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amazon-brand-analytics

Amazon Brand Analytics interprets search, shopping, and competitive data from Amazon's Brand Registry to optimize product strategy. Use it to analyze Search Frequency Rank keywords for advertising gaps, identify cross-sell opportunities from Market Basket patterns, benchmark products against competitors via Item Comparison reports, and extract demographic insights for targeted strategies across Amazon marketplaces.

Install in Claude Code
Copy
git clone --depth 1 https://github.com/nexscope-ai/Amazon-Skills /tmp/amazon-brand-analytics && cp -r /tmp/amazon-brand-analytics/amazon-brand-analytics ~/.claude/skills/amazon-brand-analytics
Then start a new Claude Code session; the skill loads automatically.

SKILL.md

# Amazon Brand Analytics 📊

Unlock Brand Analytics insights for strategic growth. Requires Brand Registry — works with your data.

## Installation

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

## Capabilities

- **Search Frequency Rank (SFR) analysis**: Decode keyword opportunities, click share gaps, and conversion optimization
- **Market Basket intelligence**: Identify cross-sell opportunities, bundle strategies, and category expansion
- **Item Comparison insights**: Understand competitive positioning and customer consideration factors
- **Demographic analysis**: Extract customer segment insights and geographic opportunities
- **Seasonal trend detection**: Identify timing patterns and market shifts from search data
- **Strategic recommendations**: Convert raw data into actionable growth strategies
- **Multi-marketplace support**: Works with Brand Analytics from all Amazon regions

## Usage Examples

Users can ask naturally. Examples:

```
Analyze my Search Frequency Rank data for "wireless earbuds" — show keyword opportunities and click share gaps
```

```
Review my Market Basket data for the last 6 months. What cross-sell and bundling opportunities do you see?
```

```
Interpret my Item Comparison report for yoga mats — how do customers evaluate my product vs competitors?
```

```
Generate Brand Analytics strategy report for Q4 combining SFR, Market Basket, and demographic data
```

```
Find seasonal trends and opportunity keywords from my Brand Analytics data for kitchen appliances
```

## Three Analysis Modes

| Mode | Input Required | Output | Best For |
|------|----------------|--------|----------|
| **SFR Analysis** | Search Frequency Rank data export | Keyword opportunities, click/conversion gaps | Advertising optimization |
| **Market Basket** | Market Basket Analysis export | Cross-sell opportunities, bundle recommendations | Product strategy |
| **Item Comparison** | Item Comparison report data | Competitive positioning insights | Product development |

## Workflow

### Step 1: Data Preparation

**For SFR Analysis:**
1. Export Search Frequency Rank report from Brand Analytics (last 90 days recommended)
2. Focus on top 100-200 keywords by search frequency rank
3. Note current click share and conversion share for each keyword

**For Market Basket Analysis:**
1. Export Market Basket Analysis report (6-12 months for pattern recognition)
2. Include both "Customers who bought X also bought Y" data
3. Filter for statistically significant purchase combinations (10+ co-purchases)

**For Item Comparison:**
1. Export Item Comparison report for your main ASINs
2. Include comparison data with top 5-10 competitors
3. Note customer consideration patterns and demographic breakdowns

### Step 2: Pattern Recognition

Use the provided data to identify:

**SFR Insights:**
- Keywords with high search frequency but low click share (opportunity gaps)
- Conversion share significantly below click share (optimization needs)
- Seasonal search pattern changes
- Emerging keyword trends

**Market Basket Patterns:**
- Products with >25% co-purchase rate (strong bundle candidates)
- Category cross-over patterns (expansion opportunities)
- Price point correlations in purchase combinations
- Geographic or demographic purchase pattern differences

**Item Comparison Analysis:**
- Customer consideration factors ranked by importance
- Your brand's competitive strengths and weaknesses
- Price sensitivity patterns in your category
- Feature preferences by customer segment

### Step 3: Strategic Synthesis

Convert insights into actionable recommendations following the output format below.

## Output Format

Present analysis in this structure:

```
## Brand Analytics Strategic Report: [Brand/Category]

**Analysis Period:** [timeframe] | **Data Sources:** [SFR/Market Basket/Item Comparison]
**Marketplace:** Amazon [region] | **Report Date:** [current date]

### 1. Search Frequency Rank Opportunities

**Top Keyword Gaps:**

| Keyword | Search Rank | Your Click Share | Category Avg | Opportunity Score |
|---------|-------------|------------------|--------------|-------------------|
| "wireless earbuds waterproof" | #23 | 2.1% | 8.4% | High |
| "bluetooth headphones gym" | #45 | 0.8% | 5.2% | Medium |
| "noise cancelling earbuds" | #67 | 4.2% | 6.1% | Low |

**Seasonal Trends:**
- [Keyword] searches peak in [months] (+X% vs baseline)
- [Category] shows declining trend (-X% YoY)
- Emerging opportunity: [new keyword trend]

**Recommended Actions:**
1. Increase advertising spend on high-opportunity keywords
2. Optimize listings for gap keywords with low click share
3. Prepare seasonal campaigns for [upcoming peaks]

### 2. Market Basket Insights

**Cross-Sell Opportunities:**

| Product Combination | Co-Purchase Rate | Revenue Opportunity | Recommendation |
|--------------------|------------------|--------------------|--------------| 
| Your Product + [Item A] | 34% | +$2.3M annually | Create bundle |
| Your Product + [Item B] | 28% | +$1.8M annually | Cross-promote |
| [Item C] + [Item D] | 25% | +$1.2M annually | New product opportunity |

**Category Expansion Insights:**
- 23% of customers also purchase [adjacent category]
- Geographic concentration: [region] shows 40% higher cross-category rate
- Demographic pattern: [age group] drives 60% of cross-category purchases

### 3. Competitive Positioning

**Item Comparison Analysis:**

**Customer Consideration Factors (Ranked):**
1. Price (43% primary factor)
2. Reviews/Rating (31% weight)  
3. Brand Recognition (18% influence)
4. Feature Set (12% consideration)

**Your Competitive Position:**
✅ **Strengths:** Higher ratings (4.6 vs 4.2), strong brand recall in 35-54 demo
⚠️ **Weaknesses:** Price perception, limited feature differentiation

**Market Opportunities:**
- Premium segment under-served (15% price tolerance above current range)
- Feature gap: customers want [specific feature] (mentioned in 67% of comparisons)
- Geographic
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