Sales and market share data for
Monthly GMV, units and market share by brand, merchant and SKU, cleaned and categorised.
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sku_namebrandcategory_3monthpricediscountavg_price_soldsold_monthlygmv_monthlygmv_monthly_usdratingmerchant_namemerchant_badgeQuestions Lazada data answers
How big is this category, and is it growing?
Monthly GMV and units for the category, month by month.
Who is gaining or losing share?
Brand GMV per month, so share can be computed for any period.
Which products drive the category?
SKU-level rows ranked by GMV, with price and, where the listing shows one, rating.
How are prices and discounts moving?
Lowest monthly price and average realised price per SKU. Lazada listings in the catalog rarely carry a discount figure, so use price movement rather than discount depth.
Which shops lead, including official stores?
Merchant name on every row, plus the badge that marks LazMall stores (Lazada Mall) apart from regular sellers.
Coverage by country
From the current catalog. Depth differs by country and category, so check your scope with a free estimate.
| Country | Months | Categories | SKU-month rows |
|---|---|---|---|
| Indonesia | 2025-01 → 2026-07 | 108 | 34M |
| Malaysia | 2025-01 → 2026-07 | 12 | 2.2M |
| Philippines | 2025-01 → 2026-07 | 14 | 1.8M |
| Singapore | 2025-01 → 2026-07 | 15 | 2.0M |
| Thailand | 2025-01 → 2026-06 | 12 | 2.9M |
| Vietnam | 2025-01 → 2026-07 | 12 | 2.1M |
How you get it, and what it costs
Query it
Filter by country, category, brand or month over the REST API or the Python client.
Export whole categories
Order a bulk Parquet or CSV export, one file per category and month. It loads straight into BigQuery, Snowflake or DuckDB.
Estimate first, free
Every export can be estimated for free. You pay per row actually delivered.
Current per-row price: rate card.
What the main fields mean
| Field | Type | Meaning |
|---|---|---|
sku_name | STRING | The listing's title exactly as scraped, with no cleanup — good for a human eyeballing the row, but wording and casing vary listing to listing, so use sku_type_complete instead when matching or grouping products. |
brand | STRING | Brand name, resolved by matching the listing's product/merchant identity against Magpie's brand reference data rather than read directly off the title. Shows the placeholder when no brand has been confirmed yet. |
category_3 | STRING | Leaf category (e.g. Facial Serum) — the export's atom grain. |
month | DATE | Calendar month representing the aggregation period. Identifies which month's daily/raw scrape records were rolled up to produce this row (e.g. sold_monthly = SUM of daily sold within the month). |
price | FLOAT64 | The lowest price recorded for the listing during the month, local currency — the cheapest price point observed, not a price taken specifically at month's end. Empty when the listing never displayed a price during the month (e.g. a pre-launch or 'coming soon' page); this shows up mostly on small, low-volume SKUs. |
discount | FLOAT64 | Listed discount as a fraction (0.70 = 70% off). |
avg_price_sold | FLOAT64 | Average realized selling price across the month's sales, local currency. |
sold_monthly | INT64 | Units sold in this month. |
gmv_monthly | FLOAT64 | GMV for this month, local currency (≈ units × realized price). Empty when the listing carried no price to value the units against (see price) — the same pre-launch / 'coming soon' small SKUs. An empty GMV means unknown, not zero: exclude those rows rather than summing them as 0. |
gmv_monthly_usd | FLOAT64 | GMV for this month in USD — the cross-market analysis metric. Empty whenever gmv_monthly is, for the same reason. |
rating | FLOAT64 | Listing's rating (0–5) at month end. |
merchant_name | STRING | Shop display name. |
merchant_badge | STRING | Platform badge, e.g. 'Shopee Mall', 'Star Seller' — official signal. |
Lazada data questions
Can I separate LazMall stores from other Lazada sellers?
Yes. merchant_badge is Lazada Mall for LazMall stores and Lazada Regular Seller for everyone else.
Is coverage the same in every Lazada country?
No. Indonesia covers the most categories; the other countries cover fewer. The coverage table on this page shows the current months and category count for each country.
How often does the data refresh?
Monthly. The coverage table on this page shows the latest month available for each country.
What formats do I get?
Bulk exports arrive as signed download links, one file per category and month: gzipped CSV or Parquet. BigQuery, Snowflake, Databricks and DuckDB read Parquet directly.
Can I see the cost before I buy?
Yes. Estimates are free and show rows and credits for your exact scope. You are billed per row actually delivered.
Can I redistribute the data or resell insights built on it?
Redistribution and derived-product rights are set in your agreement rather than assumed by default. Tell us what you intend to build and we will scope it.
How do I get access?
Sign up and you get trial credits: catalog browsing and cost estimates work immediately. Paid exports are reviewed first so we can scope the right market, category and history depth with you.
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