Twilio partners with IBM to offer real-time sentiment analysis

5 min read

Twilio partners with IBM to offer real-time sentiment analysis

You may not yet know what Twilio is, but you very well may have already used it.

If you’ve ever:

  • called your Uber driver to let her know what corner you’re standing on,

  • confirmed a reservation via text with an Airbnb host,

  • received a flight reminder from Expedia,

  • received two-factor authentication PIN via SMS from Box

…chances are you’ve used Twilio.

Twilio provides a software platform with globally available cloud APIs that allow developers to build relevant and contextual communications-driven experiences by embedding messaging, voice, and video capabilities directly into software applications.

You, and millions of others interact with Twilio on a daily basis. Twilio handled over 28 billion interactions between May 2016 and May 2017.

Recently Twilio partnered with IBM Cloud to enhance its cloud communication platform with three new offerings that are available as Add-ons in the Twilio Marketplace. IBM Watson Message Sentiment, IBM Watson Message Insights, and Watson Speech to Text are pre-integrated with Twilio’s APIs, and available to more than one million registered developers in Twilio’s community.

This partnership also enables developers who build their applications on IBM Bluemix to integrate the Twilio API and cognitive Watson services from the IBM Marketplace.

Watson represents a new era in computing called cognitive computing, where systems understand the world the way humans do: through senses, learning, and experience. Watson continuously learns from previous interactions, gaining in value and knowledge over time. These Watson Add-ons offer additional message enhancement capabilities through natural language processing to help people understand sentiment, keywords, entities and high-level concepts from text messages.

For example, with Twilio, call centers can use real-time sentiment analysis to flag which calls the supervisor should listen in on.

They can leverage post-hoc sentiment analysis to flag which calls went from angry customer to happy (or vice versa) for identifying agent training scenarios.

They can employ message sentiment and intent analysis to determine which message-based interactions can be handled automatically via a bot fulfilling self-service functions vs. which need to be delivered to an agent.

They can even use automatic language detection on inbound messaging interactions to make sure messages are delivered to the agent with the right language capabilities.

Twilio also recently demonstrated how Watson APIs could be integrated into a communication session between patient and doctor where Watson would transcribe in real time what the doctors was telling the patient. The patient would be able to see the medical terminology while the doctor would have sentiment insight based on the patient’s reactions using facial recognition technology. This would enhance the effectiveness of remote tele-medicine.

According to the American Tele-medicine Association, more than half of all U.S. hospitals now use some form of tele-medicine and the field is growing, as is the demand for services from companies Uber, Airbnb and Expedia.

People may not necessarily need to know how these services work, just that they do. And with Twilio, communications driven applications simply work better.


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