# Find Brand and Product Mentions on Telegram — CSV

**Use case:** 

Find up to five literal brand or product mentions, starting with NotebookLM. Export text, dates, channels and source links to CSV. Standard discovery, last 90 days. Review coverage warnings; no sentiment analysis. Saved run cap $0.03; check Pricing.

## Input

```json
{
  "collectionMode": "keyword",
  "keywords": [
    "NotebookLM"
  ],
  "channels": [],
  "maxResults": 5,
  "afterDate": "90 days",
  "countryCode": "auto",
  "languageCode": "auto",
  "discoveryCoverage": "standard",
  "maxResultsPerChannel": 2,
  "spreadAcrossChannels": false,
  "maxUnproductiveDiscoveryPages": 2,
  "searchWithinChannels": false,
  "keywordMatchScope": "postText",
  "excludeSignatureOnlyMatches": true,
  "includeContextPosts": false,
  "includeKeywords": [],
  "excludeKeywords": [],
  "regexFilters": [],
  "excludeChannels": [],
  "sourcePriority": "channelsFirst",
  "downloadMedia": false
}
```

## Output

```json
{
  "messageUrl": {
    "label": "Post URL",
    "format": "string"
  },
  "channelUsername": {
    "label": "Channel username",
    "format": "string"
  },
  "channelName": {
    "label": "Channel name",
    "format": "string"
  },
  "channelUrl": {
    "label": "Channel URL",
    "format": "string"
  },
  "messageId": {
    "label": "Message id",
    "format": "string"
  },
  "publishedAt": {
    "label": "Published",
    "format": "string"
  },
  "text": {
    "label": "Post text",
    "format": "string"
  },
  "views": {
    "label": "Views",
    "format": "string"
  },
  "reactions": {
    "label": "Reactions",
    "format": "array"
  },
  "media": {
    "label": "Media",
    "format": "array"
  },
  "matchedKeywords": {
    "label": "Matched keywords",
    "format": "array"
  },
  "matchedTextKeywords": {
    "label": "Keywords in post text",
    "format": "array"
  },
  "matchedChannelKeywords": {
    "label": "Keywords in channel title",
    "format": "array"
  },
  "matchType": {
    "label": "Match type",
    "format": "string"
  },
  "discoveredBy": {
    "label": "Collection source",
    "format": "string"
  },
  "scrapedAt": {
    "label": "Collected",
    "format": "string"
  }
}
```

## How it works

### 1. Sign up on Apify or log in

The Telegram Keyword Search Scraper | Brand Mentions Actor is ready to run with the inputs already set for "Find Brand and Product Mentions on Telegram — CSV". [Sign up or log in](https://console.apify.com/create-task-from-example/iMJYY31V0v4SmnQZw) and you'll land in Apify Console with a copy of this exact task.

### 2. Start the "Find Brand and Product Mentions on Telegram — CSV" task

The Telegram Keyword Search Scraper | Brand Mentions Actor will start running based on the input automatically. You can also change all the input fields, like what do you want to collect?, keywords to find, and more, to match your specific use case.

### 3. Receive the "Find Brand and Product Mentions on Telegram — CSV" output

Monitor the progress in real time. You will be notified as soon as your dataset is complete and ready for review. Each result includes data such as post url, channel username, channel name, and more.

### 4. Integrate into your workflow

The final output is delivered in JSON, CSV, or Excel format, ready to be plugged into your workflow. You can also [run the "Find Brand and Product Mentions on Telegram — CSV" task via API](https://apify.com/monkey.d.scraping/telegram-keyword-search-channel-scraper.md).

## FAQ

### Does a product mention mean positive customer feedback?

The Telegram product-mentions task finds literal words, not sentiment or verified customer feedback. Review each source: posts may be promotions, roundups or passing references.

### What does the first test cost?

Example: three verified pages + five posts + one start cost $0.02005 at standard rates, up to 1 GB. Platform usage included. The $0.03 cap is a limit, not a fee. Empty verified pages are chargeable; check Pricing.

### Can results be empty or in another language?

The Telegram product-mentions task uses partial public indexing. A successful search can be empty or multilingual. Check Results and next steps before broadening the query. Private channels are outside its coverage.

### How do I export and reuse the results?

After the run, review the linked posts and export the dataset as CSV or JSON. Repeated searches may return duplicates. Use the separate Telegram New Posts Monitor when you need checkpoint-based collection.

### Does opening this example start a paid run?

Opening this example creates an editable task copy. Review Run options and the spending cap, then choose Start or Save & start to run. No schedule is included. Actor charges apply when run; Try for free is the platform button label.

## About this Actor

This example demonstrates how to use [Telegram Keyword Search Scraper | Brand Mentions](https://apify.com/monkey.d.scraping/telegram-keyword-search-channel-scraper.md) with a specific input configuration. Visit the [Actor detail page](https://apify.com/monkey.d.scraping/telegram-keyword-search-channel-scraper.md) to learn more, explore other use cases, and run it yourself.


## How to integrate an Actor?

This Task's input is already configured above. Use it as-is rather than inventing a new one.

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 full API examples (JavaScript, Python, CLI, MCP, OpenAPI), see this Task's Actor page: https://apify.com/monkey.d.scraping/telegram-keyword-search-channel-scraper.md

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`).