Most companies are trying to accomplish two goals when it comes to customer service. The first is to identify reoccurring issues that have the potential to increase costs and adversely affect overall profitability. The second is to upsell additional products and services every time there’s an opportunity to engage with a customer. Salesforce today announced […]
Most companies are trying to accomplish two goals when it comes to customer service. The first is to identify reoccurring issues that have the potential to increase costs and adversely affect overall profitability. The second is to upsell additional products and services every time there’s an opportunity to engage with a customer.
Salesforce today announced that it is now applying artificial intelligence (AI) in the form of its Einstein software to help companies achieve those two goals using an Einstein Supervisor module to analyze agent productivity and customer satisfaction. Meanwhile, the Einstein Case Management module makes use of machine learning algorithms to automatically classify various types of issues and customer engagements.
Bobby Amezaga, senior director of product marketing for Service Cloud at Salesforce, says the latest edition of the Salesforce Service Cloud employs AI in a way that is designed to transform the customer experience. For example, Einstein can help identify issues that are occurring across multiple call centers faster or areas where upsell offers have been more successful than others.
In general, Amezaga says, the Salesforce approach to AI is aimed at turning every manager and employee into a citizen data scientist.
“What we’re trying to do here is democratize AI for the contact center,” says Amezaga.
As part of that effort, Einstein for Service Cloud can now also be invoked via an Apple iOS device. Support for Google Android devices is currently in beta.
Given the massive amounts of data that Salesforce is able to aggregate in the cloud, it makes sense that its software-as-a-service (SaaS) applications would become a focal point for applying AI. The next issue organizations need to come to terms with is how to apply those insights in a meaningful way across all the business processes that make up an extended enterprise.
Michael Vizard is a seasoned IT journalist, with nearly 30 years of experience writing and editing about enterprise IT issues. He is a contributor to publications including Programmableweb, IT Business Edge, CIOinsight and UBM Tech. He formerly was editorial director for Ziff-Davis Enterprise, where he launched the company’s custom content division, and has also served as editor in chief for CRN and InfoWorld. He also has held editorial positions at PC Week, Computerworld and Digital Review.
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