product-analytics

Product Analytics

Analyze Amazon products at the ASIN level using SimilarWeb Shopper Intelligence. Always load BRAND_PROFILE.md first for the user's tracked ASINs and domain.

Important API rules

1. Product endpoints support both variants — use time-series (get-products-sales-performance, get-products-top-keywords) with start_date, end_date, and granularity: "monthly" for trend data, or use the -agg variants for aggregated snapshots.
2. Always provide date ranges — use start_date and end_date in YYYY-MM format. Default to the last 6 months.
3. Category must be a numeric ID — never pass a category name. Use get-categories-search to resolve it.
4. Brand tools require category — pass the numeric category ID for all brand-level calls.

Core analyses

ASIN performance dashboard

Sales and traffic overview for a specific product.

1. Read BRAND_PROFILE.md for tracked ASINs, category ID, and domain
2. Call get-products-sales-performance (time-series) with asin, domain: <domain from BRAND_PROFILE.md>, start_date, end_date, granularity: "monthly" — get revenue, units, price over time; use latest month as snapshot
3. Call get-products-top-keywords (time-series) with asin, domain: <domain from BRAND_PROFILE.md>, start_date, end_date, limit: 20 — keyword drivers
4. Present: revenue, units sold, average price, top search keywords driving traffic

ASIN trend analysis

Track how a product's performance changes over time.

1. Call get-products-sales-performance (time-series) with asin, domain: <domain from BRAND_PROFILE.md>, start_date, end_date, granularity: "monthly"
2. Identify: growth/decline trajectory, seasonal patterns, price changes
3. Call get-products-top-keywords (time-series) with asin, domain: <domain from BRAND_PROFILE.md>, start_date, end_date, granularity: "monthly" to see if keyword mix is shifting
4. Flag: revenue growth decoupled from unit growth (price effect), new keywords appearing, keywords losing share

Portfolio overview

Analyze all tracked ASINs together.

1. Use get-brands-top-products-agg with brand, category (numeric ID), domain: <domain from BRAND_PROFILE.md>, limit: 20 — this returns all products with revenue, units, price, rating in one call
2. For deeper per-ASIN trends, call get-products-sales-performance (time-series) with explicit dates for each priority ASIN
3. Rank by revenue, units, growth rate
4. Classify: Stars (high revenue + growing), Cash cows (high revenue + flat/declining), Rising stars (low revenue + growing fast), Underperformers (low revenue + declining)

Competitive product comparison

Compare the user's ASIN against competitor products.

1. Identify competing ASINs via get-keywords-top-products-agg for the user's top keywords
2. For each competing ASIN, call get-products-sales-performance (time-series) with start_date, end_date, granularity: "monthly" for sales comparison
3. Call get-products-top-keywords (time-series) with start_date, end_date for both ASINs to compare keyword strategies
4. Highlight: keywords competitor wins that user doesn't index for, price positioning differences

Product keyword optimization

Find keyword gaps and opportunities for a specific ASIN.

1. Call get-products-top-keywords (time-series) with asin, domain: <domain from BRAND_PROFILE.md>, start_date, end_date for current keyword portfolio
2. Call get-categories-top-keywords-agg for category-level demand
3. Find category keywords with high volume where the ASIN has no presence
4. For each gap keyword, call get-keywords-top-products-agg to assess competition difficulty
5. Score opportunities: high volume + low competition = best opportunities

Presentation guidelines

• For portfolio views, use tables with clear ranking and classification
• Always include trend direction (arrow up/down) alongside absolute numbers
• When comparing products, normalize by price tier — a $10 product and $100 product have different benchmarks
• Link ASIN insights back to keyword strategy recommendations

Visual output

Always use the dashboard-ui skill for presenting results. After collecting data from the API calls above, build a single self-contained HTML dashboard and save it to the user's workspace folder.

Component mapping for product analytics

Analysis	Primary components
ASIN performance dashboard	KPI cards (revenue, units, avg price, keyword count), data table (top 20 keywords with clicks share), Chart.js doughnut chart (keyword traffic sources)
ASIN trend analysis	Chart.js line chart (monthly revenue + units + price), alert banner (if price effect detected), insight box (keyword mix shifts), classification badges (new / lost keywords)
Portfolio overview	Data table (all ASINs with revenue, units, growth, classification), classification badges (Star / Cash Cow / Rising Star / Underperformer), Chart.js bar chart (revenue by ASIN)
Competitive product comparison	Two-column layout (user ASIN vs competitor ASIN), data table (keyword overlap with share comparison), KPI cards (side-by-side metrics), insight box (positioning gaps)
Product keyword optimization	Data table (gap keywords with volume + competition score), classification badges (best opportunity / moderate / hard), share bar (current keyword coverage), alert banner (top opportunities)

Output rules

1. Read skills/dashboard-ui/SKILL.md for the full component library and CSS
2. Build the HTML using the dashboard shell template
3. Populate all data dynamically from API results — never use placeholder data
4. Save as .html to the workspace folder and link with computer://

SimilarWeb tools used

• get-products-sales-performance / get-products-sales-performance-agg — time-series for trends, -agg for aggregated snapshots
• get-products-top-keywords / get-products-top-keywords-agg — time-series for trends, -agg for aggregated snapshots
• get-brands-top-products / get-brands-top-products-agg — for portfolio-level data (works fine)
• get-keywords-top-products / get-keywords-top-products-agg — for competitive product discovery
• get-categories-top-keywords / get-categories-top-keywords-agg — for category keyword demand