A couple days ago, I read an interesting blog from HBR titled ‘AI with a Human Face’ where the authors described how “All companies want to provide their customers with richer and more engaging experiences. The challenge is how to scale the experiences in a way that does not depersonalize or commodify them.”

Digital Humans

The authors ask the question “What Kind of Digital Human Is Best for You?” They present four categories of digital humans:

  • Virtual agent: A conversational AI that shows the same characteristics towards all users, meaning they are not personalizing the experience on an individual level. However, they can be personalized at the segment level.
  • Virtual assistant: AIs that are programmed to be a virtual assistant are more task oriented, use case-specific and outcome focused. It means they can help customers to complete a transaction or get answers for inquiries.
  • Virtual influencer: This type of conversational AI is like a speaker at a conference, they talk to a wide audience but do not interact with them on an individual basis. They act like a thought leader on a certain topic or product and explain their opinion in a subjective way.
  • Virtual companion: A virtual companion is focused on understanding the deeper context of the conversation, such as emotions and feelings, and is able to demonstrate empathy towards the customer. These AIs are highly personalized by nature and often need to recognize and handle PI data.

Image by HBR via ‘AI with a Human Face’

How Eccentex AI is Used

Eccentex, a leading provider of process automation and case management solutions, leverages AI technologies to enhance and streamline various aspects of core business processes. Here’s how Eccentex uses AI in various case management scenarios:

Intelligent Case Routing

Eccentex uses AI algorithms to analyze case data, including case details, priorities, and historical patterns, to intelligently route cases to the most appropriate agents or departments. AI can help automate the process of case assignment, ensuring that cases reach the right individuals with the necessary expertise, improving efficiency and response times.

Automated Case Classification

AI can be employed to automatically classify incoming cases based on their content and context such as emails, documents, or messages. Natural Language Processing (NLP) technologies can extract key phrases, identify the nature of the case, and assign relevant tags or categories. This enables quicker identification, proper task handling, reduction in manual effort, accuracy improvements and eliminates human errors.

Predictive Analytics for Case Resolution

Eccentex utilizes AI-powered predictive analytics to analyze historical case data and identify patterns that lead to successful case resolutions. Machine learning algorithms can learn from past case outcomes and predict the likelihood of various resolutions or identify optimal next steps. This empowers agents and knowledge workers with in-depth insights to make informed decisions, improve customer satisfaction and reduce resolution times.

Sentiment Analysis

By employing AI technologies in case management, like sentiment analysis, Eccentex can automatically extract key phrases from customer interactions, such as emails, chats, or social media messages, to gauge customer sentiment and emotional states. This helps identify dissatisfied customers or potential issues early on, allowing proactive intervention and better management of customer relationships.

Knowledge Management and Recommendations

Eccentex AI assists knowledge workers by analyzing case histories, agent notes, and resolution patterns to identify and recommend them relevant knowledge articles or resources. This gives agents access to the right information quickly, improving accuracy in providing solutions, and ensures high quality service delivery.

Intelligent Case Escalation

Eccentex AI monitors case processes and automatically identifies situations that require escalation. By analyzing case attributes, customer behavior, and predefined rules, AI can trigger alerts and notifications to supervisors or designated individuals, ensuring timely intervention in critical cases.

Continuous Improvement

AI enables Eccentex to analyze large volumes of case data to identify operational inefficiencies, bottlenecks, and areas for improvement. By leveraging machine learning and data analytics techniques, Eccentex users can gain insights into case management processes and optimize them for better performance, cost-effectiveness, and customer satisfaction.

Overall, by incorporating AI capabilities into case management solutions, Eccentex enhances operational efficiency, automates manual tasks, improve decision-making, and provides a more personalized and efficient customer and employee experiences.

David Elgueta – Solutions Specialist