# Best Buy Reviews Scraper (`wibuild.in/best-buy-reviews-scraper`) Actor

Scrape Best Buy reviews, ratings, photos, and seller responses from any Best Buy US product page — clean, analysis-ready data for sentiment analysis, competitor research, and e-commerce analytics.

- **URL**: https://apify.com/wibuild.in/best-buy-reviews-scraper.md
- **Developed by:** [Wibuild](https://apify.com/wibuild.in) (community)
- **Categories:**
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $1.50 / 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?

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

## Best Buy Product Reviews Scraper | Extract Customer Ratings & Feedback (US)

**Scrape Best Buy reviews**, ratings, photos, and seller responses from any **Best Buy US product page** — clean, analysis-ready data for sentiment analysis, competitor research, and e-commerce analytics.

Paste a product URL → choose **Max Mode** (maximize unique coverage) or filters → get structured results you can export as JSON, CSV, or Excel.

***

### 60-second overview

| Goal | What to set |
|---|---|
| **Max coverage** | `maxMode = true` |
| **Quick sample** (e.g. latest 30) | `maxMode = false`, sort `newest`, `maxreviews = 30` |
| **Only 1★ complaints** | `maxMode = false`, `starRatings = ["1"]` |
| **Broad coverage without Max Mode** | Select **all sorts** × **star ratings 1–5** |

***

### Why use this Best Buy review scraper?

- **Max Mode** — maximizes unique coverage; often the full set, including high-volume products.
- **No browser** — reads Best Buy’s review pages over HTTP (same idea as the Home Depot path).
- **Rich fields** — stars, review text, photos, verified purchase, incentivized flags, seller replies, helpful votes, ownership days.
- **Flexible filters** — best match / highest / lowest / most helpful / most relevant / newest / oldest × 1–5 stars.
- **Easy exports** — run on Apify, push to Dataset, download CSV/Excel/JSON.

Ideal for: **product managers**, **brand analysts**, **market research**, **VOC**, and **AI/NLP pipelines**.

***

### Max Mode — maximize unique coverage

Turn **`maxMode` ON** when you want the broadest unique review set for a product.

While Max Mode is ON, **sort and star filters are ignored** — the actor paginates the newest listing until the listed total (or `maxreviews`).

```json
{
  "URL": "https://www.bestbuy.com/product/apple-airpods-max-lightning-space-gray/JJ8ZHPWH5K/sku/12705893",
  "maxMode": true,
  "maxreviews": 20000
}
```

Tip: keep `maxreviews` high enough so the run does not stop early on large SKUs.

***

### Filters (Max Mode OFF)

When **`maxMode = false`**, you control exactly what is collected using **sort × star** combinations.

#### Available sorts

| Input value | Meaning |
|---|---|
| `best_match` | Best Match |
| `highest_rated` | Highest Rated |
| `lowest_rated` | Lowest Rated |
| `most_helpful` | Most Helpful |
| `most_relevant` | Most Relevant |
| `newest` | Newest |
| `oldest` | Oldest |

#### Star ratings

`all` · `5` · `4` · `3` · `2` · `1`

#### Examples

**Latest reviews only:**

```json
{
  "URL": "https://www.bestbuy.com/product/.../sku/12705893",
  "maxMode": false,
  "sorts": ["newest"],
  "starRatings": ["all"],
  "maxreviews": 100
}
```

**Only negative feedback (1–2 stars):**

```json
{
  "URL": "https://www.bestbuy.com/product/.../sku/12705893",
  "maxMode": false,
  "sorts": ["newest"],
  "starRatings": ["1", "2"],
  "maxreviews": 2000
}
```

**Most helpful + highest rated:**

```json
{
  "URL": "https://www.bestbuy.com/product/.../sku/12705893",
  "maxMode": false,
  "sorts": ["most_helpful", "highest_rated"],
  "starRatings": ["all"],
  "maxreviews": 2000
}
```

***

### Input reference

| Field | Required | Description |
|---|---|---|
| `URL` | Yes | Best Buy **US** product URL (must include `/sku/{id}`) |
| `maxMode` | No (default `true`) | `true` = maximize unique coverage; `false` = use sort/star filters |
| `sorts` | No | Multi-select; used only when `maxMode` is false |
| `starRatings` | No | `all` or `1`–`5`; used only when `maxMode` is false |
| `maxreviews` | No (default `5000`) | Cap on unique reviews collected |

***

### Output fields (selected)

| Field | Description |
|---|---|
| `Review_ID` | Best Buy review id |
| `Title` / `ReviewText` | Review title and body |
| `Rating` | 1–5 star rating |
| `Review_Date` | Review date (`YYYY-MM-DD`) |
| `UserNickname` | Reviewer display name |
| `IsVerifiedPurchaser` / `IsIncentivized` | From badges |
| `PhotoUrls` | Customer photo URLs |
| `SellerResponse_*` | Brand / seller reply when present |
| `DaysOfOwnership` | Days owned before review |
| `Total_Reviews` | Listed total for the product |
| `Sort` | Sort used to collect the row |

***

### Tips

- Prefer **Max Mode** for the broadest unique pull.
- Use **filters + a small `maxreviews`** for cheap tests or “latest only” dashboards.
- One URL = one product; run multiple times (or a workflow) for category research.
- Some fields may be empty when the site does not provide them — that is normal.

***

### Keywords

Best Buy reviews scraper · Best Buy product reviews · scrape Best Buy ratings · Best Buy customer feedback · extract Best Buy review text · Best Buy sentiment analysis data · e-commerce review scraping Apify · VOC competitor analysis · Best Buy verified purchase reviews · Best Buy star ratings dataset

***

*Built for teams who need reliable Best Buy US review data — without manual copy-paste.*

# Actor input Schema

## `URL` (type: `string`):

Best Buy US product URL. Must include the numeric SKU (/sku/6494847 or ?skuId=6494847).

## `maxMode` (type: `boolean`):

ON = maximize unique coverage (ignores Sort and Star filters). Often the full set for typical and high-volume products. OFF = use only the filters you select below.

## `sorts` (type: `array`):

One or more sorts. Combined with Star ratings as a cross-product. Empty = newest only.

## `starRatings` (type: `array`):

Empty or \["all"] = all stars. Otherwise pick 1–5. Crossed with each selected sort.

## `maxreviews` (type: `integer`):

Stop after this many unique reviews. Use a small number (e.g. 30) for a quick sample.

## Actor input object example

```json
{
  "URL": "https://www.bestbuy.com/product/apple-airpods-max-lightning-space-gray/JJ8ZHPWH5K/sku/12705893",
  "maxMode": true,
  "sorts": [
    "newest"
  ],
  "starRatings": [
    "all"
  ],
  "maxreviews": 50
}
```

# Actor output Schema

## `reviews` (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 = {
    "URL": "https://www.bestbuy.com/product/apple-airpods-max-lightning-space-gray/JJ8ZHPWH5K/sku/12705893",
    "maxMode": false,
    "sorts": [
        "newest"
    ],
    "starRatings": [
        "all"
    ],
    "maxreviews": 50
};

// Run the Actor and wait for it to finish
const run = await client.actor("wibuild.in/best-buy-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 = {
    "URL": "https://www.bestbuy.com/product/apple-airpods-max-lightning-space-gray/JJ8ZHPWH5K/sku/12705893",
    "maxMode": False,
    "sorts": ["newest"],
    "starRatings": ["all"],
    "maxreviews": 50,
}

# Run the Actor and wait for it to finish
run = client.actor("wibuild.in/best-buy-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 '{
  "URL": "https://www.bestbuy.com/product/apple-airpods-max-lightning-space-gray/JJ8ZHPWH5K/sku/12705893",
  "maxMode": false,
  "sorts": [
    "newest"
  ],
  "starRatings": [
    "all"
  ],
  "maxreviews": 50
}' |
apify call wibuild.in/best-buy-reviews-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,wibuild.in/best-buy-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/G4TVNhG7joxQ0pbXC/builds/fZXGsRaFu0Pd5sRjA/openapi.json