Remove Analytics Remove Consumers Remove Government
article thumbnail

3 Challenges Utilities Brands Face When Aligning Strategy, Ops, and Services to CX Needs

InMoment XI

Increased government regulation and new market entrants with unique service-based offerings are creating a disruptive wave of change that traditional utilities need to respond to. Solve the Challenge: Text Analytics to the Rescue. Luckily, text analytics capabilities are getting better and better each year!

Brands 397
article thumbnail

A to Z Guide to Customer Experience Definitions and Terms (Updated)

Lumoa

Long-term actions are based on the analytics results of customer feedback. Both groups of technologies can be utilized to make analytics more actionable. But machine learning technologies can also help you to move from diagnostic to predictive analytics: if I fix this issue in my customer experience, how much will my churn decrease?

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Governing the ML lifecycle at scale, Part 3: Setting up data governance at scale

AWS Machine Learning

This post is part of an ongoing series about governing the machine learning (ML) lifecycle at scale. This post dives deep into how to set up data governance at scale using Amazon DataZone for the data mesh. However, as data volumes and complexity continue to grow, effective data governance becomes a critical challenge.

article thumbnail

Beyond Profit: The Ascendancy of Brand Purpose in B2B

ECXO

They are judging companies on environmental, social, and governance (ESG) claims, and more importantly the action they take. Price and quality matters but consumers and buyers are increasingly making decisions driven by values-based preferences aligned with customer experience. Business customers care about what your brand stands for.

B2B 367
article thumbnail

6 Killer Applications for Artificial Intelligence in the Customer Engagement Contact Center

If Artificial Intelligence for businesses is a red-hot topic in C-suites, AI for customer engagement and contact center customer service is white hot. This white paper covers specific areas in this domain that offer potential for transformational ROI, and a fast, zero-risk way to innovate with AI.

article thumbnail

Improve governance of models with Amazon SageMaker unified Model Cards and Model Registry

AWS Machine Learning

You can now register machine learning (ML) models in Amazon SageMaker Model Registry with Amazon SageMaker Model Cards , making it straightforward to manage governance information for specific model versions directly in SageMaker Model Registry in just a few clicks.

article thumbnail

Governing the ML lifecycle at scale, Part 1: A framework for architecting ML workloads using Amazon SageMaker

AWS Machine Learning

However, implementing security, data privacy, and governance controls are still key challenges faced by customers when implementing ML workloads at scale. Governing ML lifecycle at scale is a framework to help you build an ML platform with embedded security and governance controls based on industry best practices and enterprise standards.