Text Classification by MonkeyLearn

Simple and customizable text classification with AI

Text classification can automatically turn user generated content into structured tags or categories, including sentiment, topic, intent and more.
MonkeyLearn provides a simple GUI to allow non-technical users to create and use custom classifiers in minutes!
Would you recommend this product?
4 Reviews5.0/5
Hello everybody 👋 We're excited to share our **classification feature**; we've been working on it for a while now and iterating on it based on feedback from our customers. These are the highlights: 🤖**Active learning** it minimizes the effort while tagging and training models. ❤️**Pre-trained sentiment analysis** best sentiment analysis model in the market, using cutting edge deep learning. 🚀**More robust backend** we've been working with well-known companies ranging from top social apps, developer platforms and electric scooter rental services. That means we had to build an extremely reliable service that can tackle high volume transactions in real time. 🔌**Improved integrations** new versions of our integrations with Zapier, Zendesk and Google Sheets. 👨‍💻**Redesigned API and SDKs** deeper integration for developers. I wanted to share some of the **top 3 most frequent use cases** we've seen so far. We're amazed by how business teams are leveraging our AI technology in their operations without the need of technical skills! ⏰**Customer support automation** take the subject and body of a new ticket and turn into a set of tags (topic, urgency, intent, etc). Customers are using those tags alongside rules to automatically route tickets to the right team in real time, allowing them **50% reduction on first response times**. 💎**Customer feedback analysis** turn thousands of pieces of qualitative feedback (surveys, reviews, NPS comments, support tickets, emails and chats) into pre-defined buckets (categories) such as topics, features, intent (feature request, opinion, issues, etc) and sentiment (positive, negative, neutral). Qualitative feedback usually gets buried in CRMs, survey, support and chat tools. Our customers are turning data into value! 💰**Sales automation** categorize inbound messages (email, chat, sms) as "interested", "not interested", "support", "sales" "qualified" "not qualified", "high priority", etc. By automatically classifying messages, the sales teams can prioritize leads in a more effective way, boosting sales productivity. 👉We'd love to get your feedback, sign up for FREE and give it a try!
I've tried MonkeyLearn on a few projects and it's fantastic. So excited to see this new feature come out, it's something Ive been looking for for a while!
@jamesdevonport that's awesome! I'd love to know more about your projects, can you tell me more?
@rgarreta I used MonkeyLearn previously to analyse event attendees and to classify them by type which was super handy! Currently working on a content automation product (gofelix.ai) but am using Google Cloud's NLP categorisation purely because of the cost for that one. Will definitely check this out soon as I can though - loved how easy your API was to integrate compared to Google.
@jamesdevonport interesting, ping me at my email, happy to bump up your free account limits if you want to try it out!
Huge fan of MonkeyLearn - excited to try this new feature
Thanks @pierrelepoulain! Shoot me an email when you try it, I'd love to get your feedback!
Very cool product and great implementation.
This looks like a point-and-click version of the excellent open source https://spacy.io/ python NLP library. I'm pretty sure their entity extraction demo was the first place to use labels to highlight entities https://spacy.io/usage/visualize.... This looks like a great way for non-technical people to get started though - your explainer vid does a great job and it looks super easy to use, well done!
Hey @alxcnwy I appreciate your comment! We love Spacy and Python, we have them as part of our stack. You should also try our custom extractors too! You're exactly right, we want to make NLP accessible for non-technical people 🎉