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Wildberries Seller Analytics: Аналитика ВБ

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Analyze Wildberries sellers with legal entity and catalog intelligence: INN, address, brands, prices, reviews, ratings, and stock. Search by seller ID, store URL, or keyword. Аналитика продавцов Вайлдберриз for sourcing and competitor research. $0.00699 per seller dossier.

Pricing

from $2.25 / 1,000 result rows

Rating

5.0

(1)

Developer

GetAScraper

Actor stats

Bookmarked

Total users

Monthly active users

22 days ago

Last modified

Changelog

All notable changes to the Wildberries Seller Scraper are documented here.

1.3.0 🔬 Seller portfolio intelligence

✨ Added

Added transparent sample-based seller signals: top-brand share, price quartiles and median, review concentration, inventory concentration, discounted-product rate, and out-of-stock rate.
Added an 🔬 Seller Intelligence dataset view for comparing assortment concentration and price positioning across sellers.
Added monitoring deltas for median price, top-brand share, concentration, discounts, and stock-outs, plus the previous top brand when it changes.

🛡️ Data integrity

All new fields are calculated only from structurally validated scanned products and must be interpreted with scannedProducts and catalogCoveragePct.
Migrated monitoring state to version 3 without fabricating a one-time UPDATED event for existing v1/v2 monitoring projects.

1.2.2 🔎 Search coverage for seller analytics

🧾 Store listing

Added English and Russian buyer terms for Wildberries seller analytics and аналитика продавцов Вайлдберриз.
Clarified seller-dossier pricing and the legal-entity, catalog, price, review, and stock fields returned for each seller.

1.2.1 ⚡ Faster first seller dossier

🧭 First-run experience

Changed the Store prefill to one verified seller ID with a ten-product catalog sample.
Removed keyword discovery from the prefilled run so first-time users reach a seller dossier faster and at lower cost.
Kept the existing API, task, and scheduler defaults unchanged.

1.2.0 🔄 Auditable seller monitoring

✨ Added

Added backward-compatible snapshot, snapshot_with_changes, and changes_only output modes.
Added isolated monitoring state, optional silent baselines, and seller deltas for catalog size, average price, reviews, inventory, in-stock rate, and brand additions/removals.
Added NEW, UPDATED, and UNCHANGED classifications with stable first-seen and last-seen timestamps.

🛡️ Data integrity

Limited change detection to metrics with explicit deltas, preventing transient legal-profile omissions or scan metadata changes from creating unexplained updates.
Added safe migration from the earlier monitoring-state format.
Monitoring state advances only after a validated dossier is handled; seller expiry is intentionally never inferred.

1.1.0 🛡️ Seller dossier reliability

✨ Added

Added explicit catalog completeness, pages-scanned, stop-reason, and coverage metadata.

🛡️ Reliability

Added strict JSON response-shape validation and retries for every catalog page.
Prevented malformed, truncated, or failed pagination from producing a paid partial seller dossier.
Added run-wide seller deduplication and synchronous output-slot reservations so concurrent handlers respect maxItems.
Kept the legacy snapshot fields and default behavior unchanged, and intentionally avoided unsupported seller-expiry inference.

1.0.0 🎉 Initial release

✨ Features

🏪 Full seller dossiers: one row per Wildberries seller with profile + catalog intelligence.
🏛️ Legal entity data: seller name, legal name, INN (tax ID), KPP, legal address, trademark.
📊 Catalog aggregates: product count, distinct brands, price range, average rating, total reviews, inventory units.
🔎 Three input modes: seller IDs, seller URLs, and search keywords (auto-discovers the sellers behind matching products).
🛒 Optional per-product breakdown via includeProducts.
⚡ Powered by private JSON APIs (supplier profile CDN + seller catalog), no browser rendering required.

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