Create new value from your data. Train custom machine learning models to get topic, sentiment, intent, keywords and more.
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It's easy to connect Monkey Learn + Drift without coding knowledge. Start creating your own business flow.
Triggers each time when a new message in a conversation is received.
Classifies texts with a given classifier.
Extracts information from texts with a given extractor.
Uploads data to a classifier.
Create or update a contact.
Updates an existing contact.
Monkey Learn is a machine learning platform that helps users with a variety of tasks including text classification, sentiment analysis, image labeling and more. It supports a variety of datasets including YouTube, Bing, Twitter and Reddit.
Drift is a marketing platform for small businesses that allows them to track real-time interactions with customers via live chat, screen sharing, ppling and more. Drift also offers a wide range of features such as analytics, reporting and integrations with other apps.
the integration process of Monkey Learn and Drift?
This integration requires a few steps. First, you must create a MonkeyLearn classifier in the Drift interface in order to create a similar model for Drift. After that, you can use this model in Drift in order to classify customer messages into predefined categories.
In the fplowing example, we will use the Drift classifier to add a classification for positive feedback in Drift. In order to do this, we must first create a classifier in the MonkeyLearn interface.
Step 1. After logging in to the Drift interface, click on the “Classifiers” tab and then “Create new classifier”:
Step 2. Here we must fill out the field “Name of your classifier” and select “Behavior”:
Step 3. Choose “Positive feedback” from the drop-down menu:
Step 4. Add tags to your classifier by clicking on the icon “Tags”:
Step 5. Fill out all fields and click on “Save”:
Step 6. After saving this classifier, we must go back to the Drift interface and click on “Classifiers”:
Step 7. Drag the classifier we created in Step 1 and drop it on the “Behavior” icon:
Step 8. Finally, we click on the icon “Add Classifier” and choose our classifier from the drop-down menu:
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