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, and which Wildberries categories the keyword actually maps to. Built for sellers deciding where to compete.
Wildberries data suite   •  Product search, niche analytics, resale, reviews, and seller data
Niche Analyzer ➤ You are here	Price Tracker Price and search-rank monitoring	Resale Scraper Resale and secondhand listings	Reviews Scraper Ratings, text and buyer photos

See how crowded a Wildberries niche is before you commit inventory budget 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, who the biggest players are, and which real Wildberries categories the keyword actually lands in.

🧭 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.

🏆 Top sellers and brands See who already dominates the niche by product count and share.

🗂️ Category fit See which real Wildberries categories your keyword's matches actually fall into.

Turn a Wildberries (Вайлдберриз) keyword into a market read. Instead of a pile of products to sort, the Niche Analyzer samples live search results for each keyword and returns one aggregate row that scores the niche on competition and market composition. 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 who runs it:

• 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 product count.
• Category fit - the real Wildberries categories your keyword's matching products fall into, and how much of the sample lands in each one.

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.

A note on what changed. Wildberries recently cut off public access to price, rating, review, and stock data platform-wide. This is a Wildberries-side change affecting every tool built on that data, not something specific to this Actor. Competition metrics (seller count, brand count, concentration, top sellers and brands) are still computed from live, genuine data. Price band, ratings, review counts, and stock levels are no longer part of the output, and there's no fixed date for when they might return. See the FAQ below for details.

💡 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 a niche's category fit and seller concentration before I place a bulk order, so I never stock a category that's already saturated.
• I am an established seller expanding my range scanning adjacent keywords for the ones where the top few sellers don't 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 and category composition 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're weighing up, in Russian or English, one per line.

STEP 2 Pick a sample size Choose how many matching products to analyze per niche, up to 300.

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 matching products to analyze per keyword, from 20 to 300. Defaults to 300. Wildberries' discovery source caps out around 300 candidates per keyword either way, so this mainly trades off run time and depth.
priceMinRub	integer	No	Currently has no effect. Kept only so existing saved inputs don't break; see the FAQ.
priceMaxRub	integer	No	Currently has no effect, for the same reason as above.
topN	integer	No	How many of the biggest sellers, brands, and categories to list in each niche row, ranked by product count. Defaults to 5.
region	enum	No	Recorded on each row as a label. Doesn't currently change which products are analyzed; see the FAQ.
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 residential is the verified-working default.

📦 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",
  "productsDiscovered": 300,
  "productsAnalyzed": 300,
  "sellerCount": 214,
  "brandCount": 168,
  "sellerConcentrationHHI": 118,
  "topSellerSharePct": 3.7,
  "topSellers": [
    { "id": 800008, "productCount": 11, "sharePct": 3.7 },
    { "id": 107529, "productCount": 8, "sharePct": 2.7 }
  ],
  "topBrands": [
    { "name": "Xiaomi", "productCount": 22, "sharePct": 7.3 },
    { "name": "Neatsvor", "productCount": 17, "sharePct": 5.7 }
  ],
  "topCategories": [
    { "name": "Роботы-пылесосы", "productCount": 205, "sharePct": 68.3 },
    { "name": "Пылесосы", "productCount": 61, "sharePct": 20.3 }
  ],
  "scrapedAt": "2026-09-23T09:12:00Z"
}

📊 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 label selected for the run. See the Input note above.
productsDiscovered	number	How many candidate products Wildberries' discovery source returned for this keyword. Capped around 300 by that source itself, so this is not a total market-size or competitor-count figure.
productsAnalyzed	number	How many of the discovered candidates actually resolved to real product data and were used to build this row.
sellerCount	number	Number of distinct sellers found across the analyzed sample.
brandCount	number	Number of distinct brands found across the analyzed 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, productCount, and sharePct. Sellers are identified by their numeric Wildberries ID only; a human-readable seller name isn't available from this data source.
topBrands	array	The biggest brands by product count in the sample, each with name, productCount, and sharePct.
topCategories	array	The real Wildberries categories the sample's products fall into, each with name, productCount, and sharePct. Useful to confirm a keyword targets the niche you expect.
scrapedAt	string	When the niche was analyzed, in ISO 8601 format.

A note on removed fields. Price (minimum, average, median, maximum), average rating, rated-product percentage, review counts, and in-stock percentage are not part of this output anymore. Wildberries cut off public access to the data source those figures came from, platform-wide, and there is currently no reliable replacement. Rather than show stale, estimated, or placeholder numbers, this Actor omits them entirely. If that data becomes accessible again, these fields will come back for real.

💰 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?

⭐ ⭐ ⭐ ⭐ ⭐ Turning a keyword shortlist into a clear competition read, without a monthly analytics subscription? A 5-star rating takes 10 seconds and helps other Wildberries sellers and resellers researching niches find it. Your feedback also tells us what to build next.

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✨ Tips

• Put your whole shortlist in one run so the niches line up side by side in a single sheet.
• Use topCategories to sanity-check that a keyword actually targets the niche you think it does before you act on the rest of the row.
• Read a low concentration index as an open, fragmented niche, and a high one as a market a few sellers already hold.
• Raise maxProductsPerQuery toward 300 for the most complete seller and brand picture; lower it for a faster, cheaper pass across a long keyword shortlist.
• 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're weighing up, then run the Actor. It samples live Wildberries search results for each keyword and returns one row with the seller count, competition concentration, top sellers and brands, and category fit, so you can compare niches and decide which to enter.

Does this Actor show price, ratings, or review counts?

Not right now. Wildberries cut off public access to the data source these figures came from, platform-wide, sometime before September 2026. That's a change on Wildberries' side, not a gap specific to this Actor. The seller/brand competition metrics and the new category-fit breakdown are unaffected and still come from live data. The priceMinRub/priceMaxRub inputs stay in the form for backward compatibility but currently have no effect. There's no fixed date for when pricing and review data will return.

Does it estimate sales or demand?

No. This Actor never guessed at sales or demand, and it doesn't now either. It reports what's directly observable: how many sellers and brands compete for a keyword, how concentrated that competition is, and which categories the keyword actually surfaces.

Чем это отличается от парсера товаров Wildberries?

The Wildberries Scraper returns one row per product, which is what you want for catalogs and content research. 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 residential is the verified-working default. Wildberries rate-limits and blocks direct and datacenter requests, so the Actor routes through rotating residential proxies with automatic retries.

🔗 Other actors

• Wildberries Scraper ↗ - returns one row per product with name, brand, description, category, and image.
• 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.