E-Commerce Product Research — Niche Analysis Suite

Research any product niche across Amazon, eBay, Etsy, Walmart, and AliExpress in a single run. Get comprehensive analytics including competition density, price distribution, review velocity, sales volume estimates, top sellers, market gaps, and a niche opportunity score.

Who is this for?

• Dropshippers — Find profitable niches before investing in inventory
• Amazon FBA sellers — Validate private label ideas with real market data
• Market researchers — Compare pricing and competition across 5 major platforms
• Private label brands — Identify market gaps and underserved price segments
• E-commerce consultants — Generate data-backed niche reports for clients
• Arbitrage sellers — Discover cross-platform price spreads

What you get

Per-product data

Field	Description
platform	Which marketplace (amazon, ebay, etsy, walmart, aliexpress)
title	Product name
price / priceUsd	Current price (normalized to USD)
priceOriginal	Original/list price (if on sale)
rating	Star rating (0-5)
reviewCount	Number of reviews/ratings
seller / brand	Seller or brand name
salesEstimate	Estimated monthly sales volume
listingAgeDays	Estimated listing age in days
bsr	Best Seller Rank (Amazon/Walmart)
imageUrl	Product image URL
url	Direct link to product page

Per-platform analytics

Metric	Description
avgPrice / medianPrice	Price center points
priceStdDev / priceIQR	Price spread
priceBuckets	Price distribution histogram
avgRating	Average star rating
avgReviews / reviewVelocity	Review activity metrics
competitionDensity	very_low / low / medium / high / very_high
competitionScore	0-100 numeric score
topSellers	Top 10 sellers by market share
marketGaps	Identified opportunities (price gaps, quality gaps, etc.)
nicheOpportunityScore	0-100 overall opportunity rating

Cross-platform summary

• Overall competition assessment (open / moderate / competitive / saturated)
• Best platform for market entry with reasoning
• Suggested retail price (sweet spot based on price distribution)
• Arbitrage opportunities (cross-platform price spreads)
• Niche verdict (excellent_opportunity / good_opportunity / moderate / challenging / avoid)

How it works

1. Enter a product keyword or niche (e.g., "wireless earbuds", "yoga mats")
2. Select which platforms to search (default: all 5)
3. The actor scrapes search results from each platform
4. Products are deduplicated and normalized (prices converted to USD)
5. Sales volume is estimated using review-count heuristics
6. Competition density is computed from seller concentration, review depth, and price spread
7. Market gaps are identified (price gaps, quality gaps, underserved segments)
8. A niche opportunity score (0-100) is calculated for each platform
9. Cross-platform summary with arbitrage detection and market entry recommendations

Input parameters

Parameter	Type	Default	Description
keyword	string	required	Product keyword or niche to research
platforms	array	all 5	Which platforms to search
maxResultsPerPlatform	integer	50	Max products per platform (5-200)
priceMin	number	—	Minimum price filter (USD)
priceMax	number	—	Maximum price filter (USD)
sortBy	enum	relevance	Sort order: relevance, price_low, price_high, rating, reviews
proxyConfiguration	object	—	Proxy settings (residential recommended)

Example input

{
    "keyword": "wireless earbuds",
    "platforms": ["amazon", "ebay", "etsy", "walmart", "aliexpress"],
    "maxResultsPerPlatform": 50,
    "sortBy": "relevance",
    "proxyConfiguration": {
        "useApifyProxy": true,
        "apifyProxyGroups": ["RESIDENTIAL"]
    }
}

Example output (product)

{
    "platform": "amazon",
    "title": "Wireless Earbuds Bluetooth 5.3 with Charging Case",
    "price": 29.99,
    "priceUsd": 29.99,
    "currency": "USD",
    "rating": 4.4,
    "reviewCount": 12847,
    "seller": "TechBrand",
    "brand": "TechBrand",
    "isPrime": true,
    "isBestSeller": false,
    "salesEstimate": 10706,
    "salesEstimateLabel": "~10.7K/mo",
    "listingAgeDays": 540,
    "url": "https://www.amazon.com/dp/B0XXXXXXXXX"
}

Example output (niche analytics)

{
    "type": "platform_analytics",
    "platform": "amazon",
    "keyword": "wireless earbuds",
    "totalProducts": 48,
    "avgPrice": 34.52,
    "medianPrice": 29.99,
    "priceStdDev": 18.73,
    "avgRating": 4.3,
    "avgReviews": 5240,
    "competitionDensity": "very_high",
    "competitionScore": 85,
    "nicheOpportunityScore": 32,
    "topSellers": [
        { "name": "Apple", "productCount": 3, "totalReviews": 890234, "avgPrice": 179.00 }
    ],
    "marketGaps": [
        { "type": "price_gap", "description": "No products priced between $75 and $129", "suggestedPrice": 99.99 }
    ]
}

Example output (cross-platform summary)

{
    "type": "cross_platform_summary",
    "keyword": "wireless earbuds",
    "totalProductsAnalyzed": 230,
    "overallCompetition": "competitive",
    "bestPlatformForEntry": "etsy",
    "nicheVerdict": "moderate_opportunity",
    "suggestedRetailPrice": 24.99,
    "arbitrageOpportunity": {
        "buyFrom": "aliexpress",
        "buyAvgPrice": 8.50,
        "sellOn": "amazon",
        "sellAvgPrice": 34.52,
        "spreadPercent": 306,
        "viable": true
    }
}

Pricing

$0.008 per product analyzed (pay-per-event pricing).

• Researching 50 products across 5 platforms (250 total) costs ~$2.00
• Researching 100 products across 3 platforms (300 total) costs ~$2.40
• Single-platform research (50 products) costs ~$0.40

Tips for best results

1. Use residential proxies — Amazon and Walmart aggressively block datacenter IPs
2. Start with all 5 platforms — cross-platform data gives the most valuable insights
3. Use specific keywords — "bamboo yoga mat" is better than "mat"
4. Set price filters to focus on your target market segment
5. Compare multiple keywords — run the actor for related niches to find the sweet spot
6. Check the niche verdict — scores above 55 indicate good opportunities
7. Look at market gaps — price gaps and quality gaps are actionable entry points

Technical details

• Built with CheerioCrawler (no browser overhead, fast execution)
• Anti-bot measures: rotating user agents, realistic headers, platform-specific referers
• Price normalization across currencies using built-in exchange rates
• Sales volume estimation using industry-standard review-to-sales multipliers
• All 5 platform scrapers are inline (no external dependencies)

Limitations

• AliExpress and Walmart may require JavaScript rendering for some pages; results may be partial
• Sales estimates are approximations based on review counts (actual sales data is proprietary)
• Exchange rates are approximate; for exact conversions, use a live forex API
• Listing age is estimated from review velocity (platforms do not expose exact listing dates on search pages)

Integration — Python

from apify_client import ApifyClient

client = ApifyClient("YOUR_API_TOKEN")
run = client.actor("sovereigntaylor/ecommerce-product-research").call(run_input={
    "searchTerm": "example query",
    "maxResults": 50
})

for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(f"{item.get('title', item.get('name', 'N/A'))}")

Integration — JavaScript

import { ApifyClient } from 'apify-client';
const client = new ApifyClient({ token: 'YOUR_API_TOKEN' });

const run = await client.actor('sovereigntaylor/ecommerce-product-research').call({
    searchTerm: 'example query',
    maxResults: 50
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach(item => console.log(item.title || item.name || 'N/A'));