# Xiaohongshu (RED) Channel Benchmark — where to compete (`entrogix_works/xiaohongshu-channel-benchmark`) Actor

Compare Xiaohongshu explore channels side by side. One row per channel: median likes, how concentrated attention is, how video-first it is, ranked. Unofficial; not affiliated with Xiaohongshu.

- **URL**: https://apify.com/entrogix\_works/xiaohongshu-channel-benchmark.md
- **Developed by:** [Entrogix Works](https://apify.com/entrogix_works) (community)
- **Categories:** Social media
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

$50.00 / 1,000 channel benchmarkeds

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

## Xiaohongshu (RED) Channel Scraper — compare categories

Put several Xiaohongshu explore channels side by side and get **one row per channel**, ranked by how many likes a typical note actually earns.

Categories on Xiaohongshu are not variations of one game. A measurement across three channels:

| Channel | median likes | topShare | videoShare |
|---|---|---|---|
| travel | 170 | 0.554 | 39% |
| food | 569 | 0.684 | 42% |
| fitness | 264 | 0.812 | 73% |

Fitness is video-first and winner-take-most. Travel is neither. Posting the same way into both is a mistake, and you cannot see that from one channel's feed.

### What you get per channel

| Field | Example |
|---|---|
| `reachRank` | `1` |
| `channel`, `notes`, `notesWithLikes` | `food`, `24`, `24` |
| **`medianLikes`**, `maxLikes` | `569`, `8925` |
| **`topShare`** | `0.684` |
| **`videoShare`** | `0.417` |
| **`tallShare`** | `0.83` |
| `uniqueAuthors` | `23` |

**`reachRank`** is ordered by `medianLikes`, not total likes. Totals simply reward whichever channel surfaced more notes, which is not the question — you want to know what a *typical* note earns.

**`topShare`** is the share of likes held by the top 10% of notes. High means a few viral notes own the category and a new post is likely to be invisible.

**`videoShare`** and **`tallShare`** describe the *format* that is working. Xiaohongshu is a vertical scroll, so taller covers take more of the screen; `tallShare` is the proportion of notes with an aspect ratio of 1.3 or more.

**`uniqueAuthors`** shows whether the sample comes from many creators or a handful. Few authors means a small group is holding the surface.

### Summary (key-value store, `BENCHMARK_SUMMARY`)

`channels`, `channelsWithNotes`, `medianOfMedianLikes`, `strongest`, and `concentrated` — channels where the top 10% holds 70% or more of all likes.

### Input

```json
{
  "channels": ["travel", "food", "fitness"]
}
```

Eleven channels are available: fashion, food, cosmetics, movie, career, love, household, gaming, travel, fitness, video.

**Two or more channels are required.** One channel is not a comparison, and the run is rejected rather than returning a single row that answers nothing. If you want the note list for one channel, use **Xiaohongshu (RED) Explore Scraper** instead.

### Scope and limits — please read

**The explore feed is a recommendation feed, not an archive.** It returns roughly 24–35 notes per load, the set changes between runs, and this Actor does not scroll. Every channel is therefore measured on a sample of that size — which is exactly what makes the comparison fair, since all channels are sampled the same way.

These are **current-form figures**, not category averages over time. They are not a complete census of a category and should not be read as one.

Channels that return no notes are still returned as a row with `notes: 0` and `reachRank: null`, so a fetch problem is distinguishable from a genuinely empty result.

Like counts are normalized from the site's own abbreviations (`4.1万` → `41000`). Where a count cannot be read it is returned as `null`, never `0`, so it cannot silently drag a median down.

Keyword search is not supported: Xiaohongshu's search page loads results after mount rather than serving them with the page. This Actor does not log in.

**Display names only.** The output is aggregate per channel; where an author is counted, only the public nickname is used, never the account's internal id or avatar.

### Pricing

Charged **per channel**, not per note. One channel is one browser fetch, and the price reflects that this target needs a full browser rather than a plain HTTP request.

### Disclaimer

**This is an unofficial tool and is not affiliated with, endorsed by, or sponsored by Xiaohongshu (RED) or its operators.** "Xiaohongshu" and "RED" are trademarks of their respective owners and are used here only to describe what this Actor reads. You are responsible for ensuring your use of the collected data complies with applicable law and with the platform's terms.

# Actor input Schema

## `channels` (type: `array`):

Two or more explore channels. One channel is not a comparison and is rejected.

## `samplePerChannel` (type: `integer`):

The feed returns roughly 24-35 notes per load and this Actor does not scroll, so higher values will not enlarge the sample.

## `minIntervalMs` (type: `integer`):

Pacing between channel fetches.

## `useProxy` (type: `boolean`):

On by default. This target was vetted at 6/6 through a residential proxy.

## `proxyType` (type: `string`):

Residential is the vetted setting for this target. Datacenter is cheaper on bandwidth but has not been measured here yet.

## Actor input object example

```json
{
  "channels": [
    "travel",
    "food",
    "fitness"
  ],
  "samplePerChannel": 40,
  "minIntervalMs": 3000,
  "useProxy": true,
  "proxyType": "RESIDENTIAL"
}
```

# Actor output Schema

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

Every row this run produced, as JSON.

## `summary` (type: `string`):

Totals and medians for this run, so you can judge the rows without reading them all.

# 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 = {};

// Run the Actor and wait for it to finish
const run = await client.actor("entrogix_works/xiaohongshu-channel-benchmark").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 = {}

# Run the Actor and wait for it to finish
run = client.actor("entrogix_works/xiaohongshu-channel-benchmark").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 '{}' |
apify call entrogix_works/xiaohongshu-channel-benchmark --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,entrogix_works/xiaohongshu-channel-benchmark"
        }
    }
}

```

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/eIYo2lhe72dbixRRQ/builds/bQEesHDnSMxuCgVaS/openapi.json