# Influencer Audit: Fake Engagement Check, Instagram + TikTok (`kodabloomllc/influencer-audit`) Actor

Audit Instagram and TikTok creators before you pay them: engagement rate against 2026 benchmarks for their follower size, views per follower, activity, undisclosed promotions and spam comments, with the evidence for every flag.

- **URL**: https://apify.com/kodabloomllc/influencer-audit.md
- **Developed by:** [KodaBloom LLC](https://apify.com/kodabloomllc) (community)
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $10.00 / 1,000 profile auditeds

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

## Influencer Audit: Fake Engagement and Ad Disclosure Check for Instagram and TikTok

Check Instagram and TikTok creators before you pay them. Enter usernames and get one audit row per creator, with the numbers behind every flag. Built for brands, agencies and creator managers vetting influencers.

### What you get per creator

- **Engagement rate** (average likes plus comments on recent posts, divided by followers), placed against the 2026 benchmark for the same platform and follower size: bottom 25%, below median, above median, top 25% or top 10%
- **Views per follower**: median views on recent videos as a share of followers
- **Activity**: date of the last post, days since, and posts per month
- **Following vs followers**: flagged when a creator follows more accounts than follow them back
- **Possible undisclosed promotions**: posts with a discount code, or another brand's @handle next to a shopping cue, that carry no #ad, #sponsored or paid-partnership label. Each one is linked so you can look.
- **Disclosed sponsored posts**: posts with a paid-partnership label or #ad
- **Comment check (optional)**: samples comments from the 3 newest posts and counts spam, self-promotion and copy-paste comments, with examples
- **Audience risk** (low, medium, high), a risk score and a plain-language **summary**

#### Where the benchmark comes from

Engagement is compared with the iQfluence 2026 engagement benchmarks (data from September 2026, 30.1 million Instagram and 107.1 million TikTok creators with at least 1,000 followers who posted in the last 30 days). It uses the same formula, so the numbers line up. Creators under 1,000 followers have no benchmark.

#### Risk score

| Signal | Points |
|---|---|
| Engagement in the bottom 25% for the follower band | 40 |
| Follows more accounts than follow back (1,000+ followers) | 20 |
| 10% or more of sampled comments are spam or self-promotion (20+ comments sampled) | 20 |
| 3 or more copy-paste comments | 10 |

Low is under 20, medium is 20 to 49, high is 50 and up. Undisclosed promotions and inactivity are reported in the summary but are not part of the audience score.

### Example

From a test run on well-known accounts:

- **A beauty brand with 56M Instagram followers**: engagement 0.08%, bottom 25% for 5M+ accounts (p25 is 0.25%). Medium risk. Very large brand accounts often score low here because many followers are years old, not because they are fake.
- **A tech reviewer with 5.3M Instagram followers**: engagement 3.95%, top 25%, views at 22% of followers. Low risk.
- **A cooking creator with 22M TikTok followers**: engagement in the top 10%, but no new post in over 1,000 days. The account is inactive.

### How to use it

1. Enter Instagram usernames, TikTok usernames, or both. Handles and profile URLs work too.
2. Optional: set **Comments to sample per post** to 10 or more to add the comment check.
3. Run. The actor runs Apify's Instagram and TikTok scrapers in your account, then audits the results.

### Output

```json
{
  "platform": "instagram",
  "username": "example_creator",
  "followers": 5287636,
  "audience_risk": "low",
  "risk_score": 0,
  "summary": "no warning signs in these posts",
  "engagement_rate_pct": 3.95,
  "benchmark_band": "instagram 5M+",
  "engagement_vs_peers": "top 25%",
  "benchmark": "p25 0.25%, median 0.7%, p75 1.89%, p90 4.39% (iQfluence 2026 engagement benchmarks)",
  "posts_analyzed": 12,
  "views_per_follower_pct": 22.2,
  "comments_per_1k_likes": 9.2,
  "last_post_date": "2026-10-02",
  "posts_per_month": 2.9,
  "disclosed_sponsored_posts": 0,
  "possible_undisclosed_promotions": 0,
  "comments_sampled": 15,
  "spam_comments": 0,
  "copy_paste_comments": 0
}
```

### Send audits to Google Sheets, Airtable or n8n, Make and Zapier

You can audit creators as they come in and keep every result in one place. No code needed.

**n8n, Make or Zapier.** Use the Apify app (Zapier, Make) or the Apify node (n8n). Common setups:

- A creator applies through a form (Typeform, Google Forms, Airtable). The workflow runs this actor with `{"instagramUsernames": ["<their handle>"]}` and writes the audit next to their application.
- Your creator shortlist lives in a Google Sheet or Airtable. Re-run the audit monthly on a schedule and add a new row per creator to watch engagement and activity change.
- A Slack or email message when a creator comes back with audience_risk "high" or any possible undisclosed promotions.

Start from "Actor run finished" for this actor and fetch the dataset items to get the rows. Every field is plain text or a number, with no nested objects (example links and comments are joined into one text field), so each one maps straight to a column.

**AI agents.** This actor also works as a tool for AI assistants through the [Apify MCP server](https://mcp.apify.com), so an agent can audit a creator when you ask it to.

### Good to know

- A flag is a reason to look closer, not proof of fake followers or a broken rule.
- Posts younger than 2 days and pinned posts are left out of the engagement rate.
- Creators promoting their own book or product with "link in bio" are not flagged as undisclosed. Photo and video credits (for example "🎥: @name") are ignored.
- Short fan comments like "love it 😍" are normal and are not counted as spam.
- Follower growth history is not available from a single scrape, so the audit does not check for sudden follower jumps.
- Private accounts and missing profiles are listed as "not checked" and are free.

### Pricing

You pay per creator audited. The Instagram and TikTok scrapers it runs also charge your account at their usual rates (about $0.003 per Instagram profile and about $0.04 per TikTok creator at 12 videos). Run it with no input to audit a built-in demo sample for free.

Made by KodaBloom LLC. Questions: info@kodabloom.com

# Actor input Schema

## `instagramUsernames` (type: `array`):

Usernames, @handles or profile URLs. Public accounts only.

## `tiktokUsernames` (type: `array`):

Usernames, @handles or profile URLs.

## `videosPerProfile` (type: `integer`):

How many recent TikTok videos to read per creator. Instagram always returns the latest 12 posts.

## `commentsPerPost` (type: `integer`):

Reads this many comments from each creator's 3 newest posts to find spam and copy-paste comments. Comment scraping adds cost: about $0.08 per Instagram creator and $0.04 per TikTok creator at 10 comments per post.

## Actor input object example

```json
{
  "instagramUsernames": [
    "mkbhd"
  ],
  "tiktokUsernames": [
    "mkbhd"
  ],
  "videosPerProfile": 12,
  "commentsPerPost": 0
}
```

# Actor output Schema

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

One audit per creator, highest risk first.

# 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 = {
    "instagramUsernames": [
        "mkbhd"
    ],
    "tiktokUsernames": [
        "mkbhd"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("kodabloomllc/influencer-audit").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 = {
    "instagramUsernames": ["mkbhd"],
    "tiktokUsernames": ["mkbhd"],
}

# Run the Actor and wait for it to finish
run = client.actor("kodabloomllc/influencer-audit").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 '{
  "instagramUsernames": [
    "mkbhd"
  ],
  "tiktokUsernames": [
    "mkbhd"
  ]
}' |
apify call kodabloomllc/influencer-audit --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,kodabloomllc/influencer-audit"
        }
    }
}
```

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/5NT0jFSXnEolVuxWo/builds/HcpCIbHhKajkbiIhK/openapi.json