# TikTok Shop Buyer Reviews Scraper (`thenetaji/tiktok-shop-reviews-scraper`) Actor

Export customer reviews from any TikTok Shop product. Every review comes back with its star rating, text, photos, the variant bought, and whether TikTok verified the purchase. Filter to one star rating, to reviews with media, or to confirmed buyers only.

- **URL**: https://apify.com/thenetaji/tiktok-shop-reviews-scraper.md
- **Developed by:** [The Netaji](https://apify.com/thenetaji) (community)
- **Categories:** E-commerce, Social media, Automation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $3.19 / 1,000 results

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## TikTok Shop Reviews Scraper

The Actor collects customer reviews for one or many TikTok Shop products, with star-rating, media, and verified-purchase filters, and the matching review total carried on every row.

```json
{
  "product_ids": [
    "https://shop.tiktok.com/us/pdp/1730927783781307026",
    "1729447567685489298"
  ],
  "region": "US",
  "reviewFilter": "all"
}
```

### Accepted input

`product_ids` is required and takes page links or bare product IDs, mixed freely in the same list. Each product is fetched separately; one that cannot be read is logged as a warning and skipped rather than ending the run, so a bad ID in a ten-product list costs that product only. `region` is required and selects the storefront read — `US`, `GB`, `SG`, `MY`, `PH`, `TH`, or `VN` — which changes the products, prices, and currency returned, not only the display language. `reviewSort` defaults to `recommended` and also accepts `most_recent`, which walks the newest reviews first and suits tracking sentiment over time. `reviewFilter` defaults to `all` and also accepts `5_star`, `4_star`, `3_star`, `2_star`, `1_star`, `with_media`, or `verified_purchase`; only one value applies at a time, so narrowing to five-star reviews with media in a single run is not possible. `maxItems` defaults to `100` and bounds the number of reviews saved across the whole run; a value of `0` disables the bound.

### How the review count is requested

Reviews are fetched from TikTok in one request per product, up to a ceiling of `500` reviews per product; asking for more than that per product is not possible. `maxItems` is a run-wide bound, not a per-product one: it is divided across the products in `product_ids` rather than spent entirely on the first, so a three-product run with `maxItems` set to `300` asks each product for `100`. Setting `maxItems` to `0` requests the full `500`-review ceiling from every product in the list.

### Result fields

```json
{
  "review_id": "7567443161237194551",
  "product_id": "1731756086010286738",
  "review_rating": 5,
  "review_text": "This product feels super hydrating. The shade is great and it goes on smooth. Also, it smells really good and the packaging is neat.",
  "reviewer_name": "C**e",
  "review_time": "1761932674796",
  "total_reviews": "9916"
}
```

This is a trimmed, live-captured result. Numeric fields arrive exactly as the source returns them, so `review_time` and `total_reviews` are numeric strings rather than a date and an integer; `new Date(Number(review_time))` converts the timestamp without a timezone guess. The full row also carries `sku_id` (the variant the review is attached to), `sku_specification` (the size, colour, or similar the reviewer bought), `reviewer_id`, `reviewer_avatar_url`, `review_images` (any photos or video attached, empty when there are none), `review_country`, `is_verified_purchase`, and `is_incentivized_review` (whether the reviewer was rewarded for reviewing, with a free sample, a discount, or similar). `review_text` is empty when the reviewer left a star rating without writing anything. `reviewer_name` arrives partially masked by TikTok, as shown above. `product_id` on each row is taken from the upstream review record when present and falls back to the ID supplied in `product_ids` otherwise.

### Filtering and the review total

`total_reviews` reflects the filter active on that run, not the product's lifetime review count: a run with `reviewFilter` set to `1_star` reports the one-star count on every row, not the count across all ratings. A run with the default `all` filter reports the product's full review total. This makes the field a way to size the remaining pool from a single row, but only against the filter that produced it.

### Products with no reviews

A product with zero reviews, or zero reviews matching the active `reviewFilter`, yields no rows for that product and is not treated as an error; the run continues to the next product in `product_ids`.

### Related Actors

For a product's full page — description, variants, seller profile, and a page of reviews alongside everything else — use the [TikTok Shop Product Scraper](https://apify.com/thenetaji/tiktok-shop-product-scraper). For the creators and affiliates promoting a product instead of the people buying it, use the [TikTok Shop Creator Videos Scraper](https://apify.com/thenetaji/tiktok-shop-creator-videos-scraper). For the seller behind the product, use the [TikTok Shop Seller Info Scraper](https://apify.com/thenetaji/tiktok-shop-seller-info-scraper).

# Actor input Schema

## `product_ids` (type: `array`):

One or more TikTok Shop products to fetch. Paste product page links, or product IDs — both work, and you can mix them.

## `region` (type: `string`):

Which TikTok Shop storefront to read. This changes the products, prices, and currency you get back — not just the display language.

## `maxItems` (type: `integer`):

Maximum number of products to save. Set 0 for no limit.

## `reviewSort` (type: `string`):

Order reviews are returned in. Most recent walks the newest first — the right choice for tracking sentiment over time.

## `reviewFilter` (type: `string`):

Narrow to one star rating, to reviews carrying photos or video, or to confirmed purchases. Only one filter applies at a time.

## Actor input object example

```json
{
  "product_ids": [
    "1730927783781307026"
  ],
  "region": "US",
  "maxItems": 20,
  "reviewSort": "recommended",
  "reviewFilter": "all"
}
```

# Actor output Schema

## `dataset` (type: `string`):

All records scraped by this run

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "product_ids": [
        "https://shop.tiktok.com/us/pdp/1730927783781307026"
    ],
    "maxItems": 20
};

// Run the Actor and wait for it to finish
const run = await client.actor("thenetaji/tiktok-shop-reviews-scraper").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "product_ids": ["https://shop.tiktok.com/us/pdp/1730927783781307026"],
    "maxItems": 20,
}

# Run the Actor and wait for it to finish
run = client.actor("thenetaji/tiktok-shop-reviews-scraper").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "product_ids": [
    "https://shop.tiktok.com/us/pdp/1730927783781307026"
  ],
  "maxItems": 20
}' |
apify call thenetaji/tiktok-shop-reviews-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,thenetaji/tiktok-shop-reviews-scraper"
        }
    }
}

```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/1JOaTpqB1bihFujI6/builds/L0qkz2lO6YyRBS9VO/openapi.json