Optimize product visibility in Amazon search results. Analyze current search ranking factors, identify optimization gaps, and provide actionable improvement plans for the Amazon A9/COSMO algorithm.
Supported platforms: Amazon、Shopify、WooCommerce、Walmart、TikTok Shop、Etsy、eBay、BigCommerce。
How to use
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Features
- Search ranking factor analysis (relevance, performance, customer satisfaction)
- A9 algorithm title optimization (keyword placement, structure)
- Bullet point optimization (conversion and indexing)
- Index verification methodology
- Mine search terms from automatic ad campaigns
- Ranking improvement action plan with priority scoring
How it works
Step 1: Collect information from the user message — product, platform, current situation, and goals.
Step 2: Ask all follow-up questions at once in multiple-choice format. Allow abbreviated answers (e.g., "1b 2c 3a").
Step 3: Conduct research and analysis using the framework and methodology below.
A9 Algorithm Analysis
Amazon's A9 algorithm (now evolved into a comprehensive search system that includes COSMO semantic understanding) is the core engine that determines product ranking:
Relevance-first principle:
- A9 first filters products relevant to the user's search query.
- Relevance is based on: matching product information (title, bullet points, backend keywords) with search terms.
- Keywords weighted by position: Title highest → bullet points → backend keywords.
- Keywords appearing earlier in the title carry higher weight.
Sales performance weighting:
- Among relevant products, A9 ranks by historical sales performance.
- Core metrics: recent sales velocity (past 24-48 hour window), conversion rate, click-through rate.
- Sales momentum (recent sales growth rate) has a particularly large impact — this is why new products need advertising/promotions to accumulate initial sales.
Customer satisfaction factors:
- Star rating, number of reviews, return rate.
- High rating + low returns = ranking boost; low rating + high returns = ranking penalty.
COSMO Semantic Understanding System
COSMO adds deep semantic understanding to search — traditional keyword stuffing becomes less effective:
- Intent recognition: COSMO understands the consumer intent behind a search query, not just keyword matching. For example, "birthday gift for 12-year-old boy" = gift recommendation intent, not just products containing those words.
- Context analysis: COSMO analyzes the context of a consumer's browsing/purchase history — the same search may show different results to different consumers.
- Knowledge graph integration: COSMO builds a product relationship knowledge graph — understanding attribute relationships (e.g., "wireless earphones" is equivalent to "Bluetooth earphones").
Index Verification Methodology
The first step in search optimization = confirm the product is correctly indexed by Amazon:
- ASIN index detection: Search "ASIN + product keyword" in the Amazon search box — if the product appears, it means it is indexed for that keyword.
- Long-tail verification first: First verify lower-competition long-tail keywords (fewer results = easier to confirm). Progress gradually from long-tail to core keywords.
- New index trigger: Product information updates (title changes, new backend keywords) take hours to days to reindex.
Ranking Improvement Action Framework
- Title optimization: Reposition keywords based on search volume and competition. Core principle: most important keywords first, secondary keywords in remaining space, maintain readability and brand recognition.
- Bullet points dual optimization: Bullet points affect both search indexing and conversion. Optimization covers: index coverage (ensure key search terms are in the bullet points) and conversion guidance (most attractive selling points first).
- Search term expansion: Mine high-converting search terms from auto campaign reports, add them to backend or product information.
- Sales signal activation: Through ads, promotions, coupons — short-term activate sales signals to drive ranking improvement. Calculate the estimated sales needed to reach the first page based on target keyword competition intensity.
Data Sources
- web_fetch for Amazon product pages and search results.
- web_search for competitor listing information, keyword index verification.
- User-provided: current ranking position, target keywords, review count, rating, product price.
Limitations
- The exact A9/COSMO ranking formula is an Amazon trade secret — the analysis is based on industry research and cannot be guaranteed to fully match the actual algorithm.
- Ranking improvement time and magnitude are affected by uncontrollable factors — competitor optimization actions, platform algorithm adjustments, market environment changes. No guarantee of ranking improvement can be made.
- Budget estimates for sales activation are based on industry averages — actual execution may vary greatly due to category competition and ad quality score.
- Index verification is based on surface observation of search results — cache delays may cause misjudgment, requiring multiple verifications.
- Search optimization requires long-term sustained effort — short-term ranking fluctuations should not be overinterpreted.
Step 4: Provide structured, actionable output containing specific recommendations rather than vague guidance.
Output Format
- Give a summary of findings first
- Include specific data points and benchmarks (if any)
- Provide prioritized action items
- Estimates based on incomplete data need to be marked with ⚠️
- End with specific follow-up steps