Tokopedia Product Scraper - Deal Hunter

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🚀 Production-ready Tokopedia scraping with clean input/output contracts and practical data you can use right away.

Why this Actor

If your goal is to sell smarter on Tokopedia, this Actor gives you the exact signals that matter: price, sold trends, rating strength, sponsored exposure, and top sellers. You can run it in minutes, export clean data, and feed it into spreadsheets, BI dashboards, alerts, or internal tools.

What you get

• ⚡ Fast product discovery from one or many keywords in a single run
• 📉 Better pricing decisions with current price, original price, and real discount detection
• 🛒 Demand signals from sold labels normalized into usable numeric insights
• 🏪 Seller and location visibility to identify strong competitors and market hotspots
• 🧠 Keyword summary output for quick market snapshots (avg price, sponsored share, top stores)
• 🔍 Optional deep crawl mode for richer detail fields when you need premium analysis

Run configuration (Build, Memory, Timeout)

You can run this Actor from Console, API, schedule, or another Actor.

• Build: use latest for newest improvements, or pin a specific build number for stable production behavior
• Memory: standard runs work well on default memory; increase memory for heavy keywords or deep crawl mode
• Timeout: use higher timeout for bigger keyword sets or deep crawl runs

For reliable automation, pin build + set explicit timeout and memory in your task/schedule.

Input Parameters

Output Example

{
"searchKeyword":"sepatu lari pria",
"productName":"Sepatu Lari Pria Ultraboost Daily Trainer - Hitam Putih",
"price":429000,
"originalPrice":599000,
"discountPct":28,
"rating":4.9,
"soldCount":"1,2rb+",
"storeName":"SportHub Official",
"location":"Kota Bandung",
"productUrl":"https://www.tokopedia.com/sporthubofficial/sepatu-lari-pria-ultraboost-daily-trainer-hitam-putih",
"storeUrl":"https://www.tokopedia.com/sporthubofficial",
"storeFollowers":187540,
"isMallOfficial":true,
"resultPage":2,
"rank":15,
"organicRank":11,
"isSponsored":false,
"reviewCount":324,
"variantCount":6,
"stockStatus":"in_stock",
"descriptionSnippet":"Sepatu lari harian dengan upper breathable mesh, midsole empuk, dan outsole anti-slip untuk jogging, gym, dan aktivitas harian.",
"scrapedAt":"2026-04-07T10:23:41.512Z"
}

Keyword Summary Example

[
{
"recordType":"keyword_summary",
"keyword":"sepatu lari pria",
"productCount":120,
"avgPrice":382450,
"minPrice":89000,
"maxPrice":1299000,
"avgRating":4.82,
"discountedShare":41.67,
"avgDiscountPct":23.4,
"avgSoldCount":1463,
"sponsoredShare":18.33,
"topStores":[
"SportHub Official",
"RunSpace Indonesia",
"SepatuAktif Store",
"Urban Sneakers ID",
"GearLari Official"
],
"topLocations":[
"Kota Bandung",
"Jakarta Barat",
"Kota Surabaya",
"Kab. Tangerang",
"Kota Semarang"
],
"generatedAt":"2026-04-07T10:29:04.771Z"
}
]

Output Links (Output Schema)

• results -> {{links.apiDefaultDatasetUrl}}/items
• keywordSummary -> {{links.apiDefaultKeyValueStoreUrl}}/records/KEYWORD_SUMMARY
• runDetail -> {{links.apiRunUrl}}

Storage & run behavior

• Dataset: product records (plus optional keyword summary rows)
• Key-value store: input record and KEYWORD_SUMMARY JSON
• Request queue: managed internally by crawler for search and deep crawl requests
• Run origin is visible in run metadata (WEB, API, CLI, SCHEDULER, etc.) for traceability
• You can resurrect failed or timed-out runs in Console if needed

Best use cases

• Product sourcing and dropshipping validation
• Competitor price tracking
• Promo and discount benchmarking
• Assortment gap analysis
• Data feed for alert apps and automation workflows

Performance snapshot

• Standard mode: ~60-120 products/minute
• Deep crawl mode: ~20-45 products/minute
• Recommended concurrency: 3-5 (standard), 2-3 (deep crawl)
• Daily automated quality check: actor is expected to finish with non-empty dataset within 5 minutes

Pro tips for high ROI

• Use specific buyer-intent keywords instead of broad terms
• Start with 50-150 products per run for balanced speed and signal quality
• Use deep crawl only for shortlisted products to optimize cost
• Schedule runs daily or hourly for trend monitoring and rapid reaction