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  • 优麦云 广告投放

    比亚马逊后台更好用的广告工具

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Function Manual

20+ Exclusive Data-Driven Product Research Strategies

2025/10/15 Read Count (1,847) Comment Count (0)

Organized into three categories—Keyword‑Driven, Product‑Driven, and Category‑Driven—these models come with suggested filters for reference. Please adjust the exact thresholds to fit your own situation.

 

1. Keyword‑Driven Big‑Data Sourcing

 

Every Amazon search reveals real buyer demand. Keyword‑Driven sourcing uses those searches to uncover emerging niches and then find products to meet that demand.
 
Focus less on saturated head‑keywords and more on surging trends. Weekly rank movements capture real‑time shifts in interest.
Filter: In any category, select keywords whose rank improvement over the past 4 weeks > 10,000 and rank growth rate > 10%.

 

 

Keywords ranking in the Top 10,000 represent the highest‑demand niches. These have large traffic but stiff competition—best for well‑capitalized sellers.
Filter: In a category, limit max keyword rank to 10,000; results sort ascending by rank.

 

 

Keywords with solid ranks that are growing—but not yet head keywords—indicate mid‑tier niches with room for newcomers.
Filter: Rank between 20,000–100,000 and 1‑week rank growth > 20%.

 

 

Keywords whose rank jumps sharply signal urgent, often seasonal or nascent opportunities. Use Trends or Google Trends to confirm.
Filter: In a category, 1‑week rank growth > 50%.

 

 

Search volume reflects market demand size. Big sellers prefer markets with monthly searches >100,000. Smaller sellers may start with lower-volume markets.  
Filter: Monthly volume > 100,000, month‑over‑month growth > 10% and optional criteria (e.g., price).

 

 

'Click Concentration' measures how much of a keyword’s clicks go to its Top 3 ASINs—low concentration means less monopoly, easier entry.
Filter: Click Concentration < 50%, or sort keywords ascending by that metric.

 

 

Find keywords that have volume this month but had none last year—pure new markets hungry for selection.
Filter: Monthly searches > 10,000, search growth > 10%, then tick 'New Sub-market Opportunities' to isolate truly new segments.

 

 

Seasonal products turn quickly. Track seasonal keyword cycles to prepare listings in advance.
Filter: Choose category → select relevant month in ‘Market Cycle’.

 

 

'Traffic Cost' = PPC bid / average price. Lower percentages mean lower marketing cost and often less competition.
Filter: Sort segments ascending by 'Traffic Cost'.

 

 

Long‑tail keywords (≥ 3 words) have lower volume but highly targeted traffic and often higher conversion. Ideal for smaller sellers.
Filter: Keywords ≥ 3 words in your chosen category.

 

 


 

2. Product‑Driven Big‑Data Sourcing

 

Analyze product-level metrics (sales growth, reviews, etc.) to identify opportunities.
 
Low current volume but showing growth momentum.
Filter: Monthly sales < 600, growth > 10%, launched in last 6 months (Preset: Potential).

 

 

High sales but low rating = improvement opportunity.
Filter: Monthly sales > 1,000, rating < 3.7.

 

 

FBM products with decent sales = lower upfront cost.
Filter: Monthly sales > 1,000, fulfillment = FBM.

 

 

Find high-sales products with ≥3 sellers—possible resell opportunities.
Filter: Monthly sales > 1,000, seller count > 3.

 

 

High rating, low Q&A = easy to support, ideal products with low after‑sale costs.  
Filter: Monthly sales > 1,000, BSR 5,000–10,000, rating > 4.0, Q&A < 5.

 

 

On Amazon’s bestseller list with low reviews + recent launch = easier to enter.
Filter: Launched in last 3 months, review count < 50.

 

 

Track successful sellers’ new listings for inspiration.
Filter: Use New Listing Tracker to find promising new releases.

 

 

Monitor new brand products for white-labeling or differentiation.
Filter: Enter brand name and sort listings by 'Date First Available' descending.

 

 

Small or standard sizes keep FBA fees low.
Filter: Monthly sales > 1,000, select by product size; large items only if you have logistics leverage.

 

 

High sales but low Listing Quality Score = easy to outperform.
Filter: Monthly sales > 1,000, LQS < 5.

 

 

Track new Amazon retail listings—leverage Amazon’s market insights.
Filter: Fulfillment = AMZ, launched in last 3 months.

 

 

Cheap products with high volume—low risk for new sellers but need volume to win.
Filter: Monthly sales > 3,000, review count < 100, price < $10.

 

 

Deep-dive into a familiar niche to build brand and product line—e.g. phone stands → phone stands with storage, floor stands, etc.
Filter: In 'Related Products', enter an ASIN and click 'CSI' (Compare with similar items).

 

 

Expand into complementary items (e.g., yoga mats → yoga blocks) using frequently bought together data.
Filter: In 'Related Products', enter an ASIN and click 'FBT' (frequently bought together).

 

 


 

3. Category‑Driven Big‑Data Sourcing

 

Each Amazon category is its own micro‑market. By comparing multiple markets’ metrics, find the niche that best matches your strengths.
 
Analyze product/brand/seller concentration to find distributed markets with lower entry barriers.
Filter: In 'Market Research', set max Product/Brand/Seller concentration to 80%, or sort ascending.

 

 

A higher market volatility means faster product updates and more chances for new products to enter. But it can also mean the market is unstable—products may not last long if they don’t perform well. Categories like fashion often have lots of new listings, but short product lifecycles. By checking the number of new products in a subcategory, sellers can gauge how competitive or risky that market is.
Filter: In 'Market Research', sort by new product count (descending) to spot high-opportunity markets.

 

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