Einstein for Service: 4 New Salesforce Einstein Features for Service Cloud

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Service Cloud is being bolstered yet again to further ingrain Einstein AI capabilities into the product – a next generation of Service Cloud Einstein, if you like. Salesforce have the figures to prove their move: the Salesforce “State of Service” report surveyed over 1,900 industry leaders, with a high proportion (88%) of ‘high-performing’ organisations committing significant investment towards service over the following year.

What’s next for AI-powered Service Cloud? Salesforce have coined the term: “Proactive Service”, with the pumped-up Einstein for Service offering positioned to deliver this transformation.

Einstein for Service will bring a number of new features, that can be added to existing Service Cloud deployments. The move makes intelligent customer service evermore accessible to enterprises, the new features include:

  • Einstein Case Routing
  • Einstein Article Recommendations
  • Einstein Reply
  • Einstein Next Best Action

Einstein Case Routing

The Case Comes In

Directs cases to the best-suited queue or agent, able to cater to more complex routing than previously possible; factors such as agent skill-set and past resolution success rates are considered for precise case assignment – including factors not visible to the ‘naked eye’.

Benefit from optimal agent-case match, leading to faster resolution time. Consider it a weight off everyone’s shoulders knowing that routing is continuously optimised despite your diversifying product portfolio, team changes, or simply increasing customer expectations – all without admin intervention.

Einstein Reply

The Case Gets Actioned

We shouldn’t side-step the human element in Customer Service, especially when it comes to receiving customer requests written in free-form text; after all, shouldn’t customers be able to communicate naturally with your brand?

Einstein uses Machine Learning to constantly learn from every interaction your service teams have. What did they do resolve the case faster? What did they say in response to specific enquiries?

Crunching all of these interactions, Einstein can recommended replies by using natural language processing (NLP) to decode the content of the customer request. Einstein also has the ability to be very specific, tailoring suggestions based on the conversation and customer context.

Einstein Article Recommendations

The Case Gets Explained

The Einstein learnings aren’t just limited to replies. What Einstein’s Machine Learning discovers can be applied to other service scenarios: take knowledge article recommendations, for instance.

You may have seen this in play on Salesforce’s own customer support hub, where ‘Blaze’ appears with a number of suitable knowledge articles. By identifying the best knowledge article, customers can self-service more effectively, being able to locate the information they need faster, without trawling through your knowledge base or searching multiple keywords.

Einstein Next Best Action

The Case Goes Further

Using a magic combination of business rules (set by a human) and predictive intelligence (the workings of Salesforce Einstein), a next best action, when recommended to agents in ‘the heat of the moment’, can deliver maximum impact when the case reaches critical checkpoints. An example could be at the point of case resolution, to suggest a relevant cross-sell opportunity, such as an extended warranty.

Quip for Service

The Case Needs Backup

A bonus – in addition to the 4 Einstein-branded features, Salesforce also announced that Quip is now embedded within Service Cloud. Quip for Service will place the Quip collaboration platform directly into the case object, for when a case needs backup from multiple agents, also known as ‘swarming’. Quip templates can be accessed by agents to communicate efficiently with customers. In less high-pressure moments, Quip for Service can also be effectively used for discussing and editing knowledge articles.

Quick Refresher

Here’s a recap of previously existing Service Cloud Einstein features:

  • Einstein Bots: AI-powered chatbots, configured on-platform, that learn from agent feedback to the bot if it has, or hasn’t, got it right.
  • Einstein Case Classification: populate picklist and checkbox field values for new cases based on past data.
  • Lightning Flow for Service: a tool to design and activate automated processes.
  • Einstein Supervisor: predictive analytics for Service Agent Managers.


The 4 new Einstein for Service features mean intelligent customer service is increasingly accessible to service teams; helping the move from case-centric Agents, to customer-centric ambassadors. I predict the benefits would particularly resonate with organisations that have complex or rapidly diversifying product portfolios; for teams with high-turnover or niche-skill sets; or simply to keep up with the raising benchmark in customer service expectations.

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