Remove Engineering Remove ML Remove Sentiment Analysis
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To AI or not to AI? The support leader’s dilemma

Intercom

Embracing a new era The hype around ChatGPT might be very new, but artificial intelligence (AI) and machine learning (ML) have actually been around for quite some time. Up to now, companies would have needed an army of data scientists to make AI and ML work well, but that has all changed. instead, it’s, “When and how will I use it?”

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Improving support quality while embracing AI: Strategies from Intercom and Klaus

Intercom

Mervi Sepp Rei, Head Of ML and Data at Klaus That is, of course, if AI is properly implemented. Mervi Sepp Rei, Head Of ML and Data at Klaus Collaboration between AI tools, QA teams, and human agents is crucial. Mervi Sepp Rei, Head Of ML and Data at Klaus 5.

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Glossary of AI terms: Understanding GPT, neural networks, and more

Intercom

Machine learning (ML) A subfield of AI that involves the development of algorithms and statistical models that enable machines to progressively improve their performance in a specific task without being explicitly programmed to do so.

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Wootric’s Deepa Subramanian on measuring the voice of the customer

Intercom, Inc.

I started in technology at Salesforce – I was their first female engineer and learned early on how valuable it can be to build a company from the perspective of your customer. No, but one thing about our approach that’s helpful to know is that there are a lot of out-of-the-box text and sentiment analysis tools available.

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Top Customer Experience Tools to Boost Your CX Mojo in 2024

SurveySensum

Impact Analysis: Evaluate the effects of different actions on your business outcomes, helping you prioritize initiatives that drive real, tangible results. Text and Sentiment Analysis: Turn those customer comments into gold. Personalization: Uses AI and ML to personalize content according to users’ actions and interests.

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