differentiation opportunities**: Unique value proposition
   - **Follow-sell opportunities**: Products with complaints that can be addressed

### Integration with Review Analysis Skills

**When to use each skill**:

| Scenario | Recommended Skill | Why |
|----------|------------------|-----|
| Quick review summary for 1-2 products | `review-summarizer` | Fast scraping + basic sentiment |
| Deep analysis for category selection | `review-analyst-agent` | Structured output with priority matrix |
| Multi-platform comparison | `review-summarizer` | Supports Amazon, Google, Yelp, TripAdvisor |
| Competitor pain point analysis | `review-analyst-agent` | Identifies improvement opportunities |

**Example workflow**:
```
1. User specifies industry: "Home & Kitchen"
2. Use review-analyst-agent to analyze top products in that industry
3. Extract top complaints (e.g., "poor battery life", "leaks easily")
4. Map complaints to product categories (e.g., "rechargeable kitchen scales", "leak-proof containers")
5. Proceed to Step3 with category focus
```

**Output Format**:
```
### Consumer Research Summary

**Sources Analyzed**: 
- [Platform1]: [Number] reviews
- [Platform2]: [Number] posts/comments

**Top Pain Points** (by frequency):

1. [Pain Point1] — Frequency: [X]% of complaints
   - Sources: [Platform + sample reviews/posts]
   - Severity: [High/Medium/Low]
   - Product Category Opportunity: [Specific category to target]
   - Product Direction: [How to address this]
  
2. [Pain Point2] — Frequency: [X]% of complaints
   - Sources: [Platform + sample reviews/posts]
   - Severity: [High/Medium/Low]
   - Product Category Opportunity: [Specific category to target]
   - Product Direction: [How to address this]

**Feature Requests**: 
- [Request1] — Frequency: [X] mentions
- [Request2] — Frequency: [X] mentions

**Recommended Categories for Step3**:
1. [Category1] — Addresses pain points: [#1, #3]
2. [Category2] — Addresses pain points: [#2, #4]
```

---

## Step3: Product Selection

**Trigger**: Industry specified OR after completing Steps 1-2.

**Goal**: Identify specific products to follow-sell, develop, or list.

### Approach1: E-commerce Platform Analysis

**Target**: Find products with proven demand but manageable competition.

**Selection Logic**:
- **Sweet spot**: BSR rank 100-5,000 (varies by category)
- **Avoid**: Top 20 (too competitive), BSR > 10,000 (uncertain demand)
- **Check**: Review count (300-1,000 = validated), rating (4.0-4.5 = room for improvement)

**Tools & Platforms**:

| Tool/Platform | Use Case | Key Metrics |
|--------------|----------|-------------|
| Amazon Best Sellers | Identify trending products | BSR, review count, price |
| Jungle Scout / Helium 10 | Sales estimation, keyword research | Monthly revenue, search volume |
| Kalodata | TikTok Shop analysis | GMV, engagement |
| 1688.com | Supply chain reference (China) | Factory pricing, MOQ |

**Concrete Steps**:
1. Filter category by Step1/2 criteria (industry + consumer pain points)
2. Export products in target BSR range (use `product_supplier_search` if available, or manual export)
3. **Competitive analysis** (use `competitive-landscape` skill for deeper analysis):
   - Identify top 5-10 competitors in the BSR range
   - Analyze differentiation opportunities (product features, pricing, positioning)
   - Use `review-analyst-agent` to find their weaknesses (top complaints)
   - Map improvement opportunities (e.g., "Competitor has battery complaint → source better battery")
4. Calculate: Estimated sales × margin - fees = profit
5. Rank by: (Profit potential × Demand validation × Differentiation feasibility) / Competition level

**Integration with Competitive Analysis**:
- **Use `competitive-landscape` skill** when you need to:
  - Understand competitive intensity (Porter's Five Forces)
  - Identify positioning gaps (positioning map)
  - Develop differentiation strategy
- **Use `review-analyst-agent`** to find competitor weaknesses:
  - Extract top complaints from competitor products
  - Identify improvement opportunities
  - Prioritize which issues to solve in your product selection

### Approach2: Advertising & Traffic Analysis

**Target**: Products with strong recent marketing momentum.

**Selection Logic**:
- **Ad frequency**: Seen in ads ≥10 times in past 30 days (use Pipiads/Minea)
- **Engagement**: High CTR/comments/shares relative to ad spend
- **Freshness**: Launched within past 6 months (less saturated)

**Tools**:

| Tool | Coverage | Key Signals |
|------|----------|-------------|
| Pipiads | TikTok ads | Likes, comments, ad frequency |
| Minea | Meta, TikTok, Pinterest ads | Engagement, estimated revenue |
| Google Trends | Search behavior | Search volume trend, geographic interest |

**Concrete Steps**:
1. Search category keywords in ad intelligence tools
2. Filter: 10+ appearances in past 30 days, engagement rate > 5%
3. Cross-check with `product_supplier_search` (intent_type=product) to find supply options
4. Validate on destination marketplace (check if already saturated)

### Approach3: Crowdfunding Signal Mining

**Target**: Innovative products for early follow-sell or white-label opportunities.

**Selection Logic**:
- **Funding level**: 200-500% of goal (validated interest, not yet mass market)
- **Backer count**: 500-5,000 (niche demand, scalable)
- **Timeline**: Projects ending in 1-3 months (time to source & launch)

**Platforms**:
- Kickstarter / Indiegogo (innovation signal)

**⚠️ Caution**:
- **High risk**: Crowdfunding success ≠ marketplace success
- **IP concerns**: Check for patents before copying
- **Long development**: Expect 6-12 month sourcing/development cycle

**When to use**: Only for users with product development capability and higher risk tolerance.

---

## Step4: Supplier Matching

**⚠️ CRITICAL**: Execute ONLY when user explicitly requests suppliers/factories/manufacturers/sourcing.

**Goal**: Match selected products to qualified suppliers.

### Matching Process

1. **Prepare product specs**:
   - Product name/category
   - Key features (from Step3 selection)
   - Target price range
   - MOQ constraints

2. **Search suppliers**:
   - **Primary**: Call `product_supplier_search` (intent_type=supplier, query in English)
     - This searches **alibaba.com** by default (per `product-supplier-sourcing` skill)
     - **Output must include**: 
       - Clickable supplier links: `[Supplier Name](https://alibaba.com/company/...)`
       - Product thumbnails if available: `<img src="..." width="80">`
       - Direct store links for each supplier
   - **Secondary**: If alibaba.com unsuitable, try:
     - 1688.com (domestic China supply, lower MOQ)
     - Made-in-China, Global Sources (alternative B2B platforms)
     - Direct factory outreach (trade shows, referrals)

3. **Qualification criteria**:
   - Trade assurance / verified status
   - MOQ matches your budget
   - Production capacity (order size flexibility)
   - Sample policy (can order samples before bulk)
   - Communication responsiveness

**Output Format**:
```
Product: [Name from Step3]
Target Specs: [Key features/requirements]

Supplier1: **[Company name](https://alibaba.com/company/...)** 
  Platform: alibaba.com
  MOQ: [Quantity + price]
  Lead time: [Days]
  Qualification: [Verified/Trade Assurance/Years]
  Store Link: [Visit Store](https://alibaba.com/company/...)

Supplier2: ...

Next Steps:
  - Request samples from top 2-3 suppliers
  - Compare quality/pricing
  - Negotiate terms (MOQ, payment, customization)
```

**Visual Presentation** (if products shown):
- Include product thumbnails: `<img src="..." width="80">`
- Verify image URLs are valid (no broken links)
- Make all product/supplier names clickable
- See `product-supplier-sourcing` skill for detailed formatting requirements

---

## Selecting the Right Approach

| User Goal | Recommended Approach(es) | Reasoning | Required Skills |
|-----------|-------------------------|-----------|-----------------|
| Quick follow-sell (low risk) | Approach1 (E-commerce) | Validated demand, established products | `review-analyst-agent` for competitor analysis |
| Trend-driven (fast-moving) | Approach2 (Advertising) | Captures emerging trends, viral products | — |
| Innovation/differentiation | Approach3 (Crowdfunding) | Early-mover advantage, unique products | — |
| Brand building | Approach1 + 2 combined | Mix proven products + trending items | `review-analyst-agent` + `competitive-landscape` |
| Gap-filling | Approach1 + Step2 emphasis | Find unmet needs in established markets | `review-analyst-agent` (critical for finding gaps) |

**Default**: If user doesn't specify, recommend **Approach1** (lowest risk, most accessible data).

---

## Tool Integration

### Using `product_supplier_search` (from `product-supplier-sourcing` skill)

**When in Step3 (Product Selection)**:
```
intent_type: "product"
query: "[product category/name] [key attributes]" (in English)
```
Example: `query: "wireless earbuds, waterproof, noise cancelling"`

**When in Step4 (Supplier Matching)**:
```
intent_type: "supplier"
query: "[product category] [optional: region/industry]" (in English)
```
Example: `query: "consumer electronics, Shenzhen"`

**Important**: This tool searches **alibaba.com only**. If user requests other platforms (1688, Amazon, etc.), see `product-supplier-sourcing` skill for fallback strategies.

### Output Requirements (see `product-supplier-sourcing` skill for full details)

When presenting product or supplier search results:

1. **Include product thumbnails**:
   - Display images inline with controlled size: `<img src="..." width="80">`
   - Check image URL validity before displaying
   - If image unavailable, use placeholder: 📦 or `[No Image]`

2. **Include clickable links**:
   - Product name: `[Product Name](https://alibaba.com/product/...)`
   - Supplier: `[Supplier Name](https://alibaba.com/company/...)`
   - Detail link: `[View Details](https://alibaba.com/product/...)`

3. **Example product table format**:
   ```markdown
   | Thumbnail | Product | Price | MOQ | Supplier | Link |
   |-----------|---------|-------|-----|----------|------|
   | <img src="..." width="80"> | **[Product A](link)** | $5-$8 | 100 pcs | [Supplier X](link) | [Details](link) |
   ```

4. **Image validation checklist**:
   - ✅ Verify image URL starts with `https://` or `http://`
   - ✅ Use `width="80"` for consistent sizing
   - ✅ If image URL invalid, omit image but keep product link
   - ❌ Never display broken image links
   - ❌ Never exceed `width="150"` in tables

---

## Output Structure

### Comprehensive Selection Report

```markdown
## 1. Selection Scope
- Market: [Target marketplace/region]
- Category: [If specified, or "TBD after industry research"]
- Goal: [Follow-sell / Brand building / Innovation]
- Supplier required: [Yes/No]

## 2. Industry Analysis (if Step1 executed)
### Selected Industry: [Name]
- Traffic trend: [Data + source]
- Sales trend: [Data + source]
- Competition: [Concentration data]
- New listings: [Rate + source]
- **Conclusion**: [Why this industry is promising/risky]
- **Data gaps**: [What's missing]

## 3. Consumer Insights (if Step2 executed)
### Analysis Sources
- [Platform1]: [Number] reviews/posts analyzed
- [Platform2]: [Number] reviews/posts analyzed
- **Skills used**: [review-summarizer / review-analyst-agent]

### Top Pain Points (by frequency)
1. [Pain point] — [X]% of complaints
   - **Severity**: [High/Medium/Low]
   - **Product category opportunity**: [Specific category]
   - **Product direction**: [How to address]
   - **Sample evidence**: "[Quote from review]"

2. [Pain point] — [X]% of complaints
   - [Same structure]

### Feature Requests
- [Request1] — [X] mentions
- [Request2] — [X] mentions

### Recommended Categories for Selection
1. [Category1] — Addresses pain points: [#1, #3]
2. [Category2] — Addresses pain points: [#2, #4]

## 4. Product Candidates (Step3 - REQUIRED)
### Approach Used: [E-commerce / Advertising / Crowdfunding]

### Competitive Landscape
**Skills used**: [competitive-landscape / review-analyst-agent]

- **Porter's Five Forces summary** (if deep analysis):
  - New entrants: [Low/Medium/High]
  - Competition intensity: [Low/Medium/High]
  - Key finding: [Insight]

- **Competitor weakness analysis** (from reviews):
  - Competitor A: Top complaint = "[Issue]" ([X]% of reviews)
  - Competitor B: Top complaint = "[Issue]" ([X]% of reviews)
  - **Opportunity**: Address these issues in product selection

### Product Selection Results

| Thumbnail | Product | BSR/Rank | Est. Sales | Price | Competition | Improvement Opportunity | Link |
|-----------|---------|----------|------------|-------|-------------|------------------------|------|
| <img src="..." width="80"> | **[Product Name](link)** | [Data] | [Data] | [$] | [Low/Med/High] | [What to improve vs. competitors] | [View Details](link) |

**Note**: 
- Include product thumbnails with `width="80"` for visual scanning
- Verify image URLs are valid before displaying
- All product names must be clickable links to source pages
- Add "View Details" link for quick access

**Recommendation**: [Top 3 products with reasoning]
- Product1: [Why] — Addresses pain point: [#1], competitor weakness: [Issue]
- Product2: [Why] — Addresses pain point: [#2]
- Product3: [Why] — Differentiation opportunity: [Gap in positioning]

**Risk notes**: [Competition, seasonality, compliance issues]

## 5. Supplier Options (only if Step4 executed)
[See Step4 output format above]

## 6. Next Steps
- [ ] [Specific action1]
- [ ] [Specific action2]
- [ ] Deep dive on competitor reviews (use `review-analyst-agent`)
- [ ] Validate positioning gap (use `competitive-landscape`)
```

### Citation Requirements

Every conclusion must include:
- **Data source**: Tool/platform name
- **Timeframe**: When data was collected
- **Method**: How the conclusion was derived

Example: ❌ "This product is trending" → ✅ "This product has 150% sales growth in past 30 days (Source: Jungle Scout, accessed 2024-03-07)"

---

## Validation Checklist

Before finalizing output:

- [ ] Starting point determined correctly:
  - No industry specified → Step1 + 2
  - Industry specified, no category → Step2 + 3
  - Industry + category specified → Step3
- [ ] Step2 (consumer research) executed when needed (unless user provides both industry AND category)
- [ ] Step4 executed ONLY if user explicitly requested suppliers
- [ ] Review analysis skills used in Step2 (`review-summarizer` or `review-analyst-agent`)
- [ ] Competitive analysis considered in Step3 (competitor weaknesses, positioning gaps)
- [ ] All conclusions have data sources cited
- [ ] Multi-source validation used for trend claims (≥2 sources)
- [ ] Data gaps explicitly stated (not hidden)
- [ ] Quantitative criteria used (not vague terms like "popular")
- [ ] Risk factors mentioned (competition, seasonality, compliance)
- [ ] Actionable next steps provided
- [ ] **Product thumbnails included** in output tables (with `width="80"`)
- [ ] **All image URLs validated** (no broken links)
- [ ] **All product/supplier names are clickable links** to source pages
- [ ] **Image size controlled** (not oversized in tables)

---

## Common Pitfalls to Avoid

❌ **Don't**:
- Skip Step2 (consumer research) when user only specifies industry — category selection needs consumer insights
- Run supplier search (Step4) when user only asked for "products"
- State "this is a hot product" without sales/trend data
- Recommend products without analyzing competitor weaknesses
- Ignore data gaps and sound overconfident
- Mix up `product-supplier-sourcing` (alibaba.com) with 1688/other platforms
- Select products without checking review pain points
- **Present products without images or links** — always include thumbnails and clickable links
- **Use broken/invalid image URLs** — check validity before displaying
- **Display oversized images** — use `width="80"` in tables

✅ **Do**:
- Start from the right step based on user context (see Execution Flow)
- Use `review-analyst-agent` to understand consumer pain points in Step2
- Use `competitive-landscape` to identify positioning gaps in Step3
- Analyze competitor reviews to find improvement opportunities
- Cite specific data sources and timeframes
- Quantify criteria (BSR ranges, sales thresholds, complaint frequencies)
- State what you can't verify and suggest how to get that data
- Align tool capabilities with user expectations
- **Include product thumbnails** (`<img src="..." width="80">`) for visual scanning
- **Make all product/supplier names clickable links** to source pages
- **Verify image URLs** before displaying (avoid broken links)
- **Control image size** in tables (`width="80"` recommended)

---

## Dependencies

### Core Skills
- **`product-supplier-sourcing` skill**: Provides `product_supplier_search` tool (alibaba.com) for product/supplier retrieval

### Consumer Research Skills (Step2)
- **`review-summarizer` skill**: Multi-platform review scraping and summarization (Amazon, Google, Yelp, TripAdvisor)
- **`review-analyst-agent` skill**: Deep review analysis with priority matrix and actionable recommendations

### Competitive Analysis Skills (Step3)
- **`competitive-landscape` skill**: Porter's Five Forces, positioning maps, differentiation strategies

### Optional Tools
- **`chart-design-guide.md`**: Reference for visualizing trends (if generating charts from collected data)

---

## Advanced: Data Visualization

If you collect sufficient time-series or comparison data and need to visualize trends:

See `chart-design-guide.md` in this skill directory for:
- Chart type selection (trend lines, bar charts, radar charts)
- Seaborn/Matplotlib implementation
- When to use tables vs. charts

**When to visualize**:
- Comparing 5+ categories (use bar chart)
- Showing 3-month+ trends (use line chart)
- Multi-factor product comparison (use radar chart)

**When NOT to visualize**:
- Only 2-3 data points (use table)
- Data from screenshots/third-party tools (just cite the source)