amazon-seller-analytics

# Amazon Seller Analytics 📊

Analyze seller storefronts and reverse-engineer winning strategies. Competitive intelligence for Amazon success.

## Installation

```bash
npx skills add nexscope-ai/Amazon-Skills --skill amazon-seller-analytics -g
```

## Capabilities

- **Revenue estimation**: Calculate seller monthly/annual revenue from visible data
- **Product portfolio analysis**: Category diversification, pricing strategy, product mix
- **Growth trajectory tracking**: Historical expansion patterns and launch sequences  
- **Market positioning assessment**: Brand positioning, customer targeting, competitive advantages
- **Inventory strategy analysis**: Stock depth, product lifecycle management, seasonal planning
- **Pricing strategy evaluation**: Margin optimization, competitive positioning, price changes
- **Launch pattern identification**: How successful sellers introduce new products  
- **Multi-marketplace tracking**: Cross-platform seller presence and strategy

## Usage Examples

Users can ask naturally. Examples:

```
Analyze the seller "ANKER" on Amazon - revenue, strategy, product portfolio
```

```
Study how successful kitchen gadget sellers structure their storefronts
```

```
Compare seller strategies: "RAVPower" vs "AUKEY" in electronics
```

```
Analyze seller growth patterns in the yoga/fitness category
```

```
Research top sellers in baby products - what makes them successful?
```

```
Reverse engineer the strategy of sellers making $1M+ in home decor
```

## Workflow

### Step 1: Seller Identification & Basic Intelligence

Gather foundational seller information:

1. **Seller discovery**: `"top Amazon sellers [category]"` or analyze specific seller names
2. **Storefront access**: `"[seller name] Amazon storefront"` - find their seller page
3. **Basic metrics**: `"[seller name] Amazon seller feedback rating reviews"`
4. **Market presence**: `"[seller name] brand Amazon marketplace years"`

**Key Data Points:**
- Seller name and brand(s) operated
- Years active on Amazon (account age)
- Overall seller feedback score and review count  
- Estimated number of active products
- Primary categories/markets served

### Step 2: Product Portfolio Deep Dive

Analyze their complete product strategy:

1. **Product catalog**: `"[seller name] products Amazon site:amazon.com"`
2. **Category spread**: Map products across different Amazon categories
3. **Price range analysis**: Identify pricing tiers and market positioning
4. **Product relationships**: Look for complementary products, bundles, variations

**Portfolio Analysis Framework:**

**A. Category Diversification**
- **Focused**: 80%+ revenue from single category (specialist strategy)
- **Diversified**: Revenue spread across 3-5 categories (risk mitigation)
- **Scattered**: Many unrelated categories (testing/opportunistic)

**B. Product Depth**
- **SKU count**: How many total products they offer
- **Variations**: Colors, sizes, bundles of core products  
- **Accessories**: Complementary products to main offerings
- **Seasonal items**: Products for specific times/holidays

**C. Price Architecture**
- **Entry level**: Budget options to capture price-sensitive customers
- **Core range**: Main revenue drivers in sweet spot pricing
- **Premium tier**: High-margin flagship products

### Step 3: Revenue Estimation

Calculate approximate seller revenue using available signals:

1. **Best seller rank data**: `"[seller product]" Amazon BSR rank category"`
2. **Review velocity**: `"[product]" Amazon reviews per month timeline"`  
3. **Inventory indicators**: Stock levels, "only X left" messages
4. **Price tracking**: `"[product]" Amazon price history changes"`

**Revenue Estimation Methods:**

**Method 1: BSR-Based Calculation**
- Use BSR to sales conversion rates by category
- Estimate units sold per month per product
- Multiply by product price for revenue estimate  
- Aggregate across entire product portfolio

**Method 2: Review Velocity Analysis**  
- Count reviews added per month for each product
- Apply review-to-sales conversion ratios (typically 1-5%)
- Calculate implied sales volume and revenue

**Method 3: Market Share Estimation**
- Estimate category market size  
- Assess seller's market share based on visibility/dominance
- Calculate proportional revenue

**Revenue Scoring Framework:**
- **$10M+/year**: 🟢 Major seller - dominant market position
- **$1M-$10M/year**: 🟡 Significant seller - strong market presence  
- **$100K-$1M/year**: 🟡 Established seller - profitable operation
- **$10K-$100K/year**: 🔴 Small seller - testing or niche focus
- **<$10K/year**: 🔴 Minimal seller - hobby or startup level

### Step 4: Growth Strategy Analysis

Identify how successful sellers expand their business:

1. **Launch timeline**: `"[seller]" new products Amazon 2024 2023 2022` - track product additions
2. **Category expansion**: How they moved into adjacent markets  
3. **Brand evolution**: Changes in branding, positioning, target market
4. **Seasonal adaptation**: How they handle peak seasons and market cycles

**Growth Pattern Identification:**

**A. Vertical Expansion**  
- Adding more products within same category
- Going deeper into customer segment (more SKUs, variations)
- Building category authority and market share

**B. Horizontal Expansion**
- Entering adjacent categories with existing customers
- Cross-selling complementary products  
- Leveraging brand recognition in new markets

**C. Market Tier Evolution**
- Moving from budget to premium positioning (or vice versa)
- Targeting different customer segments within category
- Upgrading product quality and pricing over time

### Step 5: Competitive Positioning Analysis

Understand how sellers differentiate and compete:

1. **Brand positioning**: `"[seller brand]" unique value proposition Amazon`
2. **Customer reviews analysis**: `"[seller products]" Amazon reviews strengths weaknesses`
3. **Competitive advantages**: What makes them successful vs. competitors
4. **Marketing approach