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Raise The Bar with Machine Learning for Improved Customer Service

Holly Simmons

For today's executives, machine learning is the latest term to get hyped before slowly becoming a reality. And in fact, the majority of CIOs have now begun to take advantage of this transformational, labor-saving technology for customer service, IT, and other parts of the organization.

More than two-thirds of CIOs believe that decisions made by machines will be more accurate than human-made decisions

The Global CIO Point of View report compiled by ServiceNow notes that 89 percent of organizations are either in the planning stages or are already taking advantage of machine learning. Nearly 90 percent of the CIOs surveyed anticipate that increasing automation will increase the speed and accuracy of decisions, and more than two-thirds believe that decisions made by machines will be more accurate than human-made decisions.

With digital transformation being a top priority on many corporate agendas, IT and customer service are partnering to bring machine learning to real world use to improve the customer experience, to reduce manual work by customer service agents and field service technicians, and to improve the quality of service.

A new report from Accenture found that front-line customer support functions spend up to 12 percent of their time categorizing, prioritizing, and assigning tickets. And 27 percent are weighed down by having to choose from 100+ assignment groups.

Machine Learning Improves Customer and Agent Experiences

Most customers today prefer to help themselves via self-service ... Machine learning simplifies this process for the customer

Most customers today prefer to help themselves via self-service including filing a case or request online. Machine learning simplifies this process for the customer by reducing the number of categories from which to choose. Additionally, because requests are being automatically assigned, response times are faster and fewer calls are required.

For agents, eliminating manual work opens the door to focusing on more strategic work such as helping customers get more out of the products or services they purchased. Assignment errors are reduced thus eliminating unnecessary escalations and shortening the time to case closure. For companies, machine learning not only reduces costs, but also improves agent engagement and satisfaction.

Removing the Hurdles Democratizes Machine Learning

One of the obstacles CIOs face in bringing machine learning into their organization is the high cost of entry. Taking full advantage of machine learning in-house requires data scientists that are costly and in short supply. Only about one in four CIOs report having the staff to properly execute their machine learning strategy. This requires a rethink of the best way to implement machine learning. How can you take advantage of this technology without hiring an army of data scientists?

The good news is that third-party providers are now able to integrate machine learning models into their applications including customer service or CRM systems. Pre-built approaches enable rapid implementation and the ability to see results in less than a day without the need to staff up.

Something as simple as fewer categories and faster case assignment can have a noticeable impact on customer engagement, agent satisfaction, and the bottom line. IT working in harmony with customer service to take advantage of machine learning opens up a new world of possibilities. The hype is high, the rewards are real, and the time is right for organizations to embrace this technology and experience the benefits for themselves.

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Raise The Bar with Machine Learning for Improved Customer Service

Holly Simmons

For today's executives, machine learning is the latest term to get hyped before slowly becoming a reality. And in fact, the majority of CIOs have now begun to take advantage of this transformational, labor-saving technology for customer service, IT, and other parts of the organization.

More than two-thirds of CIOs believe that decisions made by machines will be more accurate than human-made decisions

The Global CIO Point of View report compiled by ServiceNow notes that 89 percent of organizations are either in the planning stages or are already taking advantage of machine learning. Nearly 90 percent of the CIOs surveyed anticipate that increasing automation will increase the speed and accuracy of decisions, and more than two-thirds believe that decisions made by machines will be more accurate than human-made decisions.

With digital transformation being a top priority on many corporate agendas, IT and customer service are partnering to bring machine learning to real world use to improve the customer experience, to reduce manual work by customer service agents and field service technicians, and to improve the quality of service.

A new report from Accenture found that front-line customer support functions spend up to 12 percent of their time categorizing, prioritizing, and assigning tickets. And 27 percent are weighed down by having to choose from 100+ assignment groups.

Machine Learning Improves Customer and Agent Experiences

Most customers today prefer to help themselves via self-service ... Machine learning simplifies this process for the customer

Most customers today prefer to help themselves via self-service including filing a case or request online. Machine learning simplifies this process for the customer by reducing the number of categories from which to choose. Additionally, because requests are being automatically assigned, response times are faster and fewer calls are required.

For agents, eliminating manual work opens the door to focusing on more strategic work such as helping customers get more out of the products or services they purchased. Assignment errors are reduced thus eliminating unnecessary escalations and shortening the time to case closure. For companies, machine learning not only reduces costs, but also improves agent engagement and satisfaction.

Removing the Hurdles Democratizes Machine Learning

One of the obstacles CIOs face in bringing machine learning into their organization is the high cost of entry. Taking full advantage of machine learning in-house requires data scientists that are costly and in short supply. Only about one in four CIOs report having the staff to properly execute their machine learning strategy. This requires a rethink of the best way to implement machine learning. How can you take advantage of this technology without hiring an army of data scientists?

The good news is that third-party providers are now able to integrate machine learning models into their applications including customer service or CRM systems. Pre-built approaches enable rapid implementation and the ability to see results in less than a day without the need to staff up.

Something as simple as fewer categories and faster case assignment can have a noticeable impact on customer engagement, agent satisfaction, and the bottom line. IT working in harmony with customer service to take advantage of machine learning opens up a new world of possibilities. The hype is high, the rewards are real, and the time is right for organizations to embrace this technology and experience the benefits for themselves.

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Industry experts offer predictions on how AI will evolve and impact technology and business in 2025. Part 2 covers the challenges presented by AI, as well as solutions to those problems ...

In the final part of APMdigest's 2025 Predictions Series, industry experts offer predictions on how AI will evolve and impact technology and business in 2025 ...

E-commerce is set to skyrocket with a 9% rise over the next few years ... To thrive in this competitive environment, retailers must identify digital resilience as their top priority. In a world where savvy shoppers expect 24/7 access to online deals and experiences, any unexpected downtime to digital services can lead to significant financial losses, damage to brand reputation, abandoned carts with designer shoes, and additional issues ...

Efficiency is a highly-desirable objective in business ... We're seeing this scenario play out in enterprises around the world as they continue to struggle with infrastructures and remote work models with an eye toward operational efficiencies. In contrast to that goal, a recent Broadcom survey of global IT and network professionals found widespread adoption of these strategies is making the network more complex and hampering observability, leading to uptime, performance and security issues. Let's look more closely at these challenges ...

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The 2025 Catchpoint SRE Report dives into the forces transforming the SRE landscape, exploring both the challenges and opportunities ahead. Let's break down the key findings and what they mean for SRE professionals and the businesses relying on them ...

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The pressure on IT teams has never been greater. As data environments grow increasingly complex, resource shortages are emerging as a major obstacle for IT leaders striving to meet the demands of modern infrastructure management ... According to DataStrike's newly released 2025 Data Infrastructure Survey Report, more than half (54%) of IT leaders cite resource limitations as a top challenge, highlighting a growing trend toward outsourcing as a solution ...

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