amazon-seller-analytics
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How to install amazon-seller-analytics?
nexscope-ai/amazon-skills/amazon-seller-analytics
$npx -y skills add nexscope-ai/Amazon-Skills --skill amazon-seller-analyticsSeller 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 ask
SKILL.md
| 1 | # Amazon Seller Analytics 📊 |
| 2 | |
| 3 | Analyze seller storefronts and reverse-engineer winning strategies. Competitive intelligence for Amazon success. |
| 4 | |
| 5 | ## Installation |
| 6 | |
| 7 | ```bash |
| 8 | npx skills add nexscope-ai/Amazon-Skills --skill amazon-seller-analytics -g |
| 9 | ``` |
| 10 | |
| 11 | ## Capabilities |
| 12 | |
| 13 | - **Revenue estimation**: Calculate seller monthly/annual revenue from visible data |
| 14 | - **Product portfolio analysis**: Category diversification, pricing strategy, product mix |
| 15 | - **Growth trajectory tracking**: Historical expansion patterns and launch sequences |
| 16 | - **Market positioning assessment**: Brand positioning, customer targeting, competitive advantages |
| 17 | - **Inventory strategy analysis**: Stock depth, product lifecycle management, seasonal planning |
| 18 | - **Pricing strategy evaluation**: Margin optimization, competitive positioning, price changes |
| 19 | - **Launch pattern identification**: How successful sellers introduce new products |
| 20 | - **Multi-marketplace tracking**: Cross-platform seller presence and strategy |
| 21 | |
| 22 | ## Usage Examples |
| 23 | |
| 24 | Users can ask naturally. Examples: |
| 25 | |
| 26 | ``` |
| 27 | Analyze the seller "ANKER" on Amazon - revenue, strategy, product portfolio |
| 28 | ``` |
| 29 | |
| 30 | ``` |
| 31 | Study how successful kitchen gadget sellers structure their storefronts |
| 32 | ``` |
| 33 | |
| 34 | ``` |
| 35 | Compare seller strategies: "RAVPower" vs "AUKEY" in electronics |
| 36 | ``` |
| 37 | |
| 38 | ``` |
| 39 | Analyze seller growth patterns in the yoga/fitness category |
| 40 | ``` |
| 41 | |
| 42 | ``` |
| 43 | Research top sellers in baby products - what makes them successful? |
| 44 | ``` |
| 45 | |
| 46 | ``` |
| 47 | Reverse engineer the strategy of sellers making $1M+ in home decor |
| 48 | ``` |
| 49 | |
| 50 | ## Workflow |
| 51 | |
| 52 | ### Step 1: Seller Identification & Basic Intelligence |
| 53 | |
| 54 | Gather foundational seller information: |
| 55 | |
| 56 | 1. **Seller discovery**: `"top Amazon sellers [category]"` or analyze specific seller names |
| 57 | 2. **Storefront access**: `"[seller name] Amazon storefront"` - find their seller page |
| 58 | 3. **Basic metrics**: `"[seller name] Amazon seller feedback rating reviews"` |
| 59 | 4. **Market presence**: `"[seller name] brand Amazon marketplace years"` |
| 60 | |
| 61 | **Key Data Points:** |
| 62 | - Seller name and brand(s) operated |
| 63 | - Years active on Amazon (account age) |
| 64 | - Overall seller feedback score and review count |
| 65 | - Estimated number of active products |
| 66 | - Primary categories/markets served |
| 67 | |
| 68 | ### Step 2: Product Portfolio Deep Dive |
| 69 | |
| 70 | Analyze their complete product strategy: |
| 71 | |
| 72 | 1. **Product catalog**: `"[seller name] products Amazon site:amazon.com"` |
| 73 | 2. **Category spread**: Map products across different Amazon categories |
| 74 | 3. **Price range analysis**: Identify pricing tiers and market positioning |
| 75 | 4. **Product relationships**: Look for complementary products, bundles, variations |
| 76 | |
| 77 | **Portfolio Analysis Framework:** |
| 78 | |
| 79 | **A. Category Diversification** |
| 80 | - **Focused**: 80%+ revenue from single category (specialist strategy) |
| 81 | - **Diversified**: Revenue spread across 3-5 categories (risk mitigation) |
| 82 | - **Scattered**: Many unrelated categories (testing/opportunistic) |
| 83 | |
| 84 | **B. Product Depth** |
| 85 | - **SKU count**: How many total products they offer |
| 86 | - **Variations**: Colors, sizes, bundles of core products |
| 87 | - **Accessories**: Complementary products to main offerings |
| 88 | - **Seasonal items**: Products for specific times/holidays |
| 89 | |
| 90 | **C. Price Architecture** |
| 91 | - **Entry level**: Budget options to capture price-sensitive customers |
| 92 | - **Core range**: Main revenue drivers in sweet spot pricing |
| 93 | - **Premium tier**: High-margin flagship products |
| 94 | |
| 95 | ### Step 3: Revenue Estimation |
| 96 | |
| 97 | Calculate approximate seller revenue using available signals: |
| 98 | |
| 99 | 1. **Best seller rank data**: `"[seller product]" Amazon BSR rank category"` |
| 100 | 2. **Review velocity**: `"[product]" Amazon reviews per month timeline"` |
| 101 | 3. **Inventory indicators**: Stock levels, "only X left" messages |
| 102 | 4. **Price tracking**: `"[product]" Amazon price history changes"` |
| 103 | |
| 104 | **Revenue Estimation Methods:** |
| 105 | |
| 106 | **Method 1: BSR-Based Calculation** |
| 107 | - Use BSR to sales conversion rates by category |
| 108 | - Estimate units sold per month per product |
| 109 | - Multiply by product price for revenue estimate |
| 110 | - Aggregate across entire product portfolio |
| 111 | |
| 112 | **Method 2: Review Velocity Analysis** |
| 113 | - Count reviews added per month for each product |
| 114 | - Apply review-to-sales conversion ratios (typically 1-5%) |
| 115 | - Calculate implied sales volume and revenue |
| 116 | |
| 117 | **Method 3: Market Share Estimation** |
| 118 | - Estimate category market size |
| 119 | - Assess seller's market share based on visibility/dominance |
| 120 | - Calculate proportional revenue |
| 121 | |
| 122 | **Revenue Scoring Framework:** |
| 123 | - **$10M+/year**: 🟢 Major seller - dominant market position |
| 124 | - **$1M-$10M/year**: 🟡 Significant seller - strong market pr |
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