Document Feedback Scripts 
Fonolo
SEPTEMBER 28, 2022
Every call center knows customer feedback is precious. An after-call survey is a series of questions requesting customer feedback right after an interaction. You might have a carefully crafted questionnaire or script for your after-call survey. Sample After-Call Survey Script. Use this handy sample script as a guide!
Guru
NOVEMBER 1, 2018
you think, "Our documentation has never solved our customer’s issues. Almost immediately, however, you start getting feedback from your team: “This didn’t help me at all.” I’ll turn things around!". You step away from solving tickets, and spend three months re-tooling and re-crafting every knowledge article.
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AWS Machine Learning
DECEMBER 6, 2023
Conversational AI has come a long way in recent years thanks to the rapid developments in generative AI, especially the performance improvements of large language models (LLMs) introduced by training techniques such as instruction fine-tuning and reinforcement learning from human feedback.
Callminer
JANUARY 18, 2021
Encourage agents to cheer up callers with more flexible scripting. “A 2014 survey suggested that 69% of customers feel that their call center experience improves when the customer service agent doesn’t sound as though they are reading from a script. Leverage a quality monitoring program for vital feedback.
AWS Machine Learning
MARCH 27, 2025
Lets say the task at hand is to predict the root cause categories (Customer Education, Feature Request, Software Defect, Documentation Improvement, Security Awareness, and Billing Inquiry) for customer support cases. We suggest consulting LLM prompt engineering documentation such as Anthropic prompt engineering for experiments.
Beyond Philosophy
OCTOBER 22, 2020
We discovered that after placing an order, the insurance company agent would tell the customers, “Your policy documents should be with you within five days.” We had the agents say instead, “Your policy documents will be with you within five days.” ” It was the word “should.”
AWS Machine Learning
JULY 29, 2022
BERT is pre-trained on masking random words in a sentence; in contrast, during Pegasus’s pre-training, sentences are masked from an input document. The model then generates the missing sentences as a single output sequence using all the unmasked sentences as context, creating an executive summary of the document as a result.
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