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Guest Blog: Is Your Contact Center Using the Right Customer Feedback Tool?

ShepHyken

As has been widely noted in today’s marketplace, your customers’ opinions and expectations – for good or bad, reasonable or not – are your company’s new benchmark. Before Soliciting Feedback. For example, is the goal to improve your customers’ experience, and if so, which facet? Agent Input.

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Key Benchmarks Should You Target In 2025 for your Contact Center

NobelBiz

With the advancement of the contact center industry, benchmarks continue to shift and challenge businesses to meet higher customer expectations while maintaining efficiency. In 2025, achieving the right benchmarks means understanding the metrics that matter, tracking them effectively, and striving for continuous improvement.

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Call Center Metrics: Examples, Tips & Best Practices

Callminer

Call on experienced managers for guidance in setting up benchmarks. “Experienced call center managers are helpful in setting up the initial performance benchmarks for a new outbound call center program. These benchmarks are, at first, estimated based on the past performance of similar outbound call center projects.

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Call Center Agent Feedback: Tips & Best Practices for Providing Effective Agent Feedback

Callminer

Providing feedback to agents in your call center is entirely needed to maintain and improve a quality facility. However, knowing how to deliver feedback can be tricky. Unfortunately, there are a number of pitfalls that can derail the process of delivering effective feedback.

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Study: The Health of the Contact Center

What does it take to engage agents in this customer-centric era? Download our study of 1,000 contact center agents in the US and UK to find out what major challenges are facing contact center agents today – and what your company can do about it.

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The state of CX: Trends and predictions for 2025

3CLogic

4 For example, GenAI call summarization can save agents an average of 6 minutes per call by automating the process of cleaning up notes and summarizing conversations. These solutions are setting new benchmarks for customer satisfaction by empowering organizations to solve more issues faster at a lower cost.

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LLM continuous self-instruct fine-tuning framework powered by a compound AI system on Amazon SageMaker

AWS Machine Learning

Continuous fine-tuning also enables models to integrate human feedback, address errors, and tailor to real-world applications. When you have user feedback to the model responses, you can also use reinforcement learning from human feedback (RLHF) to guide the LLMs response by rewarding the outputs that align with human preferences.

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The Health of the Contact Center: Are You Ready for 2019?

A survey of 1,000 contact center professionals reveals what it takes to improve agent well-being in a customer-centric era. This report is a must-read for contact center leaders preparing to engage agents and improve customer experience in 2019.