Intelligence

  • Release version: Xanadu
  • Updated August 1, 2024
  • 3 minutes to read
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    Summary of Intelligence Release version: Xanadu

    The Intelligence solutions for Customer Service Management enhance both agent and customer experiences through machine learning, automation, and natural language processing. These solutions utilize AI frameworks to interpret language and predict case resolutions effectively.

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    Key Features

    • Machine Learning: Assists with case creation, assignment, and resolution.
    • Natural Language Understanding (NLU): Analyzes customer sentiment and interprets intent in interactions, enabling automated request fulfillment.
    • Task Intelligence: Automates routine tasks with capabilities such as language detection and document intelligence, allowing agents to focus on complex cases.
    • Recommended Actions: Displays contextually relevant actions for agents, facilitating quicker customer assistance and issue resolution.
    • Predictive Intelligence: Minimizes data entry for agents by predicting case categories, priorities, and assignments based on minimal input.
    • Guided Decisions: Provides structured troubleshooting guidance through decision trees, enhancing agent efficiency and productivity.

    Key Outcomes

    • Reduces manual errors by standardizing processes.
    • Increases agent productivity with embedded decision trees and relevant actions.
    • Enhances customer satisfaction through consistent agent responses.
    • Improves first contact resolution by directing agents along optimal paths for complex cases.

    Use the Intelligence solutions for the Customer Service Management application to access a set of machine learning frameworks, search and automation functions, and natural language processing to automate and enhance your agent and customer experiences.

    Intelligence solutions

    Intelligence solutions use artificial intelligence (AI) to support machine learning and natural language understanding (NLU) capabilities.

    Artificial intelligence
    Several Customer Service Management applications use an artificial intelligence layer as a framework for machine learning models to interpret language and predict the best resolution for cases. Examples include Predictive Intelligence, Task Intelligence, and Document Intelligence. Artificial intelligence is the foundation of machine learning and natural language understanding frameworks.
    Machine learning
    Machine learning solutions for Customer Service Management help with case creation, case assignment, and case resolution.
    Natural Language Understanding
    Natural Language Understanding helps with features such as sentiment analysis, which analyzes customer interactions for positive, negative, or neutral tone. NLU can also interpret customer intent when interacting with a virtual agent to automatically fulfill requests. For example: a customer asks "I need access to the XYZ environment", and NLU interprets "Grant access" as the intent and "XYZ environment" as the entity.

    Task Intelligence for Customer Service

    The Task Intelligence for Customer Service application offers you several AI capabilities. You can use language detection, record categorization, Sentiment Analysis, and Document Intelligence to automate your routine tasks across a case's life cycle. These capabilities also enable your agents to focus on resolving complex cases.

    To learn more about Task Intelligence, see Task Intelligence for Customer Service.

    Recommended Actions application for Customer Service Management

    By using the Recommended Actions application for Customer Service Management, you can configure and display the relevant, recommended actions for your agents. These actions are based on the context of the record. Your agents can quickly follow these recommended actions to assist customers and to resolve issues.

    The following example shows the recommended actions on the case record. The panel gives the agent options to help the customer with a home loan application, such as getting a credit report, determining eligibility, and gathering documents.

    Figure 1. Recommended Actions contextual side panel
    Recommended Actions dashboard that shows machine learning.

    To learn more about Recommended Actions, see Recommended Actions application.

    Predictive Intelligence for case management

    You can assist your agents when they are creating cases by limiting the amount of information that they have to enter. For example, an agent only has to enter a short description of the case. Based on the information that an agent enters in the short description field, Predictive Intelligence predicts the category, priority, and assignment group, and routes the case to the correct queue.

    To learn more about Predictive Intelligence, see Predictive Intelligence for case management.

    Guided Decisions for Customer Service Management

    You can resolve complex cases faster and more efficiently by guiding your agents through a structured troubleshooting process.

    Guided Decisions is a decision tree authoring and  execution capability in the Customer Service Management application. Use Guided Decisions to guide agents through troubleshooting processes that are based on case context. These processes ask a series of questions and agents provide answers. Based on those answers, agents receive guidance on the next steps to take in the resolution process.

    Guided Decisions can help customer service agents by offering step-by-step dynamic guidance as they work to resolve customer issues. This assistance with case resolution can improve agent productivity and customer satisfaction and can help companies in meeting business outcomes. The key benefits include:
    • Reduce manual errors by setting up standard processes as decision trees.
    • Improve agent productivity by embedding decision trees in recommended actions and playbooks and surfacing relevant actions based on a customer’s situation.
    • Increase customer satisfaction with consistent agent processes and responses.
    • Improve first contact resolution by guiding agents along the optimal path to resolve complex cases.

    To learn more about Guided Decisions, see Configuring Guided Decisions.