Best for
- Use when: (1) analyzing Search Frequency Rank data for keyword opportunities, (2) interpreting Market Basket data for cross-s
nexscope-ai/Amazon-Skills/amazon-brand-analytics/SKILL.md
Amazon Brand Analytics interpretation and strategic insights for Brand Registry owners. Decode Search Frequency Rank (SFR) data, analyze Market Basket patterns, interpret Item Comparison reports, and extract demographic insights to optimize product strategy and advertising spend. Works with Brand Analytics data from all Amazon marketplaces. Requires Brand Registry access. Use when: (1) analyzing Search Frequency Rank data for keyword opportunities, (2) interpreting Market Basket data for cross-s
Decision brief
Unlock Brand Analytics insights for strategic growth. Requires Brand Registry — works with your data.
Compatibility matrix
| Platform | Status | Evidence | What to check |
|---|---|---|---|
| Codex | Not declared | No explicit evidence | Portability before use |
| Claude Code | Not declared | No explicit evidence | Portability before use |
| Cursor | Not declared | No explicit evidence | Portability before use |
| Gemini CLI | Not declared | No explicit evidence | Portability before use |
Installation
The source command is displayed only when detected. A safe inspection prompt is always available so your agent can explain every action before execution.
npx skills add https://github.com/nexscope-ai/Amazon-Skills --skill "amazon-brand-analytics"Inspect the Agent Skill "amazon-brand-analytics" from https://github.com/nexscope-ai/Amazon-Skills/blob/0f3b13fa0e5ed0a9f3d600dc18518bc76ddd813b/amazon-brand-analytics/SKILL.md at commit 0f3b13fa0e5ed0a9f3d600dc18518bc76ddd813b. List every install step, command, network request, credential, file read/write, external action, and rollback step. Explain whether it fits my task. Do not install or execute anything until I approve.
Workflow
Users can ask naturally. Examples:
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 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
Use the provided data to identify:
Convert insights into actionable recommendations following the output format below.
Permission review
The documentation asks the agent to run terminal commands or scripts.
npx skills add nexscope-ai/Amazon-Skills --skill amazon-brand-analytics -gThe documentation asks the agent to run terminal commands or scripts.
npx skills add nexscope-ai/Amazon-Skills --skill amazon-keyword-research -gEvidence record
| Signal | Value | Evidence type | Meaning |
|---|---|---|---|
| Quality score | 91/100 | Computed | Documentation, specificity, maintenance, and trust rules |
| Repository stars | 603 | Source | Repository attention, not individual Skill quality |
| Compatibility | 0 platforms | Source | Declared in the catalog source record |
| Usage guide | automated source guide | Editorial | Generated or reviewed according to the visible evidence level |
Pinned source
Unlock Brand Analytics insights for strategic growth. Requires Brand Registry — works with your data.
npx skills add nexscope-ai/Amazon-Skills --skill amazon-brand-analytics -g
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
| 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 |
For SFR Analysis:
For Market Basket Analysis:
For Item Comparison:
Use the provided data to identify:
SFR Insights:
Market Basket Patterns:
Item Comparison Analysis:
Convert insights into actionable recommendations following the output format below.
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% | +$1.2M annually | New product opportunity |
**Category Expansion Insights:**
- 23% of customers also purchase [adjacent category]
- Geographic concentration: [region] shows 40% higher cross-category rate
- Demographic pattern: [age group] drives 60% of cross-category purchases
### 3. Competitive Positioning
**Item Comparison Analysis:**
**Customer Consideration Factors (Ranked):**
1. Price (43% primary factor)
2. Reviews/Rating (31% weight)
3. Brand Recognition (18% influence)
4. Feature Set (12% consideration)
**Your Competitive Position:**
✅ **Strengths:** Higher ratings (4.6 vs 4.2), strong brand recall in 35-54 demo
⚠️ **Weaknesses:** Price perception, limited feature differentiation
**Market Opportunities:**
- Premium segment under-served (15% price tolerance above current range)
- Feature gap: customers want [specific feature] (mentioned in 67% of comparisons)
- Geographic expansion: strong brand preference in [regions]
### 4. Strategic Recommendations
**Immediate Actions (Next 30 Days):**
1. Launch [product bundle] based on Market Basket data
2. Increase ad spend on [top 3 opportunity keywords]
3. A/B test premium pricing in [geographic segments]
**Q4 Strategy:**
1. Prepare seasonal campaigns for [trending keywords]
2. Develop [feature enhancement] to address competitive gap
3. Expand into [adjacent category] with [specific product]
**2027 Growth Plan:**
1. Full [category] expansion based on cross-sell data
2. Premium line development for feature-conscious segment
3. Geographic expansion focus on [high-opportunity regions]
**Projected Impact:**
- Bundle optimization: +$X.XM revenue
- Keyword optimization: +X% conversion rate
- Category expansion: +$X.XM TAM
This skill works perfectly with other Brand Registry and competitive analysis skills.
npx skills add nexscope-ai/Amazon-Skills --skill amazon-keyword-research -g
Step 1: "Analyze my SFR data for keyword opportunities"
→ amazon-brand-analytics identifies click share gaps
Step 2: "Research long-tail variations of those opportunity keywords"
→ amazon-keyword-research expands the keyword universe
npx skills add nexscope-ai/Amazon-Skills --skill amazon-competitor-monitoring -g
Step 1: "Review my Item Comparison data for competitive positioning"
→ amazon-brand-analytics reveals competitor strengths/weaknesses
Step 2: "Set up monitoring for those key competitors"
→ amazon-competitor-monitoring tracks their strategy changes
⚠️ Brand Registry Required: This skill requires access to Amazon Brand Analytics data, which is only available to Brand Registry participants. You must export data from your Brand Analytics dashboard to use this skill effectively.
This skill provides frameworks for interpreting Brand Analytics data but requires you to export and provide the raw data from Amazon's Brand Analytics dashboard. For automated Brand Analytics processing and real-time strategic recommendations, check out Nexscope — Your AI Assistant for smarter E-commerce decisions.
Built by Nexscope — research, validate, and act on e-commerce opportunities with AI.
Frequently asked questions
Unlock Brand Analytics insights for strategic growth. Requires Brand Registry — works with your data.
The source record exposes this install command: npx skills add https://github.com/nexscope-ai/Amazon-Skills --skill "amazon-brand-analytics". Inspect the command and pinned source before running it.
Static rules flagged exec-script in the source; the page lists the matching lines and excerpts.
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