Microsoft provides a preview environment for Dynamics 365 AI for Customer Service. Especially for this purpose, Microsoft has created an AI for Customer Service Landing Page for requesting this preview environment. The requirement for testing the environment is an e-mail address that is linked to a Microsoft work account. Microsoft's AI offensive is now picking up speed and should keep the competition on their toes. Recently we wrote an article about Microsoft Dynamics 365 AI for Sales. In this article you can read how to deploy the new AI features on your CRM instance.

The new application is designed to provide new insights about the health of your service desk with the help of artificial intelligence, or to identify trends in support requests. Service managers should be encouraged to take a proactive approach supported by data-driven decision proposals. This means, for example, automatically categorizing requests based on the words used in the problem description instead of being manually assigned by the service team employee. This makes new insights immediately available so that growing problems can be identified before they reach critical levels.

Dashboard for KPI's in AI for Customer Service

The Key Performance Indicator (KPI) Summary Dashboard provides an overview of the organization's past support requests with performance trends and highlights key request topics.

AI for Customer Service

The KPI Dashboard contains among other features:

  • A summary of the most important KPI's: total number of requests, number of resolved requests, number of escalations, SLA compliance and average processing time.
  • Distribution of requests between new requests and the backlog for a certain period.
  • Division of the communication channels through which the requests are received.
  • Number of new and resolved requests for a specific period.
  • Number of unresolved requests sorted by age in days.

Dashboard for incoming requests in AI for Customer Service

This dashboard contains views of your organization's current support cases with AI-based tables to show sustained support topics or topics rising in trends. The data can be displayed for all requests, or sorted by product, channel, and team.

AI for Customer Service

The "Popular Topics" table shows how artificial intelligence works in action. The topics are not manually entered by a support employee but are the result of an analysis of similar sounding support requests.

The table sorts the queries by the largest volume in percent:

AI for Customer Service

The "Emerging Topics" table shows the topics that have experienced the biggest growth. The table is intended to identify critical topics at an earlier stage and not when they have already reached a critical share of the total volume.

AI for Customer Service

Dashboard for customer satisfaction in AI for Customer Service

This dashboard gives you an overview of customer satisfaction, sorted by topics that have the most impact on customer satisfaction (CAST). For example, you can see through which channels customer satisfaction is highest - or lowest.

AI for Customer Service

Dashboard for processing time of requests in AI for Customer Service

Here, service managers can see which topics have the greatest negative impact on the average processing time.

AI for Customer Service

For example, the marked request shows a common problem with a coupon code. The request has a high average processing time and has, due to the high volume, a high negative influence on the average processing time of all support requests.

If you take a look at the individual evaluation of the topic, you will get information such as:

  • How many requests are related to this topic?
  • How many of these have been resolved?
  • Who has the most unresolved issues related to the topic?
  • Who has the highest average processing time associated with the topic?

AI for Customer Service

Get Familiar with the new AI features of Dynamics 365

We strongly recommend everyone to get familiar with the new AI features from Microsoft. The dashboards are visually appealing and increase the efficiency of data analysis enormously. Manual activities are eliminated and complemented with the help of artificial intelligence. In the future we certainly have a lot to expect from Microsoft regarding artificial intelligence and machine learning.