Tokopedia Reviews Scraper

Extract Tokopedia product reviews quickly and turn them into structured, analysis-ready datasets. Collect reviewer feedback, ratings, variants, media counts, and timestamps in one run. Great for product research, seller monitoring, and customer sentiment analysis.

Features

• Review Collection — Gather reviews from Tokopedia product pages with consistent structured output.
• Simple Inputs — Run with a product URL or direct product ID.
• Pagination Controls — Control volume using results_wanted and max_pages.
• Sorting Options — Choose newest, most helpful, highest rating, or lowest rating.
• Clean Dataset Output — Null and empty values are removed for cleaner exports.

Use Cases

Product Quality Research

Analyze what buyers consistently praise or complain about before deciding inventory or marketing angles. Review data helps identify recurring quality signals fast.

Competitor Monitoring

Track review trends on competitor products over time. Spot shifts in satisfaction, common issues, and review momentum.

Customer Sentiment Analysis

Build datasets for sentiment scoring and theme extraction. Use ratings, review text, and variants to map buyer experience.

Marketplace Reporting

Create periodic reports for teams that need clear review KPIs. Export data to BI dashboards, spreadsheets, or internal tools.

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Input Parameters

Parameter	Type	Required	Default	Description
product_url	String	No	Jasmine sample URL	Tokopedia product URL (recommended input).
product_id	String	No	—	Direct product ID. If filled, it takes priority over product_url.
results_wanted	Integer	No	50	Maximum number of reviews to save.
max_pages	Integer	No	10	Maximum number of pages to fetch.
sort_by	String	No	informative_score desc	Review sort order.
proxyConfiguration	Object	No	{ "useApifyProxy": false }	Optional proxy settings.

Input priority:

1. product_id
2. product_url
3. Fallback to INPUT.json only when user input is empty

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Output Data

Each dataset item contains flattened review fields:

Field	Type	Description
product_id	String	Product identifier.
product_url	String	Product page URL.
product_name	String	Product name when available.
shop_name	String	Shop name when available.
review_id	String	Review identifier.
page	Integer	Review page number.
position	Integer	Review position in collected sequence.
rating	Number	Review rating.
variant_name	String	Purchased variant label.
review_text	String	Review message content.
buyer_name	String	Reviewer display name.
likes_count	Integer	Number of likes on review.
images_count	Integer	Number of attached images.
videos_count	Integer	Number of attached videos.
review_time_relative	String	Relative review time label.
review_time_iso	String	Review timestamp in ISO format when available.
sort_by	String	Sort option used in run.
source_type	String	Input source used (product_id, product_url, default_url).
fetched_at	String	Data collection timestamp.

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Usage Examples

Product URL Run

{
  "product_url": "https://www.tokopedia.com/toko-hijab-jasmine/pashmina-kaos-bahan-cotton-rayon-bahan-adem-ringan-dan-lembut-pashmina-kaos-jasmine-1729666273262209327",
  "results_wanted": 30,
  "max_pages": 5,
  "sort_by": "create_time desc"
}

Product ID Run

{
  "product_id": "100018999468",
  "results_wanted": 20,
  "max_pages": 2,
  "sort_by": "informative_score desc"
}

Rating-Based Sorting

{
  "product_url": "https://www.tokopedia.com/toko-hijab-jasmine/pashmina-kaos-bahan-cotton-rayon-bahan-adem-ringan-dan-lembut-pashmina-kaos-jasmine-1729666273262209327",
  "results_wanted": 50,
  "max_pages": 10,
  "sort_by": "rating desc"
}

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Sample Output

{
  "product_id": "100018999468",
  "product_url": "https://www.tokopedia.com/toko-hijab-jasmine/pashmina-kaos-bahan-cotton-rayon-bahan-adem-ringan-dan-lembut-pashmina-kaos-jasmine-1729666273262209327",
  "product_name": "Jasmine Pashmina Kaos Bahan Cotton Rayon Adem Ringan Lembut Ukuran 175x60 cm - Black",
  "shop_name": "Toko hijab jasmine",
  "review_id": "1469897442",
  "page": 1,
  "position": 1,
  "rating": 5,
  "variant_name": "Brownie",
  "review_text": "Bagus banget sesuai ekspektasi...",
  "buyer_name": "R***u",
  "likes_count": 1,
  "images_count": 4,
  "videos_count": 0,
  "review_time_relative": "12 bulan lalu",
  "review_time_iso": "2025-05-20T17:39:41.000Z",
  "sort_by": "informative_score desc",
  "source_type": "product_url",
  "fetched_at": "2026-05-16T08:23:33.387Z"
}

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Tips for Best Results

Start With Focused Limits

• Begin with results_wanted between 20 and 50 for validation.
• Increase limits only after confirming output quality.

Use Stable Product Targets

• Use product URLs that already have visible customer reviews.
• For automation pipelines, use product_id for consistent targeting.

Use Proxies for Scale

• Enable proxies for higher run stability in larger or repeated jobs.
• Combine scheduled runs with sensible pagination limits.

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Integrations

Connect your review dataset with:

• Google Sheets — Share review summaries with teams.
• Airtable — Build searchable product feedback databases.
• Looker Studio / BI tools — Visualize trends and sentiment metrics.
• Webhooks — Trigger downstream automations after each run.

Export Formats

• JSON — For APIs and developer workflows.
• CSV — For spreadsheets and quick analysis.
• Excel — For stakeholder reporting.

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Frequently Asked Questions

Why do some runs return fewer reviews than requested?

The actor stops when no more pages or reviews are available for that product and sort combination.

Can I run with only product ID?

Yes. product_id is supported and takes priority when both ID and URL are provided.

Are empty fields included in output?

No. Null and empty values are removed before saving dataset items.

Does sorting change the review list?

Yes. Different sort_by options can produce different review order and selections.

Can I schedule recurring runs?

Yes. You can schedule daily or hourly runs to track changes over time.

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Support

For issues or feature requests, contact support through the Apify Console.

Resources

• Apify Documentation
• Apify API Reference

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Legal Notice

Use this actor responsibly and ensure compliance with Tokopedia terms and applicable laws. You are responsible for lawful and ethical data usage.