MonkeyLearn 3.0

Get actionable data from text with machine learning

#5 Product of the WeekMay 30, 2018
+1

Turn emails, support tickets, chats, social media, surveys and documents into actionable data. Make your teams more efficient by automating business processes, getting insights and saving hours of manual text data processing.

Reviews

  • Alejandro Tocar
    Alejandro TocarCEO @ SAGAL
    Pros: 

    Super easy to use

    Support is great

    Takes under 15 minutes to start getting value

    Cons: 

    none so far!

    I was lucky to try out the new features over the last few weeks.

    The new UI is not only beautiful, but they were able to take complicated and technical concepts and present them in a way anyone could understand, so you can get value in no time.

    Congrats on the launch!

    Alejandro Tocar has used this product for one month.
  • Nico Bistolfi
    Nico BistolfiFounder at @piiojs
    Pros: 

    Events classifiers work like a charm

    Cons: 

    Can't classify what my dog is trying to say... yet

    Nico Bistolfi has used this product for one year.

Discussion

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Raúl Garreta
Raúl GarretaMaker@rgarreta
Hi everybody, we're excited to introduce MonkeyLearn 3.0! You may know of us as a service that makes it easy to classify texts (by topic, sentiment or intent) or to extract specific data (such as keywords, names, companies and addresses). Over the last couple years we have been working with clients ranging from well known SaaS companies, to oil and gas businesses. They have all had a common need to automate manual processes around text analysis: whether it be to process support tickets, analyze feedback or reviews, or extract information from contracts and documents. We are now launching a new MonkeyLearn version allowing more people to build text analysis models powered by machine learning. Here is what we are excited to share: - New redesigned GUI and API: a cleaner and simpler to use both for technical and non-technical users. - Custom Extractors: this is a new major feature, you can train a ML model to extract custom data within texts. - Custom Classifiers: you can train a ML model to classify texts into tags as with our previous version, but much easier :) - Active Learning: the tagging process is quicker and tags are suggested as you train the model. Looking forward to hearing your feedback!
Shreyaa Ratra
Shreyaa Ratra@shreyaa_ratra · Making B2B sales easy via EasyLeadz.com
@rgarreta Can't wait to test it out for my own SAAS. Couple of thoughts if you do B2B : A) Target SAAS companies who have recently raised funding. Their prime focus will be to scale. Scale >> More users >> More customer queries >> MonkeyLearn B) Target companies who are hiring for customer support/customer feedback because these are the companies who are hiring for more customer service employees and will be needing a solution to handle/process their tickets.
Santiago Alonso
Santiago AlonsoPro@madebysan · Product Designer
@rgarreta congrats! 💪🇺🇾
Federico Pascual
Federico PascualMaker@federicopascual · COO @MonkeyLearn.
@rgarreta @shreyaa_ratra let me know how it goes, I'm happy to help! Thanks for the ideas :)
Federico Pascual
Federico PascualMaker@federicopascual · COO @MonkeyLearn.
@rgarreta @madebysan thank you mate 😊
Raúl Garreta
Raúl GarretaMaker@rgarreta
@shreyaa_ratra Answering your comments: A) That's right, believe that repetitive tasks like tagging support tickets and customer feedback should be done automatically by machines. That means more efficient support/product teams: scalability and more consistent criteria. In the case of customer support: shorter response times >> happier customers. In the case of customer feedback: more powerful insights from qualitative data >> better products >> happier customers. B) Agree, this is a rising area, product companies must compete on having meaningful interactions with their customers. Our mission is to empower (not substitute) teams such as customer service to achieve those goals. Humans should be focused on strategical tasks, machines on the repetitive ones.
guillaume cabane
guillaume cabane@guillaumecabane · VP Growth @Segment
Been using MonkeyLearn for 2 years now - and it's been an awesome experience. Excited to see all the improvements brought with 3.0, especially custom extractors. Here's what I've used MonkeyLearn for: - Categorize NPS comments to inform my product team - Sentiment analysis on outbound email campaign responses (as a leading indicator to campaign/list quality) - Many other unpublished growth hacks :)
Raúl Garreta
Raúl GarretaMaker@rgarreta
@guillaumecabane Thank you G! We've learned a lot from your use cases ;)
Amazing! Congrats guys
Raúl Garreta
Raúl GarretaMaker@rgarreta
@sap_uy thank you!
Cody Fitzpatrick
Cody Fitzpatrick@codyfitzpatrick · Founder @ Timeline.io & OrbitalOne
Product and website look great. Congrats @rgarreta and @federicopascual on reaching V3! Your efforts on this will surely pay off if they haven't already. Looking forward to trying it!
Raúl Garreta
Raúl GarretaMaker@rgarreta
@federicopascual @codyfitzpatrick Thank you Cody! Definitely all the team has been working very hard :D Would love to hear your comments after you try it out!
Federico Pascual
Federico PascualMaker@federicopascual · COO @MonkeyLearn.
@rgarreta @codyfitzpatrick thanks Cody for the kind words! Looking forward for your feedback :)
Tibor Fejos
Tibor Fejos@fejostibor · Manager, Tower
I want this!
Federico Pascual
Federico PascualMaker@federicopascual · COO @MonkeyLearn.
@fejostibor sweet! would me amazing if you can try it out!