SimilarTube is an AI-powered tool designed to help users find similar YouTube channels based on a given channel. Unlike traditional third-party influencer databases, SimilarTube uses an AI bot to scan YouTube directly, providing real-time results within seconds. This approach ensures up-to-date information, especially for nano and micro influencers, making it an efficient solution for influencer marketing and channel discovery.
SimilarTube
AI Scanner & Analytics for Similar YouTube Channels
Introduction
Feature
AI-Powered Algorithm
SimilarTube's AI bot scans YouTube directly, delivering real-time results in seconds, ensuring the most current information.
Key Metrics Extraction
The AI automatically extracts public email addresses and other social media accounts (Facebook, Instagram, TikTok, etc.), facilitating quick contact information retrieval.
Automatic Email Matching and Template Filling
This feature accelerates the outreach process, making it 10 times faster than traditional methods.
AI Insight Feature
Automatically assesses niche value and highlights core metric differences among YouTubers of various tiers, providing valuable market insights.
Filtering and Sorting Capabilities
Enables convenient analysis of search results, allowing users to efficiently find the most suitable channels.
Look-Alike Algorithm
Finds similar influencers based on a given channel, displaying key metrics like engagement rate (ER) and video view rate (VVR) for quick screening.
FAQ
How does SimilarTube work?
SimilarTube uses an AI bot to scan YouTube directly, delivering real-time results in seconds. This method ensures more accurate and up-to-date information compared to traditional influencer databases.
What are the benefits of using SimilarTube?
Benefits include:
- Time-saving with real-time results
- Accurate and current information
- Efficient influencer discovery
- Enhanced analysis through AI Insights
- Streamlined outreach process
How much does SimilarTube cost?
SimilarTube offers in-app purchases. Users can subscribe to affordable products for extended access and additional features.
What are some helpful tips for using SimilarTube?
- Use it to find similar influencers for marketing campaigns
- Utilize the AI Insight feature to analyze the competitive landscape
- Take advantage of automatic email matching and template filling for faster outreach
Latest Traffic Insights
Monthly Visits
193.90 M
Bounce Rate
56.27%
Pages Per Visit
2.71
Time on Site(s)
115.91
Global Rank
-
Country Rank
-
Recent Visits
Traffic Sources
- Social Media:0.48%
- Paid Referrals:0.55%
- Email:0.15%
- Referrals:12.81%
- Search Engines:16.21%
- Direct:69.81%
Related Websites
AiJobster - Job Search in AI Companies and Remote AI Jobs
AiJobster - Job Search in AI Companies and Remote AI JobsAiJobster - Your premier platform for job search in AI companies and remote jobs across top AI-driven organizations. Discover your future in tech today!
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* Create a new notebook
* Install the `transformers` library by running `!pip install transformers`
* Import the `transformers` library and load the ChatGPT model using `from transformers import AutoModelForCausalLM, AutoTokenizer; model = AutoModelForCausalLM.from_pretrained('chatgpt'); tokenizer = AutoTokenizer.from_pretrained('chatgpt')`
* Use the model to generate text using `input_text = "Your input here"; inputs = tokenizer.encode_plus(input_text, return_tensors='pt', max_length=1024, padding='max_length', truncation=True); output = model(inputs['input_ids'], attention_mask=inputs['attention_mask']); print(tokenizer.decode(output.logits[0], skip_special_tokens=True))`
Method 2: Google Apps Script
* Open Google Apps Script ([script.google.com](http://script.google.com))
* Create a new project
* Install the `transformers` library by running `npm install transformers`
* Import the `transformers` library and load the ChatGPT model using `const { AutoModelForCausalLM, AutoTokenizer } = require('transformers'); const model = new AutoModelForCausalLM('chatgpt'); const tokenizer = new AutoTokenizer('chatgpt');`
* Use the model to generate text using `const inputText = "Your input here"; const inputs = tokenizer.encodePlus(inputText, { return_tensors: 'pt', max_length: 1024, padding: 'max_length', truncation: true }); const output = model(inputs.inputIds, inputs.attentionMask); console.log(tokenizer.decode(output.logits[0], { skipSpecialTokens: true }));`
Note: These methods require some technical knowledge and may have limitations compared to the original ChatGPT model.](https://static.right-ai.com/tools/2024/7/3/chromewebstore-google-com-detail-chatgpt-for-google-for-fr-pabeminldebomngnkgffiejipjjaaogi-thumbnail-1720037311.png "Get ChatGPT for Free with Google
You can now access ChatGPT, a powerful language model, for free with Google. Here's how:
Method 1: Google Colab
* Open Google Colab ([colab.research.google.com](http://colab.research.google.com))
* Create a new notebook
* Install the `transformers` library by running `!pip install transformers`
* Import the `transformers` library and load the ChatGPT model using `from transformers import AutoModelForCausalLM, AutoTokenizer; model = AutoModelForCausalLM.from_pretrained('chatgpt'); tokenizer = AutoTokenizer.from_pretrained('chatgpt')`
* Use the model to generate text using `input_text = \"Your input here\"; inputs = tokenizer.encode_plus(input_text, return_tensors='pt', max_length=1024, padding='max_length', truncation=True); output = model(inputs['input_ids'], attention_mask=inputs['attention_mask']); print(tokenizer.decode(output.logits[0], skip_special_tokens=True))`
Method 2: Google Apps Script
* Open Google Apps Script ([script.google.com](http://script.google.com))
* Create a new project
* Install the `transformers` library by running `npm install transformers`
* Import the `transformers` library and load the ChatGPT model using `const { AutoModelForCausalLM, AutoTokenizer } = require('transformers'); const model = new AutoModelForCausalLM('chatgpt'); const tokenizer = new AutoTokenizer('chatgpt');`
* Use the model to generate text using `const inputText = \"Your input here\"; const inputs = tokenizer.encodePlus(inputText, { return_tensors: 'pt', max_length: 1024, padding: 'max_length', truncation: true }); const output = model(inputs.inputIds, inputs.attentionMask); console.log(tokenizer.decode(output.logits[0], { skipSpecialTokens: true }));`
Note: These methods require some technical knowledge and may have limitations compared to the original ChatGPT model.")
Get ChatGPT for Free with Google You can now access ChatGPT, a powerful language model, for free with Google. Here's how: Method 1: Google Colab * Open Google Colab ([colab.research.google.com](http://colab.research.google.com)) * Create a new notebook * Install the `transformers` library by running `!pip install transformers` * Import the `transformers` library and load the ChatGPT model using `from transformers import AutoModelForCausalLM, AutoTokenizer; model = AutoModelForCausalLM.from_pretrained('chatgpt'); tokenizer = AutoTokenizer.from_pretrained('chatgpt')` * Use the model to generate text using `input_text = "Your input here"; inputs = tokenizer.encode_plus(input_text, return_tensors='pt', max_length=1024, padding='max_length', truncation=True); output = model(inputs['input_ids'], attention_mask=inputs['attention_mask']); print(tokenizer.decode(output.logits[0], skip_special_tokens=True))` Method 2: Google Apps Script * Open Google Apps Script ([script.google.com](http://script.google.com)) * Create a new project * Install the `transformers` library by running `npm install transformers` * Import the `transformers` library and load the ChatGPT model using `const { AutoModelForCausalLM, AutoTokenizer } = require('transformers'); const model = new AutoModelForCausalLM('chatgpt'); const tokenizer = new AutoTokenizer('chatgpt');` * Use the model to generate text using `const inputText = "Your input here"; const inputs = tokenizer.encodePlus(inputText, { return_tensors: 'pt', max_length: 1024, padding: 'max_length', truncation: true }); const output = model(inputs.inputIds, inputs.attentionMask); console.log(tokenizer.decode(output.logits[0], { skipSpecialTokens: true }));` Note: These methods require some technical knowledge and may have limitations compared to the original ChatGPT model.
Get ChatGPT for Free with Google You can now access ChatGPT, a powerful language model, for free with Google. Here's how: Method 1: Google Colab * Open Google Colab ([colab.research.google.com](http://colab.research.google.com)) * Create a new notebook * Install the `transformers` library by running `!pip install transformers` * Import the `transformers` library and load the ChatGPT model using `from transformers import AutoModelForCausalLM, AutoTokenizer; model = AutoModelForCausalLM.from_pretrained('chatgpt'); tokenizer = AutoTokenizer.from_pretrained('chatgpt')` * Use the model to generate text using `input_text = "Your input here"; inputs = tokenizer.encode_plus(input_text, return_tensors='pt', max_length=1024, padding='max_length', truncation=True); output = model(inputs['input_ids'], attention_mask=inputs['attention_mask']); print(tokenizer.decode(output.logits[0], skip_special_tokens=True))` Method 2: Google Apps Script * Open Google Apps Script ([script.google.com](http://script.google.com)) * Create a new project * Install the `transformers` library by running `npm install transformers` * Import the `transformers` library and load the ChatGPT model using `const { AutoModelForCausalLM, AutoTokenizer } = require('transformers'); const model = new AutoModelForCausalLM('chatgpt'); const tokenizer = new AutoTokenizer('chatgpt');` * Use the model to generate text using `const inputText = "Your input here"; const inputs = tokenizer.encodePlus(inputText, { return_tensors: 'pt', max_length: 1024, padding: 'max_length', truncation: true }); const output = model(inputs.inputIds, inputs.attentionMask); console.log(tokenizer.decode(output.logits[0], { skipSpecialTokens: true }));` Note: These methods require some technical knowledge and may have limitations compared to the original ChatGPT model.How to Add ChatGPT to All Google Searches ===================================================== Step 1: Create a Custom Search Engine -------------------------------------- * Go to the [Google Custom Search Engine](https://cse.google.com/) website and sign in with your Google account. * Click on the "New Search Engine" button. * Fill in the required information, such as the name and description of your search engine. * Click on the "Create" button. Step 2: Add ChatGPT to the Search Engine ----------------------------------------- * In the "Setup" tab, click on the "Add" button next to "Sites to search". * Enter the following URL: `https://chat.openai.com/` * Click on the "Add" button. Step 3: Configure the Search Engine -------------------------------------- * In the "Setup" tab, click on the "Edit" button next to "Search engine keywords". * Add the following keywords: `ChatGPT` * Click on the "Save" button. Step 4: Get the Search Engine Code ------------------------------------- * In the "Setup" tab, click on the "Get code" button. * Copy the HTML code provided. Step 5: Add the Search Engine to Your Browser ------------------------------------------------ * Open your browser and go to the "Settings" or "Options" page. * Look for the "Search engine" or "Default search engine" option. * Click on the "Add" or "Manage search engines" button. * Paste the HTML code you copied earlier. * Click on the "Add" or "Save" button. You're Done! =============== Now, whenever you search on Google, ChatGPT will be included in the search results. You can also use the custom search engine URL provided by Google to search directly.
193.90 M
Easily convert your conversations, audio files, or YouTube videos into text for free with our advanced transcription tool.
835.16 K
![AIScraper
This is a Python library for scraping data from websites that use the Amazon Interactive Search (AIS) API.
Features:
* Easy to use: Simply provide a search query and the library will return a list of product results.
* Flexible: You can customize your scraping by specifying filters, such as price range, brand, and category.
* Efficient: The library uses asynchronous requests to speed up the scraping process.
* Reliable: The library is designed to handle rate limits and other website restrictions.
Installation:
```bash
pip install aiscraper
```
Usage:
```python
from aiscraper import AIScraper
Create an instance of the AIScraper class
scraper = AIScraper()
Perform a search for "laptops"
results = scraper.search("laptops")
Print the product titles
for result in results:
print(result["title"])
```
Documentation:
https://github.com/aiscraper/aiscraper](https://static.right-ai.com/tools/2024/7/4/chromewebstore-google-com-detail-aiscraper-mfjniiodgjhlmleaakofgijfccdgppbc-thumbnail-1720072105.png "AIScraper
This is a Python library for scraping data from websites that use the Amazon Interactive Search (AIS) API.
Features:
* Easy to use: Simply provide a search query and the library will return a list of product results.
* Flexible: You can customize your scraping by specifying filters, such as price range, brand, and category.
* Efficient: The library uses asynchronous requests to speed up the scraping process.
* Reliable: The library is designed to handle rate limits and other website restrictions.
Installation:
```bash
pip install aiscraper
```
Usage:
```python
from aiscraper import AIScraper
Create an instance of the AIScraper class
scraper = AIScraper()
Perform a search for \"laptops\"
results = scraper.search(\"laptops\")
Print the product titles
for result in results:
print(result[\"title\"])
```
Documentation:
https://github.com/aiscraper/aiscraper")
AIScraper This is a Python library for scraping data from websites that use the Amazon Interactive Search (AIS) API. Features: * Easy to use: Simply provide a search query and the library will return a list of product results. * Flexible: You can customize your scraping by specifying filters, such as price range, brand, and category. * Efficient: The library uses asynchronous requests to speed up the scraping process. * Reliable: The library is designed to handle rate limits and other website restrictions. Installation: ```bash pip install aiscraper ``` Usage: ```python from aiscraper import AIScraper Create an instance of the AIScraper class scraper = AIScraper() Perform a search for "laptops" results = scraper.search("laptops") Print the product titles for result in results: print(result["title"]) ``` Documentation: https://github.com/aiscraper/aiscraper
AIScraper This is a Python library for scraping data from websites that use the Amazon Interactive Search (AIS) API. Features: * Easy to use: Simply provide a search query and the library will return a list of product results. * Flexible: You can customize your scraping by specifying filters, such as price range, brand, and category. * Efficient: The library uses asynchronous requests to speed up the scraping process. * Reliable: The library is designed to handle rate limits and other website restrictions. Installation: ```bash pip install aiscraper ``` Usage: ```python from aiscraper import AIScraper Create an instance of the AIScraper class scraper = AIScraper() Perform a search for "laptops" results = scraper.search("laptops") Print the product titles for result in results: print(result["title"]) ``` Documentation: https://github.com/aiscraper/aiscraperWeb scraper, powered by AI! Collect structured data from web pages in just a few clicks! What's new 🔹Simplified data collection…
193.90 M
Find inspiration online and buy the look. Choose any picture while you're browsing and search for similar styles from Fynd's entire catalog.
193.90 M
