# Influencer Rate Calculator - What You Should Charge (`reapx/engagement-benchmark-by-niche`) Actor

Stop guessing what a post is worth. Know the going engagement rate and the fair price for your niche and your follower size, so you can name a number and defend it.

- **URL**: https://apify.com/reapx/engagement-benchmark-by-niche.md
- **Developed by:** [Tarek Etman](https://apify.com/reapx) (community)
- **Categories:** For creators, Marketing, Social media
- **Stats:** 2 total users, 1 monthly users, 80.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $0.85 / 1,000 engagement benchmark record returneds

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

![reapX - the record of what changed](https://reapx.dev/reapx.gif)

## Engagement Benchmarks By Niche, Size & Country API

Maintained by reapxdev@proton.me. Complete entity records with verified citation links.

> *"I am negotiating blindly against rate cards without knowing what creators in this niche actually average."*

Ad agencies and brand strategy teams struggle to negotiate sponsorship deals when creators quote arbitrary rate cards. Without multi-creator cohort benchmarks for specific vertical niches, buyers overpay for reach or miss market baseline expectations during campaign planning.

This actor calculates engagement rate medians, top-quartile performance thresholds, comment-to-like ratios, posting cadences, and fair price estimates per sponsored post across vertical niches (fitness, beauty, gaming, finance, tech, fashion), follower size bands, and geographic markets.

### ⬇️ Input

The actor accepts arrays of vertical niches, follower size bands, target countries, and an optional proxy configuration.

```json
{
  "niches": [
    "fitness",
    "beauty",
    "gaming",
    "finance"
  ],
  "sizeTiers": [
    "100k-1M"
  ],
  "countries": [
    "US"
  ]
}
```

#### Input Parameters

| Field | Type | Default | Description |
|---|---|---|---|
| `niches` | Array | `["fitness", "beauty", "gaming", "finance"]` | List of industry vertical niches to benchmark. |
| `sizeTiers` | Array | `["100k-1M"]` | List of follower size bands to benchmark. |
| `countries` | Array | `["US"]` | List of ISO country codes to benchmark. |
| `proxyConfiguration` | Object | `null` | Optional proxy settings to rotate exit IPs per request. |

### ⬆️ Output

Every processed niche cohort outputs a structured record to the default dataset.

#### Output Fields

| Field | Type | Description |
|---|---|---|
| `benchmarkId` | String | Stable per-row identifier. Format: niche-sizeTier-country. |
| `niche` | String | Industry vertical category. |
| `sizeTier` | String | Follower size band cohort. |
| `country` | String | Geographic country filter. |
| `medianEngagementRate` | Number | Median engagement rate observed across cohort. |
| `topQuartileEngagementRate` | Number | Top-quartile (75th percentile) engagement rate threshold. |
| `medianCommentToLikeRatio` | Number | Median comment-to-like ratio across cohort. |
| `medianPostingCadence` | Number | Median posts published per week across cohort. |
| `fairPriceEstimatePerPost` | String | Computed fair market rate per sponsored post based on reach and engagement benchmark. |
| `sampleSize` | Integer | Number of creator profiles observed in benchmark calculation. |
| `daysTracked` | Integer | Number of days this benchmark cohort has been observed in our index. |
| `computedStatus` | Object | Status object with observation evidence and calculation notes. |
| `scrapedAt` | String | ISO timestamp of benchmark calculation. |

#### Worked Output Example

```json
{
  "benchmarkId": "fitness-100k-1M-US",
  "niche": "fitness",
  "sizeTier": "100k-1M",
  "country": "US",
  "medianEngagementRate": 0.022,
  "topQuartileEngagementRate": 0.0363,
  "medianCommentToLikeRatio": 0.024,
  "medianPostingCadence": 4.2,
  "fairPriceEstimatePerPost": "$450 USD per sponsored post (range: $360 - $563)",
  "sampleSize": 1420,
  "daysTracked": 1,
  "computedStatus": {
    "sampleProfilesCount": 1420,
    "tierMultiplier": 1.0,
    "nicheBaselineEr": 0.022,
    "reason": "calculated from multi-creator index ledger across vertical cohort"
  },
  "scrapedAt": "2026-08-05T17:15:00.000Z"
}
```

### How it works

1. **Cohort Data Indexing**: Aggregates performance data across multi-creator index ledgers by vertical niche and follower tier.
2. **Median & Percentile Calculation**: Computes median engagement rates, top-quartile thresholds, and posting cadences.
3. **Fair Pricing Projection**: Generates fair price estimates per sponsored post to empower ad buyers during rate card negotiations.

### ❓ FAQ

##### Why is a niche benchmark necessary for fair price estimation?

A finance creator with 50,000 followers commands significantly higher sponsorship rates than a meme account with 50,000 followers. Niche benchmarks adjust fair price estimates for category-specific audience value.

##### Can this actor run on Apify without payload bodies?

Yes. If an API request contains no input body (such as automated health checks), the actor falls back to prefilled reference niches to guarantee successful output.

##### How often are these benchmarks updated?

Benchmarks recalculate continuously across accumulated multi-creator runs in our index.

### 💬 Your feedback

Need custom vertical category taxonomies, regional currency conversions, or media plan pricing models? Contact reapxdev@proton.me.

***

Unofficial - not affiliated with social networks. Collects only data visible without logging in. reapx. Contact reapxdev@proton.me.

# Actor input Schema

## `niches` (type: `array`):

The kind of content you make - fitness, beauty, gaming, fashion, finance. Add a few if you sit between them, and you get a rate for each.

## `sizeTiers` (type: `array`):

The follower bands you care about. Rates move sharply between them, so pick the one you are in and the one you are growing into.

## `countries` (type: `array`):

Where the audience actually is. The same follower count is worth very different money in different markets, so this changes the number.

## `proxyConfiguration` (type: `object`):

How the run reaches the platform. The default is already the route that works for this source, so leave it alone unless you have a reason to change it.

## Actor input object example

```json
{
  "niches": [
    "fitness",
    "beauty",
    "gaming",
    "finance"
  ],
  "sizeTiers": [
    "10k-100k",
    "100k-1M",
    "1M-10M"
  ],
  "countries": [
    "US",
    "UK"
  ],
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": [
      "RESIDENTIAL"
    ]
  }
}
```

# Actor output Schema

## `items` (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 = {
    "niches": [
        "fitness",
        "beauty",
        "gaming",
        "finance"
    ],
    "sizeTiers": [
        "10k-100k",
        "100k-1M",
        "1M-10M"
    ],
    "countries": [
        "US",
        "UK"
    ],
    "proxyConfiguration": {
        "useApifyProxy": true,
        "apifyProxyGroups": [
            "RESIDENTIAL"
        ]
    }
};

// Run the Actor and wait for it to finish
const run = await client.actor("reapx/engagement-benchmark-by-niche").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 = {
    "niches": [
        "fitness",
        "beauty",
        "gaming",
        "finance",
    ],
    "sizeTiers": [
        "10k-100k",
        "100k-1M",
        "1M-10M",
    ],
    "countries": [
        "US",
        "UK",
    ],
    "proxyConfiguration": {
        "useApifyProxy": True,
        "apifyProxyGroups": ["RESIDENTIAL"],
    },
}

# Run the Actor and wait for it to finish
run = client.actor("reapx/engagement-benchmark-by-niche").call(run_input=run_input)

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

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

```

## CLI example

```bash
echo '{
  "niches": [
    "fitness",
    "beauty",
    "gaming",
    "finance"
  ],
  "sizeTiers": [
    "10k-100k",
    "100k-1M",
    "1M-10M"
  ],
  "countries": [
    "US",
    "UK"
  ],
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": [
      "RESIDENTIAL"
    ]
  }
}' |
apify call reapx/engagement-benchmark-by-niche --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=reapx/engagement-benchmark-by-niche",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/O13aSeOnY1G8S2HP8/builds/wuBBaPsdDF8f3tSGy/openapi.json