# Brand Mention Monitor (`patrikbraborec/brand-mention-monitor`) Actor
Brand monitoring and social listening tool. Track your brand, competitors, or keywords on Reddit, X (Twitter), Hacker News, Bluesky, Instagram, LinkedIn, GitHub, and 4 more. Get only new mentions in one feed, with Slack or email alerts.
- **URL**: https://apify.com/patrikbraborec/brand-mention-monitor.md
- **Developed by:** [Patrik Braborec](https://apify.com/patrikbraborec) (community)
- **Categories:** Social media, Marketing, News
- **Features:** Limited permissions
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet
## Pricing
from $3.00 / 1,000 new mentions
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/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
### What is Brand Mention Monitor?
Brand Mention Monitor is a **brand monitoring and social listening tool** that searches **Reddit, X (Twitter), Hacker News, Bluesky, Google News, and GitHub** for your brand, product, or keyword, and returns **one feed of new mentions** in the same format for every platform. Put it on a schedule and every run returns only the mentions you haven't seen yet, deduplicated across runs and across platforms. Instagram, LinkedIn, Facebook, Threads, and TikTok are available as optional sources.
To try it, enter a keyword such as your brand name and click **Start**. You get a table that answers *where, who, what, when,* and *link* for every mention. With pay-per-event pricing and no subscription, a daily monitor for a typical brand fits in the Apify free plan's monthly credit.
### Why use this brand monitoring tool?
- π‘ **One run instead of six.** Tracking a brand usually means a separate scraper or alert per platform. Brand Mention Monitor covers them all in one run with one output format.
- π **Only new mentions.** History is saved automatically between runs. You don't name a store or configure anything.
- π― **Less noise.** Keywords are matched as exact phrases, you can exclude words, and an optional AI filter drops mentions that use your brand name for something else.
- π **Alerts where you work.** Connect Slack, email, Google Sheets, Zapier, Make, or n8n. The run's status message says how many new mentions it found and where.
- π‘οΈ **Failures don't stop the run.** If one platform is down, the others still deliver, and the run summary tells you which source failed and why.
- π **Built on the Apify platform.** Scheduling, monitoring, an API, webhooks, and an MCP server for AI agents come included.
### Use cases
- **Brand monitoring:** see who talks about your product, and answer questions and complaints while they're fresh.
- **Competitor monitoring:** run one task per competitor to follow their launches, outages, and what customers say about them.
- **Reddit and Hacker News monitoring:** catch threads that ask for a tool like yours, or that discuss your company, on the day they're posted.
- **X (Twitter) monitoring:** track your brand name, product, domain, or handle on X without the X API.
- **PR and news monitoring:** collect press coverage from Google News next to the social conversation.
- **Developer relations:** follow GitHub issues and pull requests that mention your SDK or API.
Typical users are marketers, founders, PR and comms teams, devrel, and agencies.
### What data does Brand Mention Monitor return?
Each row is one mention, with the same fields for every platform:
| Field | Description |
| ------------------------------------------------------------------ | ----------------------------------------------------------------------------------------------------------- |
| `platform` | Where the mention was found: `reddit`, `hackernews`, `bluesky`, `googlenews`, `github`, `x`, `instagram`, β¦ |
| `authorName` | Who posted it. For news, the publication |
| `title` | Title of the post, article, or issue |
| `text` | Plain text of the mention (up to 1,000 characters) |
| `publishedAt` | When it was published (UTC) |
| `url` | Link to the mention |
| `matchedKeyword` | Which of your keywords matched |
| `likes`, `replies`, `shares`, `views` | Engagement at the time of the run, where the platform reports it |
| `relevance`, `relevanceReason` | AI filter verdict, when the filter is on |
| `type`, `authorUrl`, `id`, `canonicalUrl`, `source`, `firstSeenAt` | Mention type, author link, dedup keys, and where the row came from |
The dataset has three views: **Mentions**, **Engagement**, and **All fields**. You can download it as JSON, CSV, Excel, or HTML. Each run also saves a `SUMMARY` record with totals and the status of every source (`ok`, `capped`, `failed`, or `skipped`, with the reason).
### How to monitor brand mentions
1. Enter your brand, product, or keyword in **What to monitor**. Add spelling variants, your domain, or your handle on separate lines, for example `Apify` and `apify.com`.
2. Choose the platforms in **Where to look**, or keep the defaults.
3. Click **Start**. The first run returns mentions from the last 7 days.
4. Click **Save as a new task**, then **Schedule** the task. Daily is a good default, hourly at most. Every later run returns only new mentions.
5. Set up an alert (see [Alerts](#alerts-get-notified-about-new-mentions)) so new mentions come to you.
### How much does brand monitoring cost?
Brand Mention Monitor uses pay-per-event pricing. You pay for new mentions, not for duplicates:
| Event | Price |
| -------------------------------------------------------------- | ------ |
| New mention (one row in your dataset), from any platform | $0.006 |
| Monitor check, once per run when at least one source worked | $0.01 |
| AI relevance check, per mention, only when the AI filter is on | $0.002 |
Apify Store discounts apply to new mentions: $0.005 each at the Silver discount tier and $0.004 at Gold and above. The free plan and the Bronze tier pay $0.006.
The AI relevance filter runs its model through the [OpenRouter Actor](https://apify.com/apify/openrouter), which bills the model's token usage to your Apify account as its own run, like the partner platforms below. That comes to well under $0.001 per checked mention on a paid plan; the OpenRouter Actor charges free-plan users ten times its paid rate.
Only new mentions are ever written to the dataset. Duplicates, mentions already reported in earlier runs, mentions removed by your exclude words, and failed sources are free. The run summary is stored separately and isn't charged.
Example: a daily schedule that finds about 15 new mentions a day costs about **$3 per month** in Brand Mention Monitor fees, plus roughly **$0.50 to $1 per month** in partner fees with the default platforms (see below). That fits in the $5 of monthly credit on the Apify free plan.
If a run reaches your **Max cost per run**, it stops adding mentions, and the ones it didn't add arrive in the next run.
#### Partner platforms are billed separately
Hacker News is searched directly through its official API. Every other platform is fetched by running a specialized Apify Store Actor on your account, which handles that platform's blocking and logins. Those Actors bill you directly: a small start fee per run plus a fee per result, and the charges appear on your bill as their own runs. New mentions from these platforms then cost the same $0.006 as any other new mention. Some partners limit accounts on the Apify free plan; the Instagram partner, for example, accepts only one run about every 30 minutes from a free-plan account. A refused run shows up as a failed source in the status message, and the next run searches that window again. Brand Mention Monitor caps what partners can charge at $1.00 per run in total, split between the selected partners, and asks for at most 100 results on the first run and 50 on later runs.
Expected partner cost per run, at Bronze-tier prices as of November 2026 (set by each partner and subject to change):
| Platform | Partner Actor | Price | Typical later run (β€50 results) |
| ----------- | -------------------------------------------------------------------------------------------------------- | -------------------------------------------- | ------------------------------- |
| Reddit | [Reddit Search Scraper](https://apify.com/clearpath/reddit-search-scraper) | $0.001 per run + $0.99 per 1k results | up to ~$0.05 |
| Bluesky | [Bluesky Posts Scraper](https://apify.com/lexis-solutions/bluesky-posts-scraper) | $0.004 per run + $0.92 per 1k posts | up to ~$0.05 |
| Google News | [Google News Scraper](https://apify.com/automation-lab/google-news-scraper) | $0.005 per run + $2 per 1k articles | up to ~$0.105 |
| GitHub | [GitHub Issues & Pull Requests Scraper](https://apify.com/fetch_cat/github-issues-pull-requests-scraper) | $0.005 per run + $0.03 per 1k items | up to ~$0.007 |
| X | [X (Twitter) Posts Search](https://apify.com/scraper_one/x-posts-search) | $0.0025 per run + $0.25 per 1k posts | up to ~$0.015 |
| Instagram | [Instagram Keyword Posts Scraper](https://apify.com/seemuapps/instagram-keyword-posts-scraper) | $1.50 per 1k posts + $0.0045 per search page | up to ~$0.15 |
| LinkedIn | [Linkedin Post Search Scraper](https://apify.com/harvestapi/linkedin-post-search) | $2 per 1k posts | up to ~$0.10 |
| Facebook | [Facebook Posts Search](https://apify.com/scraper_one/facebook-posts-search) | $3 per 1k posts | up to ~$0.15 |
| Threads | [Threads Scraper](https://apify.com/futurizerush/meta-threads-scraper) | $0.005 per run + $2.50 per 1k posts | up to ~$0.13 |
| TikTok | [TikTok Search Scraper](https://apify.com/xmolodtsov/tiktok-search-scraper) | $0.25 per 1k videos | up to ~$0.013 |
With the default platforms, start fees come to about $0.02 per run, so a daily schedule costs about $0.50 per month in start fees and an hourly one about $13. **Daily is the recommended schedule.** To keep result fees low, Brand Mention Monitor asks every partner for the narrowest time window it supports, which for most partners is just the time since the last run. Partner Actors don't know what you've already seen, though, so a post that reaches Brand Mention Monitor twice is paid to the partner twice and then dropped as a duplicate.
#### Is there a free option?
Yes. Keep just Hacker News in **Where to look** and no partner fees apply. You pay only the Brand Mention Monitor fees above, which the Apify free plan's monthly credit covers for most keywords.
### Input
See the **Input** tab for every option. The ones worth knowing:
- **What to monitor** (required): one line per keyword or alias. Each line is matched as an exact, case-insensitive phrase, so `Apify` matches "Apify's" and "apify.com" but not "Apifyer".
- **Where to look**: the platforms to search.
- **First run looks back**: how many days the first run covers (1 to 30, default 7).
- **Exclude mentions containing**: drop mentions with these words, for example `fruit`, `pie`, and `recipe` when tracking Apple.
- **AI relevance filter: what is it?**: describe what you track ("Notion, the note-taking app") and an AI model removes unrelated mentions. The model runs through the [OpenRouter Actor](https://apify.com/apify/openrouter) on your account.
Changing your keywords starts a new history automatically. Two tasks with the same keyword keep separate histories, so each can have its own alerts.
Example input for monitoring an ambiguous brand name and its domain on the default platforms:
```json
{
"keywords": ["Notion", "notion.so"],
"lookbackDays": 7,
"excludeKeywords": ["notion of"],
"aboutBrand": "Notion, the note-taking and productivity app"
}
```
### Output example
```json
[
{
"platform": "hackernews",
"authorName": "exampleuser",
"title": "Show HN: A price tracker built on Apify",
"text": "I built this over the weekendβ¦",
"publishedAt": "2026-10-29T14:03:00.000Z",
"url": "https://news.ycombinator.com/item?id=12345678",
"type": "post",
"matchedKeyword": "Apify",
"likes": 42,
"replies": 7,
"source": "native"
},
{
"platform": "x",
"authorName": "Example Dev",
"title": null,
"text": "Just shipped a new scraper on Apify, scheduling works out of the box.",
"publishedAt": "2026-10-29T13:20:00.000Z",
"url": "https://x.com/exampledev/status/1983000000000000001",
"type": "post",
"matchedKeyword": "Apify",
"likes": 14,
"replies": 2,
"shares": 4,
"source": "partner:scraper_one/x-posts-search"
}
]
```
### Alerts: get notified about new mentions
On the task's **Integrations** tab you can add:
- **Slack** or **email** on *Run succeeded*. The run's status message reads like "6 new mentions (Hacker News 3, X 2, Google News 1)". These integrations fire on every run, including runs with no new mentions.
- **Webhook** on *Run succeeded* with `{{resource.defaultDatasetId}}` in the payload, to fetch the new mentions from the API.
- **Google Sheets**, **Zapier**, **Make**, or **n8n** to append each run's mentions to a sheet or another tool.
### API, MCP, and AI agents
Run Brand Mention Monitor from your own code with the [Apify API](https://docs.apify.com/api/v2) or the Apify clients for JavaScript and Python. The **API** tab has ready-to-copy examples. AI agents such as Claude or ChatGPT can run it through the [Apify MCP server](https://mcp.apify.com), for example to summarize this week's mentions of your brand.
### Tips
- Add your domain and handle as extra keywords (`apify.com`, `@apify`) to catch links and tags.
- For an ambiguous brand name, start with exclude words, and add the AI filter if noise remains.
- Use one task per brand or competitor. Each keeps its own history and alerts.
- Check `SUMMARY` after the first run: a source marked `capped` hit its result limit, and `skipped` or `failed` comes with the reason. For Reddit, Hacker News, Bluesky, Google News, and GitHub, the older mentions a capped run didn't reach arrive in the next runs (`backfillPending` in `SUMMARY`). For X, Instagram, LinkedIn, Facebook, Threads, and TikTok, a capped run skips the oldest mentions in its window, so a more frequent schedule helps for very popular keywords.
### FAQ
#### How is this different from Google Alerts?
Google Alerts emails you about web pages and news articles. Brand Mention Monitor also covers social and community platforms (Reddit, X, Hacker News, Bluesky, GitHub, and Instagram), returns structured data with engagement counts, and sends results to Slack, Google Sheets, an API, or any tool you connect. Use it as a Google Alerts alternative when the conversation about your brand happens outside news sites.
#### Can I monitor Reddit and Hacker News for keywords?
Yes. Keep `reddit` and `hackernews` in **Where to look**, or select only those two. Reddit search covers posts and comments, Hacker News covers stories and comments, and each run returns only threads that are new since the last run.
#### Which platforms are searched for each keyword?
All of them, except Facebook, which searches only the first keyword because its search doesn't support OR. Bluesky searches posts, Reddit searches posts and comments, and GitHub searches issues and pull requests. Instagram searches posts and Reels; its search also matches audio and on-screen text, so the keyword isn't always in the caption.
#### Why did my second run return nothing?
Each run returns only mentions that are new since the previous run. If nothing new was posted, the dataset is empty and the status message says so. To search the full lookback window again, duplicate the task and run the copy. A new task starts with an empty history, so you're charged again for mentions you already got.
#### What happens if a platform fails?
The other platforms still run. The failed platform is listed in the status message and in `SUMMARY`, and the next run searches it again from where it last succeeded.
#### Is it legal to monitor brand mentions?
Brand Mention Monitor collects only public posts and the public names or handles of their authors. Your results could contain personal data. Personal data is protected by the GDPR in the European Union and by other regulations around the world. You should not collect personal data unless you have a legitimate reason to do so. If you're unsure whether your reason is legitimate, consult your lawyers.
#### Where can I report a problem?
Open an issue on the **Issues** tab.
### Other Actors you might like
Need more depth on a single platform? The partner Actors Brand Mention Monitor uses work on their own too: [Reddit Search Scraper](https://apify.com/clearpath/reddit-search-scraper), [X (Twitter) Posts Search](https://apify.com/scraper_one/x-posts-search), [Google News Scraper](https://apify.com/automation-lab/google-news-scraper), and [Bluesky Posts Scraper](https://apify.com/lexis-solutions/bluesky-posts-scraper).
# Actor input Schema
## `keywords` (type: `array`):
Brand, product, person or topic. Add spelling variants or aliases on separate lines (e.g. Apify, apify.com). Each line is matched as an exact phrase, case-insensitive.
## `platforms` (type: `array`):
Platforms to search. Hacker News is free. Every other platform is fetched by a partner Actor from Apify Store that bills you separately on your Apify account: a small start fee per run plus a fee per result, capped at $1 per run in total. With the defaults that's about $0.02 per run in start fees plus up to ~$0.25 per run in results. See the README for prices. To use only the free source, keep just Hacker News.
## `lookbackDays` (type: `integer`):
How far back the first run searches. Later runs only return mentions that are new since the previous run.
## `excludeKeywords` (type: `array`):
Drops any mention whose text contains one of these words. For "Apple", for example: fruit, pie, recipe.
## `aboutBrand` (type: `string`):
Describe what you're tracking in a few words, e.g. "Notion, the note-taking app". When this is filled in, an AI model reads each new mention and drops the unrelated ones ($0.002 per checked mention). The model runs through the OpenRouter Actor, which bills its token usage to your Apify account separately (well under $0.001 per mention). Leave it empty to skip the filter.
## Actor input object example
```json
{
"keywords": [
"Apify"
],
"platforms": [
"reddit",
"hackernews",
"bluesky",
"googlenews",
"github",
"x"
],
"lookbackDays": 7,
"excludeKeywords": []
}
```
# Actor output Schema
## `mentions` (type: `string`):
Mentions that are new since the previous run, normalized across platforms
## `summary` (type: `string`):
Totals and per-source status (ok, capped, failed, skipped)
# API
You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.
## JavaScript example
```javascript
import { ApifyClient } from 'apify-client';
// Initialize the ApifyClient with your Apify API token
// Replace the '' with your token
const client = new ApifyClient({
token: '',
});
// Prepare Actor input
const input = {
"keywords": [
"Apify"
],
"platforms": [
"reddit",
"hackernews",
"bluesky",
"googlenews",
"github",
"x"
]
};
// Run the Actor and wait for it to finish
const run = await client.actor("patrikbraborec/brand-mention-monitor").call(input);
// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`πΎ Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
console.dir(item);
});
// π Want to learn more π? Go to β 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 '' with your token.
client = ApifyClient("")
# Prepare the Actor input
run_input = {
"keywords": ["Apify"],
"platforms": [
"reddit",
"hackernews",
"bluesky",
"googlenews",
"github",
"x",
],
}
# Run the Actor and wait for it to finish
run = client.actor("patrikbraborec/brand-mention-monitor").call(run_input=run_input)
# Fetch and print Actor results from the run's dataset (if there are any)
print(f"πΎ 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)
# π Want to learn more π? Go to β https://docs.apify.com/api/client/python/docs/quick-start
```
## CLI example
```bash
echo '{
"keywords": [
"Apify"
],
"platforms": [
"reddit",
"hackernews",
"bluesky",
"googlenews",
"github",
"x"
]
}' |
apify call patrikbraborec/brand-mention-monitor --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"type": "http",
"url": "https://mcp.apify.com/?tools=fetch-actor-details,patrikbraborec/brand-mention-monitor"
}
}
}
```
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 ` 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/aTv1kSZYiAaq4BavA/builds/GCjMt9owgGbwwuLrQ/openapi.json