insights ai-data 
AWS Machine Learning
NOVEMBER 7, 2023
Without continued learning, these models remain oblivious to new data and trends that emerge after their initial training. Instead of relying solely on their pre-trained knowledge, RAG allows models to pull data from documents, databases, and more. The model then skillfully integrates this outside information into its generated text.
AWS Machine Learning
JUNE 13, 2023
Implementing a modern data architecture provides a scalable method to integrate data from disparate sources. By organizing data by business domains instead of infrastructure, each domain can choose tools that suit their needs. However, realizing the full benefits requires overcoming some challenges.
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CCNG
APRIL 12, 2024
If you received a penny for every time you heard “automation” or “AI” in the contact center, you could pay off the national debt in about a month. We will examine how automation and AI are not the same in the context of the contact center, that automation can contain AI and AI can utilize automation.
Callminer
JUNE 3, 2019
More companies are mastering their use of analytics, and are delving deeper into their data to increase efficiency, gain a greater competitive advantage, and boost their bottom lines even more.
Speaker: Rana Gujral, CEO at Behavioral Signals
Most importantly, it lacks the ability to immediately deliver actionable insights that can be used to improve real-time service. With the help of AI and voice data, conversations can be broken down and analyzed, helping businesses make changes to calibrate these conversations and ultimately improve outcomes.
Creative Virtual
APRIL 13, 2021
However, it can be a struggle to gather and identify the customer insights that are meaningful and most important for your CX strategy. In fact, Gartner analyst Augie Ray identified ‘looking in the wrong places for customer insight’ as one of the key mistakes that kill CX programmes in their infancy.
Beyond Philosophy
JULY 13, 2023
Organizations are making a common mistake with AI. For example, a large telecom company designed an AI system to identify customer churn. The issue was the AI didn’t pinpoint why the customers were leaving. Here’s the thing: AI models are outstanding at predicting customer behavior.
Speaker: Francoise Tourniaire - Founder of FT Works, Omid Razavi - Chief Advocacy Officer at SupportLogic, and Gregory Walker - Senior Product Manager at SupportLogic
Traditional methods of agent coaching lack the ability to automatically analyze the unstructured data inside support interactions to identify opportunities for improvement and reward strong performance. Attendees will walk away with insight on the following: Critical components for coaching programs.
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