Wildberries Niche Analyzer: аналитика ниш WB

Analyze any Wildberries keyword as a market, not a product list. One aggregate row per niche: seller and brand counts, competition concentration, the ruble price band, ratings, and review demand. Built for sellers deciding where to compete.
Wildberries (Вайлдберриз) suite   •  Products, sellers, reviews, prices, resale, and niche analysis
Product Search Products, prices, and full catalogs	Seller Scraper Supplier intel and shop stats	Reviews Scraper Ratings, text and buyer photos
Price Tracker Price and search-rank monitoring	Resale Scraper Resale and secondhand listings	Niche Analyzer ➤ You are here

See how crowded a Wildberries niche is before you source inventory Give the Actor a shortlist of keywords and get one market-summary row for each: how many sellers compete, how tightly they hold the niche, the ruble price band, ratings, and review demand. The research you would pay an analytics subscription for, on demand.

🧭 One row per niche Each keyword comes back as a single market summary, not a catalog to sort yourself.

🧮 Competition, scored A 0 to 10000 concentration index shows how many sellers already own the niche.

🏷️ Ruble price band Minimum, average, median, and maximum price show you where the market sits.

📈 Ratings and demand Average ratings and total review counts flag the quality bar and buyer interest.

Turn a Wildberries (Вайлдберриз) keyword into a market verdict. Instead of a pile of products to sort, the Niche Analyzer samples the live search results for each keyword and returns one aggregate row that scores the niche on competition, price, and demand. It runs on the Apify platform with API access, scheduling, integrations (Make, Zapier, Google Sheets), proxy rotation, and run monitoring built in.

🔍 What does Wildberries Niche Analyzer do?

Give it a list of keywords, in Russian or English, and it returns one market-summary row per keyword. Each row tells you how contested the niche is and how much demand it carries:

• Competition and saturation - distinct seller count, brand count, a seller concentration index (0 to 10000), the top seller's share, and the biggest sellers and brands by name.
• Price band - minimum, average, median, and maximum price in rubles, so you know where the market sits.
• Quality bar - the average rating incumbents have earned and the share of products that carry ratings.
• Demand signal - the cumulative reviews products in the niche have collected. This is a demand proxy, not a sales or revenue estimate.
• Availability - the share of sampled products currently in stock.

This is the sibling of the Wildberries Scraper, which returns one row per product. The Niche Analyzer returns one row per market, so you can compare a whole shortlist of niches side by side and decide where to compete.

⚡ Research a niche before you spend on inventory. No account or login needed. Compare a full shortlist of keywords in one run and see where you still have room to compete.

💡 Why use Wildberries Niche Analyzer?

• I am a new Wildberries seller comparing ten product niches at once to pick the one with the fewest entrenched sellers, so I commit my first inventory budget where I actually have room to rank.
• I am a reseller sourcing from wholesalers checking the price band and in-stock rate of a niche before I place a bulk order, so I never stock a category that is already a price war.
• I am an established seller expanding my range scanning adjacent keywords for the ones where the top few sellers do not already own most of the shelf, so I grow into markets I can still win.
• I am a marketplace consultant running a client's keyword shortlist every week to show concentration, pricing, and review demand side by side, so my niche recommendations are backed by numbers instead of hunches.

🚀 How to use Wildberries Niche Analyzer

STEP 1 Add your keywords Paste the niches you are weighing up, in Russian or English, one per line.

STEP 2 Pick depth and region Choose how many products to sample per niche and which warehouse region to price against.

STEP 3 Read the verdict Run it and download one comparison-ready row per niche as JSON, CSV, or Excel.

⚙️ Input

Field	Type	Required	Description
keywords	array of strings	Yes	Product keywords or niches to analyze, in Russian or English (for example робот пылесос or wireless earbuds). Each keyword returns one aggregate market-summary row.
maxProductsPerQuery	integer	No	How many products to sample per keyword before aggregating, from 100 to 5000. Defaults to 300, the top three result pages a shopper actually sees.
priceMinRub	integer	No	Optional price-band floor in rubles. Analyze only products at or above this price, to size up one segment such as premium models. Leave blank for the whole niche. A narrow band may need a larger sample size.
priceMaxRub	integer	No	Optional price-band ceiling in rubles. Analyze only products at or below this price. Combine with the minimum to focus on a single price tier of the market.
sort	enum	No	Which Wildberries result ordering to sample. Popular, the default, reflects what a real shopper sees first.
topN	integer	No	How many of the biggest sellers and brands to list in each niche row, ranked by product count. Defaults to 5.
region	enum	No	Warehouse region used for localized pricing and availability, from Moscow to Kazakhstan. Defaults to Moscow and Central.
debugLogging	boolean	No	Turn on verbose per-niche tracing in the run log. Defaults to false.
proxyConfiguration	object	No	Proxy settings. A proxy is required, and the shared datacenter group works reliably out of the box.

📦 Output

You can download the dataset in various formats such as JSON, HTML, CSV, or Excel. Each row is one niche:

{
  "query": "робот пылесос",
  "queryType": "keyword",
  "region": "MOSCOW",
  "productsAnalyzed": 300,
  "sellerCount": 87,
  "brandCount": 54,
  "sellerConcentrationHHI": 642,
  "topSellerSharePct": 18.3,
  "topSellers": [
    { "id": 1234567, "name": "ООО Техно Импорт", "productCount": 55, "sharePct": 18.3 },
    { "id": 2345678, "name": "Smart Home Store", "productCount": 41, "sharePct": 13.7 }
  ],
  "topBrands": [
    { "name": "Xiaomi", "productCount": 48 },
    { "name": "Dreame", "productCount": 33 }
  ],
  "priceMin": 4990,
  "priceMax": 89990,
  "priceAvg": 27340,
  "priceMedian": 23990,
  "avgRating": 4.6,
  "ratedProductsPct": 92.0,
  "totalFeedbacks": 184230,
  "avgFeedbacks": 614,
  "medianFeedbacks": 212,
  "inStockPct": 88.7,
  "scrapedAt": "2026-07-17T09:30:00Z"
}

📊 Output data fields

Field	Type	Description
query	string	The keyword or niche this row summarizes.
queryType	string	How the niche was requested. Currently keyword for every row.
region	string	The warehouse region the pricing and availability reflect.
productsAnalyzed	number	How many products were sampled to build this row.
sellerCount	number	Number of distinct sellers found across the sample.
brandCount	number	Number of distinct brands found across the sample.
sellerConcentrationHHI	number	Seller concentration on a 0 to 10000 Herfindahl scale. Higher means a few sellers dominate the niche.
topSellerSharePct	number	Share of the sample held by the single largest seller, as a percentage.
topSellers	array	The biggest sellers by product count, each with id, name, productCount, and sharePct.
topBrands	array	The biggest brands by product count in the sample.
priceMin	number	Lowest product price in the sample, in rubles.
priceMax	number	Highest product price in the sample, in rubles.
priceAvg	number	Average product price across the sample, in rubles.
priceMedian	number	Median product price across the sample, in rubles.
avgRating	number	Average star rating across rated products, from 1 to 5.
ratedProductsPct	number	Percentage of sampled products that carry at least one rating.
totalFeedbacks	number	Cumulative lifetime review count across the sample. A demand proxy, not a sales figure.
avgFeedbacks	number	Average review count per product in the sample.
medianFeedbacks	number	Median review count per product in the sample.
inStockPct	number	Percentage of sampled products currently in stock.
scrapedAt	string	When the niche was analyzed, in ISO 8601 format.

💰 Pricing

This Actor uses pay-per-result pricing, billed per niche row saved to your dataset. Each keyword you submit becomes one row. There are no monthly subscriptions and no fixed fees, and empty runs cost nothing.

⭐ Enjoying Wildberries Niche Analyzer?

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✨ Tips

• Put your whole shortlist in one run so the niches line up side by side in a single sheet.
• Raise maxProductsPerQuery for broad keywords where 300 products only cover the first few pages.
• Set priceMinRub and priceMaxRub to analyze only the price segment you plan to sell in, and raise the sample size if the band is narrow.
• Read a low concentration index as an open, fragmented niche, and a high one as a market a few sellers already hold.
• Pick the region closest to your buyers, since pricing and availability shift by warehouse.
• Once you pick a niche, use the sibling Wildberries Scraper to pull the actual product listings inside it.

❓ FAQ

Как проанализировать нишу на Wildberries?

Add the keywords for the niches you are weighing up, then run the Actor. It samples the live Wildberries search results for each keyword and returns one row with the seller count, competition concentration, price band, ratings, and review demand, so you can compare niches and decide which to enter.

Does it estimate sales or revenue?

No. The totalFeedbacks field is the cumulative number of reviews products in the niche have collected over their lifetime. It is a demand proxy that shows how much buyer engagement a niche carries, not a sales count or a revenue figure. Wildberries does not publish sales, so this Actor never guesses at them.

Чем это отличается от парсера товаров Wildberries?

The Wildberries Scraper returns one row per product, which is what you want for catalogs and price monitoring. The Niche Analyzer returns one aggregate row per keyword, which is what you want to size up and compare markets before you source inventory.

Do I need a proxy, and will it get blocked?

A proxy is required, and the shared datacenter group is the default and works reliably out of the box. Wildberries rate-limits direct requests, so the Actor retries through rotating proxies. If datacenter degrades at scale, you can switch the proxy input to residential.

🔗 Other actors

• Wildberries Scraper ↗ - returns one row per product with name, brand, price, discount, supplier, rating, and reviews.
• Wildberries Seller Scraper ↗ - pulls supplier intel and shop stats for any Wildberries seller.
• Wildberries Reviews Scraper ↗ - extracts ratings, full review text, and buyer photos for any product.
• Wildberries Price & Rank Tracker ↗ - monitors Wildberries prices and search rank positions on a schedule.
• Wildberries Resale Scraper ↗ - scrapes resale and secondhand product listings from Wildberries.