amazon-brand-analytics

Name: amazon-brand-analytics
Author: nexscope-ai

631installs70forks

How to install amazon-brand-analytics?

nexscope-ai/amazon-skills/amazon-brand-analytics

$npx -y skills add nexscope-ai/Amazon-Skills --skill amazon-brand-analytics

Installs into the current project.

Summary

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.

Files · 1

View on GitHub

SKILL.md

1	# Amazon Brand Analytics 📊
2
3	Unlock Brand Analytics insights for strategic growth. Requires Brand Registry — works with your data.
4
5	## Installation
6
7	```bash
8	npx skills add nexscope-ai/Amazon-Skills --skill amazon-brand-analytics -g
9	```
10
11	## Capabilities
12
13	- Search Frequency Rank (SFR) analysis: Decode keyword opportunities, click share gaps, and conversion optimization
14	- Market Basket intelligence: Identify cross-sell opportunities, bundle strategies, and category expansion
15	- Item Comparison insights: Understand competitive positioning and customer consideration factors
16	- Demographic analysis: Extract customer segment insights and geographic opportunities
17	- Seasonal trend detection: Identify timing patterns and market shifts from search data
18	- Strategic recommendations: Convert raw data into actionable growth strategies
19	- Multi-marketplace support: Works with Brand Analytics from all Amazon regions
20
21	## Usage Examples
22
23	Users can ask naturally. Examples:
24
25	```
26	Analyze my Search Frequency Rank data for "wireless earbuds" — show keyword opportunities and click share gaps
27	```
28
29	```
30	Review my Market Basket data for the last 6 months. What cross-sell and bundling opportunities do you see?
31	```
32
33	```
34	Interpret my Item Comparison report for yoga mats — how do customers evaluate my product vs competitors?
35	```
36
37	```
38	Generate Brand Analytics strategy report for Q4 combining SFR, Market Basket, and demographic data
39	```
40
41	```
42	Find seasonal trends and opportunity keywords from my Brand Analytics data for kitchen appliances
43	```
44
45	## Three Analysis Modes
46
47	\| Mode \| Input Required \| Output \| Best For \|
48	\|------\|----------------\|--------\|----------\|
49	\| SFR Analysis \| Search Frequency Rank data export \| Keyword opportunities, click/conversion gaps \| Advertising optimization \|
50	\| Market Basket \| Market Basket Analysis export \| Cross-sell opportunities, bundle recommendations \| Product strategy \|
51	\| Item Comparison \| Item Comparison report data \| Competitive positioning insights \| Product development \|
52
53	## Workflow
54
55	### Step 1: Data Preparation
56
57	For SFR Analysis:
58	1. Export Search Frequency Rank report from Brand Analytics (last 90 days recommended)
59	2. Focus on top 100-200 keywords by search frequency rank
60	3. Note current click share and conversion share for each keyword
61
62	For Market Basket Analysis:
63	1. Export Market Basket Analysis report (6-12 months for pattern recognition)
64	2. Include both "Customers who bought X also bought Y" data
65	3. Filter for statistically significant purchase combinations (10+ co-purchases)
66
67	For Item Comparison:
68	1. Export Item Comparison report for your main ASINs
69	2. Include comparison data with top 5-10 competitors
70	3. Note customer consideration patterns and demographic breakdowns
71
72	### Step 2: Pattern Recognition
73
74	Use the provided data to identify:
75
76	SFR Insights:
77	- Keywords with high search frequency but low click share (opportunity gaps)
78	- Conversion share significantly below click share (optimization needs)
79	- Seasonal search pattern changes
80	- Emerging keyword trends
81
82	Market Basket Patterns:
83	- Products with >25% co-purchase rate (strong bundle candidates)
84	- Category cross-over patterns (expansion opportunities)
85	- Price point correlations in purchase combinations
86	- Geographic or demographic purchase pattern differences
87
88	Item Comparison Analysis:
89	- Customer consideration factors ranked by importance
90	- Your brand's competitive strengths and weaknesses
91	- Price sensitivity patterns in your category
92	- Feature preferences by customer segment
93
94	### Step 3: Strategic Synthesis
95
96	Convert insights into actionable recommendations following the output format below.
97
98	## Output Format
99
100	Present analysis in this structure:
101
102	```
103	## Brand Analytics Strategic Report: [Brand/Category]
104
105	Analysis Period: [timeframe] \| Data Sources: [SFR/Market Basket/Item Comparison]
106	Marketplace: Amazon [region] \| Report Date: [current date]
107
108	### 1. Search Frequency Rank Opportunities
109
110	Top Keyword Gaps:
111
112	\| Keyword \| Search Rank \| Your Click Share \| Category Avg \| Opportunity Score \|
113	\|---------\|-------------\|------------------\|--------------\|--------

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amazon-brand-analytics

631installs70forks

View on GitHub

How to install amazon-brand-analytics?

nexscope-ai/amazon-skills/amazon-brand-analytics

$npx -y skills add nexscope-ai/Amazon-Skills --skill amazon-brand-analytics

Installs into the current project.

Summary

Files · 1

View on GitHub

SKILL.md

1	# Amazon Brand Analytics 📊
2
3	Unlock Brand Analytics insights for strategic growth. Requires Brand Registry — works with your data.
4
5	## Installation
6
7	```bash
8	npx skills add nexscope-ai/Amazon-Skills --skill amazon-brand-analytics -g
9	```
10
11	## Capabilities
12
13	- Search Frequency Rank (SFR) analysis: Decode keyword opportunities, click share gaps, and conversion optimization
14	- Market Basket intelligence: Identify cross-sell opportunities, bundle strategies, and category expansion
15	- Item Comparison insights: Understand competitive positioning and customer consideration factors
16	- Demographic analysis: Extract customer segment insights and geographic opportunities
17	- Seasonal trend detection: Identify timing patterns and market shifts from search data
18	- Strategic recommendations: Convert raw data into actionable growth strategies
19	- Multi-marketplace support: Works with Brand Analytics from all Amazon regions
20
21	## Usage Examples
22
23	Users can ask naturally. Examples:
24
25	```
26	Analyze my Search Frequency Rank data for "wireless earbuds" — show keyword opportunities and click share gaps
27	```
28
29	```
30	Review my Market Basket data for the last 6 months. What cross-sell and bundling opportunities do you see?
31	```
32
33	```
34	Interpret my Item Comparison report for yoga mats — how do customers evaluate my product vs competitors?
35	```
36
37	```
38	Generate Brand Analytics strategy report for Q4 combining SFR, Market Basket, and demographic data
39	```
40
41	```
42	Find seasonal trends and opportunity keywords from my Brand Analytics data for kitchen appliances
43	```
44
45	## Three Analysis Modes
46
47	\| Mode \| Input Required \| Output \| Best For \|
48	\|------\|----------------\|--------\|----------\|
49	\| SFR Analysis \| Search Frequency Rank data export \| Keyword opportunities, click/conversion gaps \| Advertising optimization \|
50	\| Market Basket \| Market Basket Analysis export \| Cross-sell opportunities, bundle recommendations \| Product strategy \|
51	\| Item Comparison \| Item Comparison report data \| Competitive positioning insights \| Product development \|
52
53	## Workflow
54
55	### Step 1: Data Preparation
56
57	For SFR Analysis:
58	1. Export Search Frequency Rank report from Brand Analytics (last 90 days recommended)
59	2. Focus on top 100-200 keywords by search frequency rank
60	3. Note current click share and conversion share for each keyword
61
62	For Market Basket Analysis:
63	1. Export Market Basket Analysis report (6-12 months for pattern recognition)
64	2. Include both "Customers who bought X also bought Y" data
65	3. Filter for statistically significant purchase combinations (10+ co-purchases)
66
67	For Item Comparison:
68	1. Export Item Comparison report for your main ASINs
69	2. Include comparison data with top 5-10 competitors
70	3. Note customer consideration patterns and demographic breakdowns
71
72	### Step 2: Pattern Recognition
73
74	Use the provided data to identify:
75
76	SFR Insights:
77	- Keywords with high search frequency but low click share (opportunity gaps)
78	- Conversion share significantly below click share (optimization needs)
79	- Seasonal search pattern changes
80	- Emerging keyword trends
81
82	Market Basket Patterns:
83	- Products with >25% co-purchase rate (strong bundle candidates)
84	- Category cross-over patterns (expansion opportunities)
85	- Price point correlations in purchase combinations
86	- Geographic or demographic purchase pattern differences
87
88	Item Comparison Analysis:
89	- Customer consideration factors ranked by importance
90	- Your brand's competitive strengths and weaknesses
91	- Price sensitivity patterns in your category
92	- Feature preferences by customer segment
93
94	### Step 3: Strategic Synthesis
95
96	Convert insights into actionable recommendations following the output format below.
97
98	## Output Format
99
100	Present analysis in this structure:
101
102	```
103	## Brand Analytics Strategic Report: [Brand/Category]
104
105	Analysis Period: [timeframe] \| Data Sources: [SFR/Market Basket/Item Comparison]
106	Marketplace: Amazon [region] \| Report Date: [current date]
107
108	### 1. Search Frequency Rank Opportunities
109
110	Top Keyword Gaps:
111
112	\| Keyword \| Search Rank \| Your Click Share \| Category Avg \| Opportunity Score \|
113	\|---------\|-------------\|------------------\|--------------\|--------

People who liked this also viewed

6 picks

Type