Lexalytics®, an InMoment® Company and pioneer in AI-based NLP technology, announced today that its Head, Jeff Catlin, and its Chief Scientist, Paul Barba, will present at the Text Analytics Forum in Washington, D.C. on November 9th.
Lexalytics, an InMoment Company and pioneer in AI-based NLP technology, announced that its Head, Jeff Catlin, and its Chief Scientist, Paul Barba, will present at the Text Analytics Forum in Washington, D.C. on November 9th. Details of their presentations are:
Who: Paul Barba, Chief Scientist, Lexalytics, an InMoment Company
Jeff Catlin, Head of Lexalytics, an InMoment Company
What: “Machine-Learning Model-Building for NLP: What Can & Can’t Be Automated?”
“How Text Analytics Are Driving the Innovation in Experience Improvement in an Omnichannel World”
When: November 9, 2022 at 11:45 a.m. ET – 12:30 p.m. ET (Paul Barba)
November 9, 2022 at 2:30 p.m. ET – 3:15 p.m. ET (Jeff Catlin)
Where:Text Analytics Forum
Washington, D.C. 20004
At the Forum, Paul Barba will speak about the growing popularity of AutoML platforms, and how it’s a good time to take a step back and evaluate what is and isn’t currently possible with automated machine learning. The questions that will be answered are, can the machines clean data for me? How do you choose an appropriate algorithm? And how do you detect changes in the world that invalidate a deployed model? Barba will look at the full lifecycle of a machine-learning project and discuss whether the task is best solved by humans, machines, or some combination of the two. He will also outline how different techniques, from traditional supervised learning to approaches like reinforcement learning, can introduce their own unique challenges and opportunities. Finally, when a human is called for, he has identified the skill sets and perspectives that provide the most value at each stage in the machine learning process.
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Subsequently, Jeff Catlin will discuss how the traditional CX space is undergoing a period of upheaval with many clients of CX vendors questioning the value of purely survey-focused CX programs, and how you should measure the effect on their bottom line. This is where the concept of omnichannel text analytics and NLP comes into play. By measuring every part of a business and how the different parts affect each other, a business can get a holistic view of the winning and losing parts of their business. He will outline how It’s not customer experience (CX) and employee experience (EX) and product experience (PX) which suggest a siloing of the parts of a business. It’s Total Experience and how all of the different parts of your business affect each other. Catlin will discuss how if you have an issue in your call center isn’t enough; you need to be able to drill into the call center issue and see, for example, that most of the problems are related to a new product feature that is being poorly received by customers and feeding that back into product management so they can modify the product to meet customer needs and help the bottom line. The vendors that are best able to make the transition to working with all of a company’s feedback data, both structured and unstructured, regardless of where it came from, and be able to feed that back into operational business systems like product management, order processing, call center, and others are going to become the winners in the total experience space.
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