AWS Machine Learning

AUGUST 2, 2024

Investors and analysts closely watch key metrics like revenue growth, earnings per share, margins, cash flow, and projections to assess performance against peers and industry trends. The initial draft of a large language model (LLM) generated earnings call script can be then refined and customized using feedback from the company’s executives.

Engineering 131

Engineering Scripts Metrics APIs 131

AWS Machine Learning

JANUARY 28, 2025

Rigorous testing allows us to understand an LLMs capabilities, limitations, and potential biases, and provide actionable feedback to identify and mitigate risk. Evaluation algorithm Computes evaluation metrics to model outputs. Different algorithms have different metrics to be specified.

Management 107

Management APIs Engineering Metrics 107

AWS Machine Learning

FEBRUARY 21, 2025

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.

Benchmark 88

Benchmark Metrics Engineering Feedback 88

AWS Machine Learning

NOVEMBER 14, 2024

The DS uses SageMaker Training jobs to generate metrics captured by , selects a candidate model, and registers the model version inside the shared model group in their local model registry. Optionally, this model group can also be shared with their test and production accounts if local account access to model versions is needed.

Government 100

Government Management APIs Accountability 100

AWS Machine Learning

NOVEMBER 15, 2024

For automatic model evaluation jobs, you can either use built-in datasets across three predefined metrics (accuracy, robustness, toxicity) or bring your own datasets. Diverse feedback is also important, so think about implementing human-in-the-loop testing to assess model responses for safety and fairness.

APIs 110

APIs Government Best practices Metrics 110

Calabrio

FEBRUARY 27, 2025

Workforce Management 2025 Call Center Productivity Guide: Must-Have Metrics and Key Success Strategies Share Achieving maximum call center productivity is anything but simple. Revenue per Agent: This metric measures the revenue generated by each agent. For many leaders, it might often feel like a high-wire act.

Call Center 52

Call Center Metrics Gamification Contact Center 52

ProProfs Blog

OCTOBER 25, 2021

Yes, you can collect their feedback on your brand offerings with simple questions like: Are you happy with our products or services? Various customer feedback tools help you track your customers’ pulse consistently. What Is a Customer Feedback Tool. Read more: 12 Channels to Capture Customer Feedback. Here we go!

Feedback 148

Feedback Surveys Enterprise Analytics 148

Call Center Weekly

APRIL 17, 2018

By Dan MacDougall Contact center metrics are developed to measure operational performance (e.g. How do we then collect metrics on customer experience? Direct customer feedback is probably the best method for determining how customer-focused a brand is. They also have the power to take their money somewhere else.

Contact Center 136

Contact Center Metrics Customer Experience Technical Support 136

Callminer

AUGUST 1, 2017

Metrics, Measure, and Monitor – Make sure your metrics and associated goals are clear and concise while aligning with efficiency and effectiveness. Make each metric public and ensure everyone knows why that metric is measured. They don’t do anything else except maybe monitor a few calls and give some feedback.

Contact Center 334

Contact Center Call Center Average Handle Time Real estate 334

AWS Machine Learning

OCTOBER 9, 2024

Amazon Lookout for Metrics is a fully managed service that uses machine learning (ML) to detect anomalies in virtually any time-series business or operational metrics—such as revenue performance, purchase transactions, and customer acquisition and retention rates—with no ML experience required.

Metrics 92

Metrics APIs Engineering Accountability 92

AWS Machine Learning

MAY 3, 2023

One aspect of this data preparation is feature engineering. Feature engineering refers to the process where relevant variables are identified, selected, and manipulated to transform the raw data into more useful and usable forms for use with the ML algorithm used to train a model and perform inference against it.

Engineering 96

Engineering Metrics APIs Big data 96

Callminer

FEBRUARY 4, 2021

Call center managers and supervisors need to train agents on the course of action to take for a vulnerable customer, and they also need to communicate regular feedback to agents to help them get better. Now more than ever, organizations need to actively manage the Average-Speed-of-Answer (ASA) metric. Adrian Travis. Grant Aldrich.

Call Center 345

Call Center Contact Center Finance Consulting 345

Outsource Consultants

FEBRUARY 18, 2025

Negative customer feedback and declining customer satisfaction: The cumulative effect of these issues often manifests as negative reviews, complaints, and a general decline in customer satisfaction scores. Proactive quality control is the engine that powers this positive cycle. Tie rewards to specific, measurable quality metrics.

Feedback 67

Feedback Customer centricity Best practices Engineering 67

AWS Machine Learning

MARCH 25, 2025

The ability to quickly retrieve and analyze session data empowers developers to optimize their applications based on actual usage patterns and performance metrics. Try out the Session Management APIs for your own use case, and share your feedback in the comments. Aniketh Manjunath is a Software Development Engineer at Amazon Bedrock.

APIs 116

APIs Management Government Healthcare 116

AWS Machine Learning

MARCH 27, 2025

This requirement translates into time and effort investment of trained personnel, who could be support engineers or other technical staff, to review tens of thousands of support cases to arrive at an even distribution of 3,000 per category. If the use case doesnt yield discrete outputs, task-specific metrics are more appropriate.

Education 109

Education Engineering APIs Enterprise 109

CCNG

JUNE 14, 2023

Actively listening to customer feedback and observing their behavior can provide valuable insights into their emotional needs and help you tailor your products, services, and communication strategies accordingly. How to Build Your Customer-Driven Growth Engine , "Competency #1 is to Honor and Manage Customers as Assets".

Customer Experience 195

Customer Experience Airlines CCNG Chief Customer Officer 195

AWS Machine Learning

MARCH 25, 2025

Automated safety guards Integrated Amazon CloudWatch alarms monitor metrics on an inference component. AlarmName This CloudWatch alarm is configured to monitor metrics on an InferenceComponent. Andrew Smith is a Cloud Support Engineer in the SageMaker, Vision & Other team at AWS, based in Sydney, Australia.

APIs 106

APIs Engineering Accountability Metrics 106

Connect

APRIL 14, 2025

AI-based decisioning engines field and prioritise inbound calls, allocating basic engagements and repetitive tasks to automated AI solutions like chatbots or virtual assistants. This continuous feedback loop allows contact centres to constantly refine their operations and improve efficiency. AIs indirect cost benefits.

Average Handle Time 66

Average Handle Time Chatbots First call resolution Cloud contact 66

Lumoa

FEBRUARY 28, 2023

No matter what industry you’re in, your customers are eager and encouraged to share their feedback: the good, the bad, and the ugly. You’ll be richly rewarded: 78% of customers have a more favorable view of brands that ask for feedback. Strategically reacting to customer feedback can increase customer loyalty and retention.

Feedback 78

Feedback Surveys Metrics Customer Experience 78

ChurnZero

APRIL 25, 2025

Choose the right metrics to inform your forecasting model. Focus on collecting and tracking the metrics that are most meaningful to your teams retention strategy. With metrics in hand, its time to start pulling out the trends, themes, and stories behind the numbers. Collecting the right historical data is key.

Finance 52

Finance Metrics Engineering Construction 52

Win the Customer

JANUARY 2, 2025

Leading Cross-Functional Teams: Assembling the Right Team: Product managers will need to lead cross-functional teams with diverse expertise, including data scientists, AI engineers, UX/UI designers, and customer success managers. Continuous Improvement: AI models require continuous monitoring and optimization.

Management 59

Management Metrics Chatbots Engineering 59

TeleDirect

DECEMBER 20, 2024

Use surveys, feedback forms, and analytics to understand your audience better. Measure and Optimize Consistently measure CX performance using metrics like Net Promoter Score (NPS), Customer Satisfaction (CSAT), and Customer Effort Score (CES). Q: What metrics should businesses use to measure CX?

Customer Experience 62

Customer Experience Journey mapping Call Center Chatbots 62

REVE Chat Blog

MARCH 18, 2020

Building a good chatbot is a daunting task but at the same time, it is important to understand the key chatbot metrics and how they are performing to achieve your goals. Information is the oil of the 21st century, and analytics is the combustion engine”. Chatbot analytics: User metrics. Why chatbot analytics matter? .

Chatbots 81

Chatbots Metrics Analytics Banking 81

CSM Magazine

APRIL 22, 2025

For example, a 2002 GitLab survey has shown that 82% of remote engineers name communication as the most challenging part of their work. According to the experienced engineers, among the most efficient and effective methods of process control are: Precise meeting adjustments.

Morale 52

Morale Best practices Engineering outsourcing 52

AWS Machine Learning

FEBRUARY 5, 2025

There is consistent customer feedback that AI assistants are the most useful when users can interface with them within the productivity tools they already use on a daily basis, to avoid switching applications and context. For Slack, we are collecting user feedback, as shown in the preceding screenshot of the UI.

Engineering 70

Engineering Feedback Analytics Education 70

AWS Machine Learning

SEPTEMBER 6, 2024

This post focuses on evaluating and interpreting metrics using FMEval for question answering in a generative AI application. FMEval is a comprehensive evaluation suite from Amazon SageMaker Clarify , providing standardized implementations of metrics to assess quality and responsibility. Question Answer Fact Who is Andrew R.

Best practices 92

Best practices Metrics Sales Benchmark 92

AWS Machine Learning

NOVEMBER 7, 2024

Prompt engineering is typically an iterative process, and teams experiment with different techniques and prompt structures until they reach their target outcomes. Model monitoring – The model monitoring service allows tenants to evaluate model performance against predefined metrics. They’re illustrated in the following figure.

Enterprise 112

Enterprise APIs Government Accountability 112

REVE Chat Blog

MARCH 18, 2020

Building a good chatbot is a daunting task but at the same time, it is important to understand the key chatbot metrics and how they are performing to achieve your goals. Information is the oil of the 21st century, and analytics is the combustion engine”. Chatbot analytics: User metrics. Why chatbot analytics matter? .

Chatbots 77

Chatbots Metrics Analytics Banking 77

CSM Magazine

MAY 19, 2023

Customer Experience Engineering (CXE) is a growing field that focuses on designing, managing, and improving the interactions between a company and its customers. At its core, customer experience engineering seeks to ensure that every touchpoint a customer has with a company leaves a positive and lasting impression.

Engineering 52

Engineering Customer Experience Journey mapping CRM 52

SharpenCX

MARCH 4, 2020

And, they cram months (and months) of feedback into a single coaching session. But given how our memories work, coaching in spurts and keeping feedback in your back pocket won’t lead to better performance. And, they give feedback that optimizes agent strengths and improves team effectiveness.

Call Center 84

Call Center Feedback Coaching Average Handle Time 84

AWS Machine Learning

DECEMBER 22, 2023

TruLens evaluations use an abstraction of feedback functions. Although new components have worked their way into the compute layer (fine-tuning, prompt engineering, model APIs) and storage layer (vector databases), the need for observability remains.

Feedback 118

Feedback Engineering Metrics APIs 118

AWS Machine Learning

AUGUST 26, 2024

Built on AWS with asynchronous processing, the solution incorporates multiple quality assurance measures and is continually refined through a comprehensive feedback loop, all while maintaining stringent security and privacy standards. As new models become available on Amazon Bedrock, we have a structured evaluation process in place.

Sales 126

Sales Accountability Feedback Metrics 126

GetFeedback

JANUARY 19, 2020

As my trip progressed, I got email requests for feedback at each step. If I just wanted to give feedback to Expedia or the hotel, I’d probably drop out at this point. . Key point : Feedback surveys have to be thoughtfully designed into each touchpoint, in terms of the channel, timing, and survey questions. .

Surveys 146

Surveys Journey mapping Feedback B2B 146

GetFeedback

MAY 9, 2019

F or CXM to be successful, you need two components: real-time feedback (across the entire customer journey) and data analytics to close the gap between what customers expect and their perception of the experience that is currently being delivered. From this feedback, you can identify trends and opportunities to improve customer experience.

Customer Experience 134

Customer Experience Journey mapping Metrics Customer centricity 134

AWS Machine Learning

JUNE 20, 2024

Additionally, evaluation can identify potential biases, hallucinations, inconsistencies, or factual errors that may arise from the integration of external sources or from sub-optimal prompt engineering. This makes it difficult to apply standard evaluation metrics like BERTScore ( Zhang et al.

Metrics 136

Metrics Engineering Accountability Benchmark 136

AWS Machine Learning

OCTOBER 2, 2024

This is often referred to as platform engineering and can be neatly summarized by the mantra “You (the developer) build and test, and we (the platform engineering team) do all the rest!” Amazon Bedrock is compatible with robust observability features to monitor and manage ML models and applications.

Government 125

Government APIs Enterprise Best practices 125