# Walmart Reviews Scraper: Ratings, Text & Dates (`leathered_latch/walmart-reviews-scraper`) Actor

Scrape Walmart product reviews into a clean dataset: star rating, title, full text, date, verified purchase, helpful votes and variant. Up to 1,000 reviews per product. No reviewer names. Pay only for reviews delivered.

- **URL**: https://apify.com/leathered_latch/walmart-reviews-scraper.md
- **Developed by:** [Noor Holdings](https://apify.com/leathered_latch) (community)
- **Categories:** E-commerce
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

$2.70 / 1,000 reviews

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

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

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
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.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## 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.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## Walmart Reviews Scraper: star ratings, review text and dates

Give it Walmart product links or item IDs and get the reviews back, one row each: stars, title, text, date, verified-purchase flag, helpful votes and the exact variant reviewed.

Reviewer names and IDs are left out on purpose. You get what people said, not who they are.

You pay only for reviews delivered. A product with no reviews, or a bad link, costs nothing.

### What you get

| Field | Example |
|---|---|
| `productName` | Gevalia House Blend Ground Coffee, 12 oz. Bag |
| `rating` | 2 |
| `title` | Gevalia |
| `text` | This is a ground gevalia coffee not as expected. |
| `date` | 2026-10-03 |
| `verifiedPurchase` | true |
| `helpfulVotes` | 0 |
| `variantItemId` | 19477401 |
| `productAverageRating` / `productTotalReviews` | 4.7 / 8644 |

#### Sample output

```json
{
  "productId": "19477394",
  "productName": "Gevalia House Blend Ground Coffee, 12 oz. Bag",
  "productUrl": "https://www.walmart.com/ip/19477394",
  "productAverageRating": 4.7,
  "productTotalReviews": 8644,
  "reviewId": "442826450",
  "rating": 2,
  "title": "Gevalia",
  "text": "This is a ground gevalia coffee not as expected.",
  "date": "2026-10-03",
  "verifiedPurchase": true,
  "helpfulVotes": 0,
  "unhelpfulVotes": 0,
  "variantItemId": "19477401",
  "sellerName": "Walmart.com",
  "fulfilledBy": "Walmart",
  "syndicatedFrom": null,
  "photoCount": 0,
  "language": "English"
}
```

### Quick start

1. Paste product links (`https://www.walmart.com/ip/...`) or item IDs into **Products**.
2. Set **Max reviews per product**. Walmart shows 10 per page; up to 1,000 works.
3. Pick a **Sort**: most recent, most helpful, highest or lowest rated.
4. Click **Start**.

The default input pulls 50 recent reviews of one coffee and runs as-is.

### Use cases

- Read every 1- and 2-star review of your product (sort: lowest) and fix what keeps coming up.
- Track new reviews on a competitor each week with sort: most recent.
- Compare complaints across sizes or flavors with `variantItemId`.
- Count verified vs unverified reviews before you trust a product's average.

### What happens when something goes wrong

Walmart sometimes shows a "Robot or human?" page when a lot of pages come fast. The scraper slows down, switches connection and tries again on its own. In testing that brought back 300 of 300 reviews across three products.

A wrong item ID or a product with no reviews returns 0 rows and isn't charged. `RUN_SUMMARY` in the run's key-value store lists what happened to each product.

### Pricing

Pay per review delivered, plus Apify's small start fee per run. Set a maximum cost per run and the scraper stops at your limit.

### FAQ

**Why don't I see reviewer names?**
We leave personal identifiers out. If you need them, this isn't the tool.

**Why is `title` empty so often?**
Many Walmart reviewers skip the headline. In our test about half had one.

**What is `syndicatedFrom`?**
Some reviews are copied in from the brand's own website. When that happens this field names the source; empty means it was written on Walmart.

**Something broke?**
Open an issue with the product link. I answer within a day.

### Limitations

- walmart.com (US) only.
- Review text is the reviewer's own words. Quote it, analyze it, but check before republishing it word for word.
- Sorting is Walmart's; we don't re-sort.

### Export or use as an API

Download any run's results from the **Storage** tab as CSV, Excel, JSON or XML.

To call it from your own code, send your input to Apify's API and get the rows back in one request:

```
POST https://api.apify.com/v2/acts/leathered_latch~walmart-reviews-scraper/run-sync-get-dataset-items?token=YOUR_APIFY_TOKEN
```

It also plugs into Make, Zapier and n8n through Apify's integrations, and AI agents can find and run it through Apify's MCP server.

### Your responsibility

How you use the output is your call, and so is the legal side of it. Copyright still covers any text or images you republish. Reviewer names are left out on purpose. Review text is still someone's own words, so quote it fairly. The source site's own terms apply too. If you're unsure about a use, check with a lawyer first.

If you own content that shows up in these results and want it handled differently, open an issue on the Issues tab. We answer within 14 days.

### Data source and credit

Every row comes from Walmart.com (Walmart Inc.). We don't own this data, and we don't take credit for it. The reviews belong to the customers who wrote them.

This tool reads only what Walmart shows to any logged-out visitor. No logins, no private data. Each row keeps a link back to the page it came from (the `productUrl` field), so you can check any result and credit the source when you use it.

Not affiliated with, endorsed by or sponsored by Walmart. All names and trademarks belong to their owners.

### Changelog

- **0.1** First release. Five sort orders, up to 1,000 reviews per product, automatic retry through Walmart's bot check, no reviewer names.

# Actor input Schema

## `products` (type: `array`):

Walmart product links or item IDs, one per line. Example: https://www.walmart.com/ip/5344812220

## `maxReviewsPerProduct` (type: `integer`):

How many reviews to return per product (1-1000). Walmart shows 10 per page. You pay only for reviews delivered.

## `sort` (type: `string`):

Which reviews come first.

## Actor input object example

```json
{
  "products": [
    "https://www.walmart.com/ip/5344812220"
  ],
  "maxReviewsPerProduct": 50,
  "sort": "most_recent"
}
```

# Actor output Schema

## `results` (type: `string`):

No description

# 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 = {
    "products": [
        "https://www.walmart.com/ip/5344812220"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("leathered_latch/walmart-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 = { "products": ["https://www.walmart.com/ip/5344812220"] }

# Run the Actor and wait for it to finish
run = client.actor("leathered_latch/walmart-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 '{
  "products": [
    "https://www.walmart.com/ip/5344812220"
  ]
}' |
apify call leathered_latch/walmart-reviews-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,leathered_latch/walmart-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/5RSMIHOZEKDOBxmMi/builds/RteV3LYA66Ao9bABY/openapi.json