# Instagram Lead Qualifier - Profile Fit Scoring (`seemuapps/instagram-lead-qualifier`) Actor

Score Instagram profiles as outreach and partnership leads. Get niche, account type, brand safety, a fit score against your brand brief, and a ready to send opening line for each profile.

- **URL**: https://apify.com/seemuapps/instagram-lead-qualifier.md
- **Developed by:** [Andrew](https://apify.com/seemuapps) (community)
- **Categories:** AI, Social media, Lead generation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $20.00 / 1,000 results

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/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

## Instagram Lead Qualifier

Turn a list of Instagram usernames into scored, ready to action leads. Each profile is scraped and scored for fit against your brand, with niche, account type, brand safety, and a ready to send opening line.

### What you get

For every profile:

- Profile basics: full name, bio, followers, following, posts, verified and business flags, category, website, public email and phone
- **Niche**: the profile's main topic
- **Account type**: business, creator, personal, or brand
- **Brand safety**: safe, review, or risky, with a short reason
- **Fit score**: 0 to 100 against your brand brief
- **Fit reason**: one sentence explaining the score
- **Outreach opener**: a friendly first line for a DM or email

### Use cases

- Influencer and creator partnership shortlists
- Outbound lead scoring before you spend time on manual review
- Brand safety screening of profiles before a campaign
- Prioritizing a scraped list of profiles by fit

### How to use

1. Add the **Usernames** to qualify (with or without @)
2. Optionally write a **Brand brief** describing your product or ideal partner. Fit scores are calculated against it. Leave it empty to score general lead quality
3. Optionally set the **Model**
4. Run the actor. Each profile becomes one row in the **Dataset** tab, ready to sort by fit score

### Output example

```json
{
  "username": "natgeo",
  "followerCount": 269213109,
  "category": "",
  "niche": "photography and travel",
  "accountType": "business",
  "brandSafety": "safe",
  "brandSafetyReason": "Highly reputable brand known for quality content.",
  "fitScore": 95,
  "fitReason": "Aligns perfectly with premium photography and travel.",
  "outreachOpener": "Hi! We're big fans of your stunning visuals and would love to explore a collaboration."
}
```

### Notes

- Provide a clear brand brief for the most useful fit scores.
- One profile that fails to resolve never stops the rest of the run.
- A small fast model keeps cost per profile low while still producing strong qualifications.

# Actor input Schema

## `usernames` (type: `array`):

Instagram usernames to qualify, with or without @. One profile is scored per username.

## `brandBrief` (type: `string`):

Describe your brand, product, or ideal partner. Each profile's fit score is calculated against this. Leave empty to score general lead quality.

## `model` (type: `string`):

Model used for qualification. A fast, low cost model is recommended.

## Actor input object example

```json
{
  "usernames": [
    "garyvee",
    "natgeo"
  ],
  "model": "google/gemini-2.5-flash"
}
```

# Actor output Schema

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

One record per profile. Fields: username, userId, fullName, biography, followerCount, followingCount, mediaCount, isVerified, isBusiness, category, externalUrl, email, phone, profileUrl, niche, accountType, brandSafety, brandSafetyReason, fitScore, fitReason, outreachOpener.

# 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 = {
    "usernames": [
        "garyvee",
        "natgeo"
    ],
    "brandBrief": ""
};

// Run the Actor and wait for it to finish
const run = await client.actor("seemuapps/instagram-lead-qualifier").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 = {
    "usernames": [
        "garyvee",
        "natgeo",
    ],
    "brandBrief": "",
}

# Run the Actor and wait for it to finish
run = client.actor("seemuapps/instagram-lead-qualifier").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 '{
  "usernames": [
    "garyvee",
    "natgeo"
  ],
  "brandBrief": ""
}' |
apify call seemuapps/instagram-lead-qualifier --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=seemuapps/instagram-lead-qualifier",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/Zv7oEDCNt0BgdEqg8/builds/0BS7S0P5hnvS07e9Q/openapi.json