MonkeyLearn Integrations

  • Add tags to new Evernote notes with MonkeyLearn classification

    Do you take tons of notes but it's a little hard to keep organized? Some machine learning magic could help. With this integration, every time a new Evernote note is created, MonkeyLearn classifies it based on the title and text content. Tags are automatically added to the note based on MonkeyLearn classification.

    How this Evernote-MonkeyLearn integration works

    1. A new note is created in Evernote
    2. MonkeyLearn classifies the note based on the title and content
    3. Tag is added to the note based on MonkeyLearn classification

    Apps involved

    • Evernote
    • MonkeyLearn
  • +2

    Analyze HARO requests with MonkeyLearn and get notifications for relevant ones via Slack

    Have you ever wanted to get your company featured in TIME Magazine, Reuters or Mashable? It could happen through Help a Reporter Out (HARO) and get this media coverage for free by answering Help A Reporter Out requests.

    But why spend time screening HARO requests if machine learning can do the heavy lifting for you?

    This integration uses MonkeyLearn + Zapier + Slack to build a personalized notification system for HARO.

    How it works

    1. Get a new HARO requests from an RSS feed
    2. Zapier uses MonkeyLearn to classify HARO queries into AI & Machine Learning and Not Relevant
    3. The process will only continue if a HARO query is classified as AI & Machine Learning
    4. Zapier sends a private message via Slack notifying you about the AI & Machine Learning HARO query

    Apps involved

    • RSS by Zapier
    • MonkeyLearn
    • Filter by Zapier
    • Slack
  • Classify new RSS posts with MonkeyLearn and add them to Google Sheets

    Want to store blog posts of a particular topic in a Google Sheet? With this integration, every time a new post is created, the RSS feed will capture it and send it to MonkeyLearn to be classified. The result will be added to a Google Sheet spreadsheet.

    How it works

    1. A new post is published
    2. MonkeyLearn classifies the post based on the content
    3. The post and classification are added to a Google Sheet spreadsheet

    Apps involved

    • RSS by Zapier
    • MonkeyLearn
    • Google Sheets
  • Analyze new rows in Google Sheets with MonkeyLearn

    Wouldn't it be great if you could structure text content in your Google Sheets spreadsheet? With this integration, every time you add a new row to your spreadsheet, MonkeyLearn will analyze the content and fill structured columns with a sentiment, topic or any particular classification.

    How this Google Sheets-MonkeyLearn integration works

    1. A new row is added to a Google Sheets spreadsheet
    2. MonkeyLearn classifies the text content of the row
    3. Columns in the sheet are updated with the MonkeyLearn classification

    Apps involved

    • Google Sheets
    • MonkeyLearn
  • Label new Gmail emails based on MonkeyLearn classification

    Tired of manually labeling your emails in Gmail? Add artificial Intelligence to your workflow with MonkeyLearn. Every time a new email is received, MonkeyLearn will classify it based on the subject and body. New emails will be automatically labeled based on MonkeyLearn analysis.

    How it works

    1. A new email is received in your Gmail account
    2. MonkeyLearn classifies the email based on the subject and body content
    3. The email is labeled based on MonkeyLearn's classification

    What you need

    • Gmail
    • MonkeyLearn
  • Analyze Promoter.io feedback with MonkeyLearn and send to Google Sheets

    Struggling to analyze all of your open-ended feedback? With this integration, you will be able to process thousands of free format text answers with MonkeyLearn. When a new response is received in Promoter.io, MonkeyLearn will analyze the content and classify according to aspect or sentiment. The results will be sent to a Google Sheets spreadsheet.

    How it works

    1. A new survey response is completed in Promoter.io
    2. MonkeyLearn analyzes the response and gets the corresponding aspect or sentiment
    3. Zapier adds a new row to your selected Google Sheets spreadsheet

    Apps involved

    • Promoter.io
    • MonkeyLearn
    • Google Sheets
  • Tweet new blog posts based on your interests

    Want to automate how you tweet with artificial intelligence? What if you had an AI that mimics what you would and wouldn't share? Once you've set up a MonkeyLearn classifier that predicts if the content is relevant or not based on your interests, you can do exactly that! With this integration, every time a new post is published, MonkeyLearn will classify it based on the content and your custom classifier. If the classification results are relevant, it will be automatically shared on your Twitter account.

    How it works

    1. A new blog post is published
    2. MonkeyLearn classifies the post
    3. The content is posted to your Twitter account

    Apps involved

    • RSS by Zapier
    • MonkeyLearn
    • Twitter
  • Add tags to new Zendesk tickets based on MonkeyLearn classification

    Want to save precious time for your customer support team and automate support ticket classification and tagging? Once set up, this integration will automate ticket tagging and classification with MonkeyLearn. Every time a new ticket arrives in your Zendesk account, MonkeyLearn will classify the content (subject + body) to automatically tag the ticket.

    How this Zendesk-MonkeyLearn integration works

    1. A new ticket is created in Zendesk
    2. MonkeyLearn classifies the ticket based on the subject and body of the ticket
    3. Tag is added to the ticket based on MonkeyLearn classification

    Apps involved

    • Zendesk
    • MonkeyLearn
  • +2

    Use MonkeyLearn to keep tabs on competitors with a customized Product Hunt notifications Slack bot

    In a competitive tech industry, it’s important to regularly scan the lay of the land to spot trends and stay a step ahead of your rivals. Reading Product Hunt can help you scope out the latest launches in your space so you don't fall behind, but manually reviewing the website on a regular basis can seriously drain your time and energy.

    We ran into this very problem at MonkeyLearn, and after finding ourselves checking Product Hunt for the millionth time, we decided to make our own personalized notification system for Product Hunt posts related to our interests.

    This Zapier integration uses Product Hunt and MonkeyLearn to automatically trigger Slack direct messages from new Product Hunt updates that are relevant to our interests.

    How it works

    1. Product Hunt posts a new product.
    2. MonkeyLearn classifies the Product Hunt taglines as related to your topics of interest or not relevant.
    3. Zapier checks the data from MonkeyLearn and only allows the workflow to continue if the Product Hunt taglines are related to your specified topics.
    4. A direct message (DM) notification is sent via Slack for Product Hunt posts about your topics.

    Apps involved

    • Product Hunt
    • MonkeyLearn
    • Filter by Zapier
    • Slack
  • Upload emails from Gmail to MonkeyLearn

    Do you have an email classifier with MonkeyLearn and want to keep adding more training samples? With this integration, new labeled emails from Gmail will be sent into a MonkeyLearn classifier. The subject and body of the email will be used as the text and the label as the category.

    How it works

    1. A new email is labeled in Gmail
    2. The new email is uploaded to a MonkeyLearn classifier

    Apps involved

    • Gmail
    • MonkeyLearn
  • Analyze Delighted feedback with MonkeyLearn and add to Google Sheets

    Do you have hundreds or thousands of open-ended survey answers and struggling to get actionable feedback from them? With this integration, you will be able to process thousands of free format text answers with MonkeyLearn.

    When a new response is received in Delighted, MonkeyLearn will analyze the content and classify according to aspect or sentiment. The results will then be added a Google Sheets Spreadsheet.

    How it works

    1. A new survey response is completed in Delighted
    2. MonkeyLearn analyzes the response and gets the corresponding aspect or sentiment
    3. Zapier adds a new row to your selected Google Sheets spreadsheet

    Apps involved

    • Delighted
    • MonkeyLearn
    • Google Sheets
  • Tag new Zendesk tickets based on MonkeyLearn urgency classification

    Dealing with issues in order of urgency is a tried-and-true way to work through your support queue. Detect if the tone of an incoming support ticket is urgent and automatically tag it to help your support team process tickets faster and get to the important ones sooner. Use this Zapier integration to automatically send new Zendesk tickets through MonkeyLearn's text classification. Then Zapier will take the classification from MonkeyLearn and automatically tag the Zendesk ticket. That way, your support team doesn't waste time reading and tagging tickets manually.

    How this Zendesk-MonkeyLearn integration works

    1. A new ticket is created in Zendesk
    2. MonkeyLearn classifies the ticket using the Urgency Detector Module
    3. A tag is added to the Zendesk ticket

    Apps involved

    • Zendesk
    • MonkeyLearn
  • Add tags to new Zendesk tickets based on MonkeyLearn Keyword Extraction

    Want to save precious time for your customer support team and automate support ticket tagging? Once set up, this integration will automate ticket tagging based on MonkeyLearn Keywords Extractor. Every time a new ticket arrives in your Zendesk account, MonkeyLearn will Extract the most relevant keywords from the content (subject + body) to automatically tag the ticket.

    How this Zendesk-MonkeyLearn integration works

    1. A new ticket is created in Zendesk
    2. MonkeyLearn extracts relevant keywords from the ticket based on its subject and body.
    3. Keywords extracted are automatically added as tags.

    Apps involved

    • Zendesk
    • MonkeyLearn
  • Classify SatisMeter survey feedback text using MonkeyLearn

    If you’re receiving customer feedback on a large scale, one of the most daunting tasks can be turning huge numbers of hastily written comments into hard, actionable data. Using MonkeyLearn's Natural Language Processing, you can classify and tag the subjects of large amounts of feedback with complete automation.

    How this SatisMeter-MonkeyLearn integration works

    1. SatisMeter receives a new response with verbal feedback
    2. Zapier pushes the feedback to MonkeyLearn for classification.

    Apps involved

    • SatisMeter
    • MonkeyLearn
  • Analyze Retently feedback with MonkeyLearn and tag new responses

    Struggling to analyze all of your open-ended feedback on Retently? With this zap, you will be able to automatically process answers with MonkeyLearn. When a new response is received in Retently, MonkeyLearn will analyze the content and classify the answer according to aspect or sentiment. The results will be sent back to Retently to tag the customer response on the platform.

    How it works

    1. A new customer response is completed in Retently
    2. MonkeyLearn analyzes the response and gets the corresponding aspect or sentiment
    3. The customer response is tagged in Retently

    Apps involved

    • Retently
    • MonkeyLearn

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MonkeyLearn Integration Details

Launched on Zapier November 12, 2016

Zapier combines Triggers (like "New Subscriber") and Actions (like "Extract Text") to complete an action in one app when a trigger occurs in another app. These combos—called "Zaps"—complete your tasks automatically.

The following MonkeyLearn Triggers, Searches, and Actions are supported by Zapier:

Extract Text

Extracts data from text and does other transformations. Eg: find keywords, clean up emails, etc.

Classify Text

Classifies a text. Eg: topic, sentiment, etc.

Upload Training Data

Uploads training data to a classifier. It may or may not be tagged.

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MonkeyLearn is an AI platform that allows you to classify and extract actionable data from raw texts like emails, chats, webpages, documents, tweets and more! You can classify texts with custom categories or tags like sentiment or topic, and extract any particular data like organizations or keywords.