Survey Says… CX AI Models Improve CSAT!

Best Practices

400 CX Leaders Speak Out: Learn the Impact of AI on Quality Management


Customer experience (CX) is changing fast. Artificial Intelligence (AI) is driving this change. Recent advancements in AI have open new possibilities for analyzing customer interactions and deriving valuable insights. In this blog post, we’ll delve into the findings from a recent survey of CX leaders and explore how ElevateAI’s CX AI models can help measure agent behaviors that influence customer satisfaction.

Survey Report Overview

Global Surveyz Research Company conducted the survey, which included 400 senior decision-makers from various industries in Customer Care, Customer Service, or Contact Center departments. These respondents, based in the United States and the United Kingdom, represent companies with contact centers of over 200 agents. The survey was conducted online in December 2022, with an average completion time of just over 5 minutes. You can read the full survey report here.

Key Findings

Inadequate Sampling

First off, the survey unveiled a startling fact: 65% of contact centers base critical decisions on skewed or random data. Now, let’s put this into perspective. The average contact center measures 13 voice and 6 digital interactions monthly. Given the size of these centers (over 200 agents), this sample size is statistically insignificant. It doesn’t truly represent agent performance. This lack of a statistically significant or holistic view is a real cause for concern, especially when you consider that 85% of stakeholders use this data to make critical business decisions.

The Trust Deficit

Next up, we have the issue of trust. Agents need feedback that’s accurate and relevant. Without it, they feel the measurements are unfair and often refuse to accept the feedback. The survey showed that 42% of respondents face a significant challenge: agents don’t buy into their current feedback. Why? Well, 38% believe the sample size or random sampling doesn’t truly represent agent performance. This trust deficit drives quality disputes and undermines the effectiveness of performance feedback.

Soft Skills Disconnect

Moving on, let’s talk about soft skills. A whopping 94% of respondents agree on their importance for customer satisfaction. But here’s the twist: only 41% of companies actually measure these skills. The main hurdles? Subjective analysis and lack of operational buy-in. This disconnect between recognizing the importance of soft skills and actually measuring them is a significant gap in current contact center practices.

AI Adoption Surge

Finally, we come to AI adoption. The survey found that almost all respondents either already have or plan to implement an AI-driven quality management solution. And they’re not dragging their feet. Most companies want to get this ball rolling within the next 12 months. A solid 51% feel strongly that this kind of solution will help boost CSAT scores. Plus, 63% of supervisors believe it will provide the objective feedback they’re currently missing.

Revolutionize CX with AI

ElevateAI, brought to life by NICE, is shaking things up in the customer experience world. This innovative solution doesn’t just provide speech-to-text transcription. It goes beyond that, measuring sentiment and purpose-built behavioral scores to enrich any application or data lake. And the best part? It only takes a few lines of code. But don’t mistake this for a generic AI model trained on public “internet data.” Far from it. ElevateAI has been rigorously trained on over 20 years of CX data, labeled by market-leading analytics. This gives it a deep understanding of customer conversations. Want to learn more about how ElevateAI’s sentiment model stands out from the crowd? Check out this link.

CX AI Models Impact CSAT

ElevateAI’s CX AI models are designed to measure agent behaviors that have a proven influence on customer satisfaction. But these models are not just about transcribing speech to text; they go a step further to understand the context and sentiment behind the interactions.

Now, one of the key features of ElevateAI’s CX AI models is their ability to measure soft skills, like empathy. Despite the recognition of the importance of soft skills in customer satisfaction, many companies struggle to measure them due to subjective analysis and lack of operational buy-in. ElevateAI’s AI models can help overcome these challenges by providing objective and consistent measurements of soft skills.

But wait, there’s more. Another key feature of ElevateAI’s CX AI models is their ability to provide a holistic view of agent performance. Instead of relying on skewed or random samples, these models can analyze 100% of interactions, providing a comprehensive and representative view of agent performance. This can help address the trust deficit among agents and increase their acceptance of performance feedback.

And the best part? ElevateAI’s CX AI models are also designed to be integrated into any application or data lake with just a few lines of code. This makes it easy for companies to adopt these models and start benefiting from AI-driven quality management.

For a deeper understanding of how these models work, you can check out this tutorial on understanding customer-agent behavior with CX AI.


The survey underscores pressing challenges in the contact center industry: inadequate sampling, agent trust deficit, soft skills measurement disconnect, and the AI adoption wave. ElevateAI’s CX AI models are the answer. They offer precise, objective measurements of agent behaviors, driving customer satisfaction.

ElevateAI isn’t just about improving performance—it’s about transforming your contact center. It’s about boosting your CSAT scores and gaining a competitive edge. Your journey to superior customer experience starts with ElevateAI.

Visit today.

ElevateAI Upgrades Free Pla...
The Importance of Regularly...

Related Posts