In mid-November, Salesforce announced Service Intelligence, a new analytics application for Service Cloud designed to improve agent productivity, cut costs, and improve customer satisfaction.
Service Intelligence is powered by Salesforce's real-time hyperscale data enginePowered by Data Cloud, allowing users to access all data directly in the Service Cloud, without having to switch information between screens.
AI is gaining traction in the service cloud space, with AI adoption increasing by 88% from 2020 to 2022. 63% of service professionals say AI will help them serve their customers faster. By embracing artificial intelligence, service professionals can make informed decisions quickly and improve customer satisfaction, ensuring a competitive advantage.
With AI-driven service intelligence,:Companies can bridge the gap between data and actionto turn raw data into valuable customer insights. This provides service professionals with the right information to achieve their core mission:Deliver exceptional customer experiences.
Senior Vice President, Salesforce Service Cloud.
ryan nichols
Pre-built service dashboards
Service agents can gain AI-driven insights through Einstein Conversation Mining and key metrics across cases, including the total number of escalated cases, average close time, and customer satisfaction scores, to improve customer engagement engagement. Service managers can use pre-built service dashboards to identify and support busy teams.
einstein conversation mining
Use artificial intelligence to analyze customer conversationsso service leaders can quickly identify trends and major customer issues. For example, determine if there are a large number of customers asking questions about the return policy for products. Service agents can train bots to recognize the cause of such issues and provide self-help articles about returns when customers seek support.
Tableau integration
Tableau integration allows users to jump directly from the Service Intelligence dashboard to data exploration in Tableau with a single click, while preserving data from the Service Console. Users can also seamlessly embed visualizations built in Tableau into Service Intelligence to share insights with their teams.
copilot for service
Enable users to ask Einstein questions about their service intelligence dashboards, metrics, trends, and more using natural language directly in Service Cloud.
einstein studio
Provide AI-driven insights such as propensity to escalate customer complaints, and the time it takes to resolve customer cases.
customer effort score
Provide a holistic view of how difficult the customer service experience is, as well as recommendations on how service professionals can adjust interactions to improve customer satisfaction, such as offering discounts to unhappy customers.
Pre-built service dashboards, Einstein Conversation Mining, and Tableau integrations are now generally available.
Einstein Copilot for Service is expected to be piloted in spring 2024.
Einstein Studio, which assesses propensity escalation and customer effort scores, is expected to be fully available in spring 2024.
Material**: Liberty Tribe***