Tokopedia Scraper — Products, Prices, Reviews & Change Monitor

Tokopedia Scraper reads Indonesia's largest marketplace without the official API and without a browser: products by keyword with price, discount, units sold, seller tier, cash-on-delivery and every offer label on the card, shop reviews and product reviews with buyer photos and seller replies. It also does the thing no other Tokopedia Actor does — Monitor mode returns only what changed since your last run: a price that moved, a discount that started or ended, how many were sold in between, and products that disappeared from the results. Export as JSON, CSV or Excel, run it on a schedule, or call it from the API and AI agents.

What is Tokopedia Scraper?

Tokopedia Reviews Scraper is a no-code tool to scrape Tokopedia reviews for a whole shop at once. Give it one or more shop URLs, pick a sort order (newest, most helpful, highest or lowest rating) and an optional filter (star rating, or only reviews with photos), and set how many reviews you need. Results come back as clean JSON, downloadable as CSV or Excel.

• Any shop, any volume: official stores and regular sellers, 10 reviews or 10,000.
• Full review fields: rating, text, buyer name, date, product name and URL, review photos and videos, seller reply and reply date, helpful votes.
• Filters and sorting built in.
• Fast and cheap: no browser, no proxies needed for small runs.

What data can Tokopedia Scraper extract?

Field	Example
rating	5
reviewText	sangat wangi dan bagus, rekomendasi
reviewerName	Q***b
reviewTime	Hari ini
productName	Makarizo Advisor Hair Recovery Vitamin
productUrl	https://www.tokopedia.com/makarizo-advisor/…
sellerReply	Terima kasih atas ulasannya!
reviewImages	["https://images.tokopedia.net/…"]
reviewVideos	[]
shopName, shopID, totalReviews	Makarizo Advisor, 7494500774502172946, 10000

How much does it cost to scrape Tokopedia?

The Actor uses Apify's pay-per-event pricing: you pay only for the review and shop records saved to your dataset — nothing per run or per page. Error rows are never charged.

Event	Price	Per 1,000
Review	$0.0015	$1.50
Product found by search	$0.0015	$1.50
Shop record (name, total reviews)	$0.002	$2

The Actor uses lightweight HTTP requests, so compute cost is negligible even for large shops. The Apify Free plan ($5 monthly credit) covers roughly 3,000 reviews a month. Bronze, Silver and Gold Store tiers get a discount on top.

Bulk export: what 50,000 reviews actually cost

This Actor is built for bulk jobs — put hundreds of inputs into one run, or call it from the API on a schedule. There is no fee per run, no fee per page and no proxy charge: you pay for the rows you keep, and error rows are free. That is what decides the bill once you pull a whole market rather than a single property.

Job	This Actor	Most-used Actor in this category
50,000 reviews across 100 runs	$75	$173.50

Checked on the Apify Store on 21 September 2026 against the Actor with the most monthly users in this category; its per-run fee is counted in, as ours would be if we charged one. Some Actors here ask less per row — this table compares against the one buyers actually use most.

How to scrape Tokopedia

1. Open any shop on Tokopedia and copy its URL, for example https://www.tokopedia.com/makarizo-advisor.
2. Paste it into Tokopedia shop URLs. Add several shops if you like.
3. Set Max reviews per shop, choose Sort reviews by, and optionally Filter by rating (or With photo/video only).
4. Click Start, then export from the Storage tab as JSON, CSV, or Excel.

Monitor mode — the part no other Tokopedia Actor has

Every Tokopedia scraper in the Store answers what is on sale right now. None of them answers what changed since yesterday — which is the question a seller watching competitors, or a buyer waiting for a sale, actually asks.

Switch What to get to Monitor, give it a name, and put it on a schedule. Each run does the same search, compares it with what it saw last time, and returns only the movement:

changeType	What happened
new	The product entered your watch — first run, or it just appeared in the results
price_down / price_up	The price moved. previousPrice, priceChange and priceChangePercent say by how much
discount_started / discount_ended	A discount badge appeared or disappeared
sold_more	Units sold went up. soldChange is the closest thing Tokopedia gives to live demand
gone	The product dropped out of the results — out of stock, delisted, or pushed off the page you watch

Several can happen at once and arrive comma-separated, for example price_down,sold_more.

A run where nothing moved returns nothing and costs nothing. That is the point: you can watch a keyword every hour through 11.11 and only pay on the days the market actually moves.

Each watch keeps its own memory, so monitorStateKey of iphone-jakarta and competitor-shop never overwrite each other.

⬇️ Input

{
    "startUrls": ["https://www.tokopedia.com/makarizo-advisor"],
    "maxReviewsPerShop": 500,
    "reviewsSort": "recent",
    "ratingFilter": "all"
}

Field	Required	Description
startUrls	yes	Tokopedia shop URLs (tokopedia.com/{shop-name})
maxReviewsPerShop	no	Default 200
reviewsSort	no	recent, helpful, highest, lowest
ratingFilter	no	all, 5…1, or with_media

Searching by keyword

Type what a shopper would type — hair mask, iphone 15, kopi arabica — into 🔍 Search keywords and the Actor returns the matching products: name, price, rating, how many have sold, the shop and its city. Turn on ⭐ Reviews for each product found and every one of those products also brings back its own reviews, with the variant the buyer chose and the date in ISO form.

That is the difference between the two ways in: a shop URL gives you everything one seller has ever been told, a keyword gives you a whole product category across sellers. Both can run in the same job.

{
  "searchTerms": ["hair mask"],
  "maxProductsPerTerm": 20,
  "includeProductReviews": true,
  "maxReviewsPerProduct": 50
}

Scrape only negative Tokopedia reviews

Set ratingFilter to 1 or 2 to pull complaints only — useful for quality monitoring and competitor research.

⬆️ Output

One review per dataset item, plus one shop record (type: "shop") per URL with the shop's total review count.

{
    "type": "review",
    "shopName": "Makarizo Advisor",
    "rating": 5,
    "reviewText": "sangat baik dan wangi sekali rekomendasi",
    "reviewerName": "Q***b",
    "reviewTime": "Hari ini",
    "productName": "Makarizo Advisor Hair Recovery Vitamin",
    "productUrl": "https://www.tokopedia.com/makarizo-advisor/…",
    "sellerReply": "",
    "reviewImages": ["https://images.tokopedia.net/img/…"],
    "totalLikes": 0
}

Use cases for Tokopedia data

Seller and brand monitoring

Watch your own shop's reviews and reply times; schedule daily runs and get alerted on 1–2 star reviews.

Competitor research

Compare what buyers praise and complain about across competing shops in your category.

Indonesian-language sentiment analysis

Feed structured Bahasa Indonesia reviews into sentiment models and dashboards.

Product-quality reports for agencies

Build reputation reports for e-commerce clients without manual copy-paste.

Integrations and Tokopedia API

Run the Actor from code with the Apify API and the JavaScript or Python client, or without code via Google Sheets, Slack, n8n, Make, Zapier, and webhooks. It also works with LangChain, LlamaIndex, and the Apify MCP server for AI agents.

from apify_client import ApifyClient

client = ApifyClient("<YOUR_API_TOKEN>")
run = client.actor("lergassy/tokopedia-reviews-scraper").call(run_input={
    "startUrls": ["https://www.tokopedia.com/makarizo-advisor"],
    "maxReviewsPerShop": 200,
})
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item["rating"], item["reviewText"])

🤖 For AI Agents & LLM Apps

Compact reference for agents calling this Actor through the Apify MCP server or the Apify API (lergassy/tokopedia-reviews-scraper).

Purpose: returns the product reviews of any Tokopedia store — Indonesia's largest marketplace — as one row per review, with the seller's replies attached. Use it to answer "what do buyers complain about in this shop", "which products get the worst ratings" and "does this seller answer complaints".

Minimal input:

{ "startUrls": ["https://www.tokopedia.com/makarizo-advisor"], "maxReviewsPerShop": 100 }

Output: one row per review — type, shopID, shopName, shopUrl, reviewId, rating, reviewText, reviewTime, reviewerName, reviewerId, isAnonymous, totalLikes, sellerReply, sellerReplyTime, productName, productUrl, productId, productImage, reviewImages, reviewVideos. The dataset also carries one shop row per store with totalReviews and reviewsScraped, which is how you tell a store with few reviews from a run that hit its cap.

Behaviors an agent should know:

• Input is store URLs, not product URLs or search queries. The Actor resolves the store id from the URL and walks the store's whole review feed.
• maxReviewsPerShop defaults to 200 and is the only real cost control. A store with 10,000 reviews will happily return all of them if you raise it.
• ratingFilter narrows to a single star rating or to with_media (reviews that carry photos or video); reviewsSort chooses recent, helpful, highest or lowest. Filter through these rather than post-filtering rows, so the cap is spent on rows you want.
• Review text is written by Indonesian shoppers and is mostly in Indonesian, often with slang and abbreviations. Translate before sentiment scoring.
• Buyer names arrive masked (R***a) when the reviewer chose to stay anonymous; isAnonymous marks those rows.
• No login and no API key: the Actor reads the store's own review endpoint.

❓ FAQ

Is it legal to scrape Tokopedia reviews?

The Actor extracts only publicly visible review data; Tokopedia's robots.txt explicitly allows crawling review pages, and no private buyer data is collected. Review the site's terms and consult a lawyer for your specific use case.

Can I use Tokopedia Reviews Scraper with the Apify API?

Yes — see the API tab for ready snippets in JavaScript, Python, and cURL.

Can I use it through an MCP server?

Yes. Connect the Apify MCP server and your AI agent can call this Actor as a tool.

Can I integrate it with other apps?

Yes — Google Sheets, Slack, n8n, Make, Zapier, webhooks, or any HTTP client.

Which shops work?

Any Tokopedia shop URL of the form tokopedia.com/{shop-name} — official stores and regular sellers.

The reviews are in Indonesian. Can I translate them?

The Actor returns original text; add a translation step or an LLM in your workflow.

Do I need proxies?

Small runs work without them. For large volumes keep Apify Proxy enabled (on by default).

Can I scrape product listings and prices too?

Yes. Put keywords in Search terms and the Actor returns product rows with the name, price, rating, sold count, shop and link, and it can follow each product to collect its reviews. Give a shop URL instead if you want the reviews of one seller.

Notes and limits

• Tokopedia rounds the units-sold label: "30+ terjual" is returned as soldCount: 30. The exact number is not published anywhere on the card.
• shopTier is Tokopedia's own seller standing as a number. Higher is a more established seller, but Tokopedia does not publish what each level means, so the value is passed through rather than guessed at.
• Offer labels come back in the storefront's own words (Indonesian), because that is what the buyer on Tokopedia sees. hasCashOnDelivery and isDiscounted are the parsed booleans if you would rather not read Indonesian.
• Monitor mode remembers products, not pages. If you widen maxProductsPerTerm between runs, the products that were never in the old, narrower result set arrive as new.

Your feedback

Missing a field or hitting an error? Open an issue in the Issues tab — requests are welcome and shipped fast. If the Actor saved you time, a review helps other sellers find it.

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