This site uses cookies to improve your experience. To help us insure we adhere to various privacy regulations, please select your country/region of residence. If you do not select a country, we will assume you are from the United States. Select your Cookie Settings or view our Privacy Policy and Terms of Use.
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Used for the proper function of the website
Used for monitoring website traffic and interactions
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Strictly Necessary: Used for the proper function of the website
Performance/Analytics: Used for monitoring website traffic and interactions
This post explores the new enterprise-grade features for KnowledgeBases on Amazon Bedrock and how they align with the AWS Well-Architected Framework. AWS Well-Architected design principles RAG-based applications built using KnowledgeBases for Amazon Bedrock can greatly benefit from following the AWS Well-Architected Framework.
Amazon Bedrock empowers teams to generate Terraform and CloudFormation scripts that are custom fitted to organizational needs while seamlessly integrating compliance and security best practices. Traditionally, cloud engineers learning IaC would manually sift through documentation and best practices to write compliant IaC scripts.
Bill Dettering is the CEO and Founder of Zingtree , a SaaS solution for building interactive decision trees and agent scripts for contact centers (and many other industries). Interactive agent scripts from Zingtree solve this problem. Agents can also send feedback directly to script authors to further improve processes.
This solution uses Retrieval Augmented Generation (RAG) to ensure the generated scripts adhere to organizational needs and industrystandards. In this blog post, we explore how Agents for Amazon Bedrock can be used to generate customized, organization standards-compliant IaC scripts directly from uploaded architecture diagrams.
However, according to the most recent available data , the AHT industrystandard or average is about 6 minutes and 3 seconds. For example, you can leverage AI to score your calls based on relevant metrics such as resolution rate or AHT. Setting an Average Handle Time Benchmark: What is a Good AHT?
To boost FCR rates, call centers should: Invest in comprehensive agent training Develop robust knowledgebases Implement effective call routing systems Regular quality assurance checks and feedback loops help identify common issues that prevent first-call resolution.
The correlation is straightforward: the better your knowledgebases, the faster agents can find the answers and information they need, resulting in quicker calls and reduced AHT. For example, companies like Zapier and Shopify have extensive Help Center knowledgebases. Review the sentiment of your scripts.
Tools and resources to help agents succeed include knowledgebases and scripts. Data Security and Compliance Protecting customer data and adhering to industry regulations is non-negotiable. Provide Detailed Training and Guidelines Offer the call center agents comprehensive training materials, guidelines, and scripts.
With KnowledgeBases for Amazon Bedrock , you can give FMs and agents contextual information from your company’s private data sources for RAG to deliver more relevant, accurate, and customized responses. Knowledgebase responses come with source citations to improve transparency and minimize hallucinations.
Generate Agent Scripts With generative AI, you can easily draft and fine-tune agent scripts for different customer interactions. You can also use generative AI to create internal knowledgebases for your agents to develop their skills and recall information when required. . Share transcripts showcasing this tactic.”
It’s not just about the tools or scripts, it’s about the environment, empowerment, and encouragement agents receive. KnowledgeBase Accuracy: Regularly update the knowledgebase with the latest product or service information and establish a feedback mechanism for agents to suggest improvements or additions.
However, the standard AHT for a call center is typically considered to be about five to seven minutes. As per Call Centre Magazine , the industry-standard AHT is six minutes and ten seconds. Also, use standardized call center scripts and templates for common customer queries and issues.
Benchmark Your Metrics Against IndustryStandards How do you know if your contact center metrics are strong? Compare them against industrystandards. Steps to Benchmark Effectively: Research benchmarks for critical metrics like FCR, AHT, and CSAT in your industry. Set realistic improvement goals.
Benchmark Your Metrics Against IndustryStandards How do you know if your contact center metrics are strong? Compare them against industrystandards. Steps to Benchmark Effectively: Research benchmarks for critical metrics like FCR, AHT, and CSAT in your industry. Set realistic improvement goals.
Tools and resources to help agents succeed include knowledgebases and scripts. Data Security and Compliance Protecting customer data and adhering to industry regulations is non-negotiable. Provide Detailed Training and Guidelines Offer the call center agents comprehensive training materials, guidelines, and scripts.
To optimize ATT, call centers employ various strategies, such as agent training programs, call scripting, and technological tools, to strike the right balance between service quality and efficiency. For reference, according to callcenterhelper.com , the industrystandard for Average Handling Time (AHT) is 6 minutes and 10 seconds.
We asked respondents to rank how often they use the following tools today, and how they expect them to be used ten years from now: Voice (phone) assistance IVR (Interactive Voice Response) assistance Online chat bot Live chat with a human Self-service knowledgebase Discussion forums Social media Email Text Mobile app. 10 Year Rank.
You can create self-service menus, instant messaging-based self-services (like WhatsApp or SMS), a knowledgebase, voice assistants, etc., Look at the product from the customers’ point of view to better model your contact center scripts. to get the job done. How will this product improve their quality of life?
This review can include: – Security Flaws : Auditors look for vulnerabilities such as SQL injections, cross-site scripting (XSS), and improper authentication processes. – Adherence to Best Practices : Ensuring the code follows industrystandards for readability, consistency, and scalability.
We organize all of the trending information in your field so you don't have to. Join 34,000+ users and stay up to date on the latest articles your peers are reading.
You know about us, now we want to get to know you!
Let's personalize your content
Let's get even more personalized
We recognize your account from another site in our network, please click 'Send Email' below to continue with verifying your account and setting a password.
Let's personalize your content