Amazon Seller Analytics

What the source does

• FilesystemNone observedNo reads or writes in the source
• NetworkNone observedNo outbound calls in the source
• ShellNone observedNo commands run in the source
• DependenciesPinnedNothing floats
• SecretsNone foundNo keys in source

Five audit layers

Gates applied: no behavioural pass.

Audit 0.4.1 · source sha 1bc9142374b1 · 19 Oct 2026Report an issue or request a re-scan

• Publishernexscope-ai GitHub organizationOwner of the repository this skill is read from
• Source foldernexscope-ai/Amazon-Skills/amazon-seller-analyticsThe exact folder we audited
• LicenceMITAs the repository states it
• Commit pinned for this verdict1bc9142374b1A new audit runs when the source changes
• Repository statusNot archivedLast push 54 days ago
• Sandboxed runNot runSkills are read, not executed; layer L4 is skipped

Its description: Seller storefront analysis and competitive intelligence for Amazon. Analyzes seller revenue estimation, product portfolio strategy, growth trajectory, and market positioning. Reverse-engineer successful seller…

---
name: amazon-seller-analytics
description: "Seller storefront analysis and competitive intelligence for Amazon. Analyzes seller revenue estimation, product portfolio strategy, growth trajectory, and market positioning. Reverse-engineer successful seller strategies and identify expansion opportunities. Use when the user asks about analyzing sellers, competitor seller analysis, seller revenue estimation, storefront analysis, seller strategy, or learning from successful Amazon sellers."
metadata: {"nexscope":{"emoji":"📊","category":"amazon"}}
---

# 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

Excerpt, first 6,007 characters of SKILL.md, verbatim from the audited commit. It is text from someone else’s repository, quoted so you can judge it before your agent reads it.

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

git clone https://github.com/nexscope-ai/Amazon-Skills
git -C Amazon-Skills checkout 1bc9142374b1

Works in

1. 2026-10-19
   ✓SAFE B 89 / 100

   first audit · source 1bc9142374b1

Questions about Amazon Seller Analytics

• github.com/nexscope-ai/Amazon-Skills/tree/main/amazon-seller-ana — the audited source at commit 1bc9142374b1 and every finding aboveObserved · 19 Oct 2026

Spotted something wrong? Report a correction · Methodology