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AI and Real-Time Tech vs. Traditional CX Surveys: Who Will Win the Upcoming Battle?

eglobalis

Using natural language processing (NLP) and machine learning, companies can interpret the tone and emotion behind customer interactions on a massive scale. Technologies enabling this include machine learning algorithms that learn from historical instances (e.g., Instead of explicitly asking How do you feel?,

AI 348
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From Asking to Knowing: How AI Is Replacing B2B Customer Surveys—Not If, but When

eglobalis

Beyond Surveys: Listening to Unstructured and Silent Feedback Much of the valuable feedback in B2B relationships is never explicitly given via a survey question. These health scores are increasingly powered by machine learning. Its spoken in passing on support calls, written in emails, or implied through customer behaviour.

B2B 303
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How AI and Omnichannel Support Elevate Customer Service in Call Center

Hodusoft

Machine Learning (ML) In the last few years, ML is proving to be a game changer for call centers and customer-facing organizations. Natural Language Processing (NLP) NLP enables machines to understand and interpret human language in a meaningful way.

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Track Performance and Boost Operational Efficiency With Contact Center Analytics

SurveySensum

Instead of relying on the traditional method of manually keeping track of customer interactions, feedback, and agent performance, contact center analytics centers around improving and optimizing customer service processes with the help of advanced analytics like AI, machine learning, etc. Let’s understand each of them.

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Fast-Track Support Success with Support Ticket Analysis

SurveySensum

All of this sets the stage for what really matterslets understand how AI and machine learning help in support ticket analysis. Heres where most teams struggle: Too Much Data, Not Enough Direction Support platforms collect everythingbut that everything quickly turns into noise if you dont know what youre looking for.

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Sentiment Analysis: Guide to Boost CX & Drive Business Insights

SurveySensum

Sentiment analysis is the process of analyzing open-ended feedback using AI technologies like natural language processing, machine learning, and text analytics. However, most customer feedback comes as unstructured datalacking a common shape or formwhich can make analysis time-consuming and complex. Lets dive in and explore.

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Top 5 Text Analytics Tools: Features, Benefits, and Use Cases

SurveySensum

In simple terms, text analytics tools leverage machine learning, NLP, and other AI capabilities to break down unstructured data from customer feedback, online reviews, customer support chat, etc. Text analytics tools use AI, NLP, and machine learning algorithms to process and interpret large volumes of text.