Outsource Consultants

JANUARY 16, 2025

Essential Components of a Winning QA Program A comprehensive QA program includes several key elements: Clear Standards and Metrics: Define quality for your organization. Consider both objective and subjective metrics. A financial services company integrated their QA data with customer feedback and operational metrics.

Best practices 67

Best practices Contact Center First call resolution Average Handle Time 67

AWS Machine Learning

APRIL 3, 2023

The database was calibrated and validated using data from more than 400 trials in the region. The parent nodes are field-related parameters (including the day of sowing and area planted), and the child nodes are yield, nitrogen uptake, and nitrogen leaching metrics. The following figure illustrates these metrics.

Calibration 93

Calibration Engineering Scripts Accountability 93

SharpenCX

NOVEMBER 5, 2020

The key metrics you track are objective. Instead, the objective metric is a hard data point you use to quantify pieces of your agent’s performance. Do your agent performance tiles ( like these ) tell you that one agent consistently sits at the bottom of his peer group on important metrics like AHT and FCR? DO calibrate often.

Average Handle Time 67

Average Handle Time Coaching Calibration Feedback 67

NobelBiz

MAY 9, 2023

Every step of the process can be calibrated to minimize the agent’s effort, from dialing the number to logging the call in the CRM. Use Case: The Automatic Preview Dialer is highly versatile, adding time efficiency to complex campaigns where agents need to review client data before the call, take notes, personalize scripts, and so on.

Best practices 98

Best practices Call Center Gamification Contact center software 98

AWS Machine Learning

OCTOBER 19, 2022

Lastly, we compare the classification result with the ground truth labels and compute the evaluation metrics. Because our dataset is imbalanced, we use the evaluation metrics balanced accuracy , Cohen’s Kappa score , F1 score , and ROC AUC , because they take into account the frequency of each class in the data. Balanced accuracy.

APIs 75

APIs Metrics Calibration Accountability 75

Voxjar

MAY 22, 2018

When you experiment with different metrics and track improvement over time, you set yourself up for success. Good parameters are measurable and clearly defined (something you can test through calibration sessions with management, supervisors, and reps – post on this coming soon). Did your rep: Follow the greeting script.

Coaching 45

Coaching Scripts Calibration Telemarketing 45

AWS Machine Learning

APRIL 11, 2023

You can use Spark UIs or CloudWatch instance metrics and logs to calibrate these values over multiple run iterations. In this example pipeline, the PySpark script spark_process.py (as shown in the following code) loads a CSV file from Amazon S3 into a Spark data frame, and saves the data as Parquet back to Amazon S3.

Calibration 85

Calibration Scripts Best practices Engineering 85

Customer Relationship Metrics

JANUARY 11, 2017

The project was designed to use the same data collection method with the same survey script for both contact centers. As the study progressed and agent-level feedback was collected by “Contact Center A”, the results for this metric were dramatic. You know what happens when you don’t have their trust.

Customer Experience 67

Customer Experience Interactive Voice Response Caller satisfaction Calibration 67

AWS Machine Learning

NOVEMBER 29, 2023

Furthermore, these data and metrics must be collected to comply with upcoming regulations. They need evaluation metrics generated by model providers to select the right pre-trained model as a starting point. Evaluating these models allows continuous model improvement, calibration and debugging.

Benchmark 100

Benchmark Metrics Engineering APIs 100

AWS Machine Learning

APRIL 8, 2025

Iteratively refine the code by: Reviewing for accuracy and efficiency Adjusting prompts as needed Incorporating developer input for complex scenarios The result is a tailored script that generates synthetic data entries matching your specific requirements and closely mimicking real-world data in your domain.

Enterprise 96

Enterprise Calibration Accountability Best practices 96