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Why Do Agents Go Off Script? Mistakes vs Improvisation

Balto

When agents intentionally go off script, it’s because they are improvising to get a better call outcome and should be encouraged. In 2022, we published our findings on why agents intentionally go off their scripts. Why Agents Go Off Script. Figure 3: Why do agents go off script? Key Takeaways.

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The Key Role of Call Center Dynamic Agent Scripting in Customer Experience

NobelBiz

Scripts are an essential component of every contact center. The correct amount of data and accurate information delivery can yield impressive scripting capabilities. To provide a better customer experience (CX), dynamic agent scripting is required. Table of Contents show What is call center Dynamic Agent Scripting?

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The Customer Success Maturity Model Part 2: “Operationalize” Capabilities (Constructing Your CS System)

Education Services Group

Constructing and evolving these processes is the second category of capabilities on the ESG Customer Success Maturity Model. Metrics that track your customers’ experience are crucial to the stability and longevity of your CS organization. Let’s break that down a bit. CX (NPS, CSAT, etc.).

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Build an air quality anomaly detector using Amazon Lookout for Metrics

AWS Machine Learning

This post shows you how to use an integrated solution with Amazon Lookout for Metrics and Amazon Kinesis Data Firehose to break these barriers by quickly and easily ingesting streaming data, and subsequently detecting anomalies in the key performance indicators of your interest. You don’t need ML experience to use Lookout for Metrics.

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The Comprehensive Guide to Assessing the Average Talk Time Metric in Call Centers

NobelBiz

For call centers, metrics provide insights that shape strategies and determine operational efficiency. Among these metrics, the “Talk” metric stands out as a vital instrument. Understanding the Average Talk Time metric Average Talk Time represents the actual duration an agent spends conversing with a customer.

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Introduction to Process Mining: Understanding the Basics and Benefits

CSM Magazine

Process Discovery Algorithms : Algorithms like Alpha Miner and Heuristics Miner automatically construct process models from event data. Performance Analysis : Metrics such as throughput, cycle time, and resource utilization are essential for process optimization. Organizations collect data from various sources (e.g.,

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Build an end-to-end MLOps pipeline for visual quality inspection at the edge – Part 2

AWS Machine Learning

With this format, we can easily query the feature store and work with familiar tools like Pandas to construct a dataset to be used for training later. We can follow a simple three-step process to convert an experiment to a fully automated MLOps pipeline: Convert existing preprocessing, training, and evaluation code to command line scripts.

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