amazon-listing-competitor-analysis-skill
# Amazon Listing Competitor Analysis Skill This skill analyzes Amazon competitor listings by ASIN through a two-phase workflow: Phase 1 extracts visible product data including titles, bullets, keywords, visuals, and pricing using the BrowserAct Amazon Listing Extractor, while Phase 2 diagnoses competitive strengths, market gaps, and unmet buyer needs to synthesize strategic opportunity points for the user's go-to-market. Use this skill when researching why a competitor listing converts well, identifying keyword placement patterns and SEO strategies, mining reviews for buyer psychology, comparing content approaches, or running gap analysis before launching a competing SKU.
git clone --depth 1 https://github.com/browser-act/skills /tmp/amazon-listing-competitor-analysis-skill && cp -r /tmp/amazon-listing-competitor-analysis-skill/solutions/ecommerce/amazon-listing-competitor-analysis-skill ~/.claude/skills/amazon-listing-competitor-analysis-skillSKILL.md
# Amazon Listing Competitor Analysis
## 📖 Brief
This skill runs a two-phase workflow on a single **competitor** Amazon listing. **Phase 1** uses the BrowserAct Amazon Listing Extractor for SEO template to pull visible product data from that listing. **Phase 2** diagnoses what that competitor does well and where the market shows gaps, then closes with **your strategic opportunity points** (how you can win next to them). Do **not** end with instructions that read like editing or rewriting **this competitor's** listing; the analyzed ASIN is evidence only. Final narrative output should be grounded in extracted data, not generic claims.
## ✨ Features
1. **No hallucinations, ensuring stable and accurate data extraction**: Pre-set workflows avoid AI generative hallucinations.
2. **No CAPTCHA issues**: No need to handle reCAPTCHA or other verification challenges.
3. **No IP restrictions or geo-blocking**: No need to deal with regional IP restrictions or geofencing.
4. **Faster execution**: Tasks execute faster compared to purely AI-driven browser automation solutions.
5. **Extremely high cost-efficiency**: Significantly reduces data acquisition costs compared to AI solutions that consume massive amounts of tokens.
## 🔑 API Key Guide
Before running, you must check the `BROWSERACT_API_KEY` environment variable. If it is not set, do not take other actions first; you should ask and wait for the user to provide it.
**Agent must inform the user**:
> "Since you haven't configured the BrowserAct API Key yet, please go to the [BrowserAct Console](https://www.browseract.com/reception/integrations) to get your Key."
## 🛠️ Input Parameters
When calling the script, the Agent should flexibly configure the following parameters based on user needs:
1. **ASIN**
- **Type**: `string`
- **Description**: The ASIN (Amazon Standard Identification Number) of the Amazon product to analyze.
- **Example**: `B0CS62LY6P`
- **Required**: Yes
2. **Marketplace_url**
- **Type**: `string`
- **Description**: The base URL of the Amazon marketplace. Use the correct regional site for the listing.
- **Example**: `https://www.amazon.com/`, `https://www.amazon.de/`
- **Default**: `https://www.amazon.com/`
## 🚀 Invocation Method
Run Phase 1 extraction with the script below. After structured data is returned, the Agent performs Phase 2 analysis using the framework in **Competitive Analysis Framework (Phase 2)**. The closing section must synthesize **opportunity points for the user's business**, not a checklist of edits applied to the competitor page under review.
```bash
python -u ./scripts/amazon_listing_competitor_analysis.py "B0CS62LY6P" "https://www.amazon.com/"
```
When only the ASIN is needed, the marketplace argument may be omitted; the script defaults to `https://www.amazon.com/`.
### ⏳ Running Status Monitoring
Since this task involves automated browser operations, it may take a long time (several minutes). The script will **continuously output status logs with timestamps** while running (e.g., `[14:30:05] Task Status: running`).
**Agent guidelines**:
- While waiting for the script to return results, please keep an eye on the terminal output.
- As long as the terminal continues to output new status logs, it means the task is running normally. Do not misjudge it as a deadlock or unresponsiveness.
- If the status remains unchanged for a long time or the script stops outputting without returning a result, only then consider triggering the retry mechanism.
## 📊 Data Output
Upon successful execution, the script prints the API result string (or full task JSON if no string field is present). Typical fields include:
- `asin`, `title`, `product_url`, `brand`, `price`, `coupon_text`, `rating`, `review_count`, `best_sellers_rank`, `availability`, `prime_eligible`
- `description`, `short_description`, `category`, `key_features`, `bullet_points`
- `main_image_url`, `additional_image_urls`, `seller_name`, `ships_from`, `sold_by`
- `specifications`, `product_details`, `attributes`, and review-related blocks (reviewer, content, date, helpful votes, etc.)
Use this payload as the single source of truth for Phase 2; do not invent listing facts.
## ⚠️ Error Handling & Retry
During script execution, if errors occur (such as network fluctuations or task failure), the Agent should follow this logic:
1. **Check the output content**:
- If the output **contains** `"Invalid authorization"`, it means the API Key is invalid or expired. At this point, **do not retry**, but guide the user to recheck and provide the correct API Key.
- If the output **contains** `"concurrent"` or `"too many running tasks"` or similar concurrency limit messages, it means the concurrent task limit for the current subscription plan has been reached. **Do not retry**; guide the user to upgrade their plan.
**Agent must inform the user**:
> "The current task cannot be executed because your BrowserAct account has reached the limit of concurrent tasks. Please go to the [BrowserAct Plan Upgrade Page](https://www.browseract.com/reception/recharge) to upgrade your subscription plan and enjoy more concurrent task benefits."
- If the output **does not contain** the above error keywords but the task fails (e.g., output starts with `Error:` or returns empty results), the Agent should **automatically try to run the script once more**.
2. **Retry limit**:
- Automatic retry is limited to **once**. If the second attempt still fails, stop retrying and report the specific error message to the user.
## 🌟 Typical Use Cases
1. **Competitor listing teardown**: Analyze one ASIN to see title formula, bullets, and differentiation language.
2. **Keyword placement audit**: Map where primary and long-tail terms appear across title, bullets, and description or A+ content.
3. **Visual strategy review**: Infer image narrative, infographic highlights, and video approach from extracted media data.
4. **Buyer-validated selling points**: Use high-Extracts comprehensive wholesale product data from 1688.com product detail pages: title, tiered pricing, SKU variants with dimensions/weight, product images, seller info, shop scores, buyer protection, cross-border flags, product attributes, coupon/promotion data, and review stats. Use when user mentions 1688, 1688.com, wholesale China, alibaba wholesale, B2B China sourcing, Chinese wholesale scraper, 1688 product scrape, 1688 offer, 1688 detail, extract 1688 data, pull 1688 listings, get wholesale price, 1688 supplier info, factory stats 1688, 1688 SKU variants, 1688 product attributes, 1688 shop score, DSR score 1688, 1688 buyer protection, 1688 cross-border, 1688 dropship. Also applies to: scraping bulk product data from 1688 by offer ID list, monitoring 1688 supplier metrics, extracting 1688 pricing tiers for resale analysis.
Fetches complete Airbnb listing details for a given numeric listing ID via the internal GraphQL API, returning title, room type, description, amenities, photos, coordinates, city, house rules, highlights, ratings, review count, bedroom configuration, and property overview. Use when user mentions Airbnb listing details, Airbnb property info, Airbnb room details, get Airbnb listing data, Airbnb amenities list, Airbnb house rules, Airbnb property description, Airbnb detail page scraper, Airbnb rooms detail, Airbnb property page data, Airbnb listing info, fetch Airbnb room details, pull Airbnb listing.
Extracts Airbnb accommodation search results from a destination query via SSR-embedded data, returning listing ID, URL, name, coordinates, rating, price, photos, and badge info for each result, plus pagination cursors for multi-page retrieval. Use when user mentions Airbnb search results, Airbnb listings, vacation rental search, short-term rental listings, scrape Airbnb, get Airbnb data, find rentals on Airbnb, Airbnb destination search, Airbnb property list, Airbnb stays search, Airbnb accommodation results, pull Airbnb listings, collect Airbnb search data, Airbnb scraper, Airbnb search page extraction, Airbnb search by destination.
Amazon Alexa for Shopping Q&A automation: submits questions to Amazon's Alexa/Rufus AI shopping assistant and collects response text; supports optional keyword search context (navigate to search results page before asking for category-specific answers). Use when user mentions Amazon Alexa, Rufus, Amazon shopping assistant, Amazon AI chat, ask Amazon, Amazon Q&A, automate Alexa questions, Rufus chatbot, Amazon assistant automation, collect Alexa responses, bulk question submission to Amazon, keyword search context, category research. Also applies to extracting Amazon product recommendations from conversational AI, automating repeated queries to Amazon's AI shopping feature, collecting Alexa shopping responses at scale, or market research within a specific product category.
This skill helps users extract structured product details from Amazon using a specific ASIN (Amazon Standard Identification Number). Use this skill when the user asks to get Amazon product details by ASIN, lookup Amazon product title and price using ASIN, extract Amazon product ratings and reviews count for a specific ASIN, check Amazon product availability and current price, get Amazon product description and features via ASIN, enrich product catalog with Amazon data using ASIN, monitor Amazon product price changes for specific ASINs, retrieve Amazon product brand and material information, fetch Amazon product images and specifications by ASIN, validate Amazon ASIN and get product metadata.
This skill helps users extract structured best-selling product data from Amazon via the BrowserAct API. Agent should proactively apply this skill when users express needs like search for best selling products on Amazon, extract Amazon product data based on keywords, find top rated Amazon products, monitor Amazon competitor prices and sales, discover trending products on Amazon marketplace, extract Amazon product titles prices and ratings, gather Amazon product sales volume for market research, search Amazon best sellers in specific region, collect Amazon product reviews and promotion details, analyze Amazon product availability and badges, get Amazon product data for market analysis.
Amazon Best Sellers listing scraper: extract product cards from any Amazon Best Sellers (zgbs) or /gp/bestsellers/ category page — returns rank (position on chart), asin, title, url, image, imageAlt, price, stars, reviewCount, ratingRaw per item, plus category metadata (categoryName, categoryFullName, categoryUrl) and pagination state (currentPage, hasNextPage, nextPageUrl). Works across all Amazon regional TLDs (amazon.com, amazon.co.uk, amazon.de, amazon.co.jp, amazon.fr, amazon.it, amazon.es, amazon.ca, amazon.com.au, amazon.in, etc.). Use when user mentions Amazon Best Sellers, Amazon bestsellers, Amazon top 100, Amazon zgbs, Amazon /zgbs/, Amazon /gp/bestsellers/, Amazon Best Sellers Rank, Amazon BSR, Amazon top ranked products, Amazon top-selling products, Amazon chart, Amazon category ranking, Amazon best sellers by category, Amazon best sellers electronics, Amazon best sellers kitchen, Amazon best sellers toys, scrape Amazon bestsellers, extract Amazon top 100, Amazon rank scraper, Amazon best seller list, Amazon leaderboard, Amazon trending products, discover trending Amazon products, Amazon niche discovery, Amazon top ranked ASINs. Also applies to competitive intelligence via ranking snapshots, spotting up-and-coming products, sourcing bestseller ASINs for further enrichment, tracking rank changes over time, and building bestseller-per-category datasets.
This skill helps users extract basic product details other sellers prices and seller ratings from Amazon via ASIN automatically using the BrowserAct API. Agent should proactively apply this skill when users express needs like query Amazon buy box information, monitor Amazon product prices, extract Amazon product details by ASIN, check other sellers prices on Amazon, get Amazon seller ratings and feedback count, monitor buy box ownership for a specific ASIN, track Amazon fulfillment methods for competitors, compare Amazon product prices across different sellers, retrieve Amazon buy box availability status, analyze Amazon seller profile details.