Salesforce updates Sales and Service Cloud with new capabilities

Customer relationship management (CRM) software provider Salesforce on Thursday added new capabilities to its Sales Cloud and Service Cloud with updates to its Einstein AI and Data Cloud offerings.

The updates to Sales Cloud aim to help enterprises make sales calls more productive, and include a generative AI enhancement to Einstein Conversation Insights, Sales Signals, and Einstein Copilot for Sales Actions.

Together, they can help sellers prepare for, conduct, and follow up on customer and prospects calls, the company said.

The generative AI enhancement for Einstein Conversation Insights (ECI) allows enterprises to generate call summaries that users can explore and review using natural language prompts, the company said.

Einstein Conversation Insights already had the ability to transcribe meeting notes, surface insights and action items from individual sales calls, and automatically update CRM systems to eliminate data entry.

The company also added another capability that it calls Sales Signals to the Sales Cloud  to help build a sales pipeline. It unifies data from all customer meetings to identify cross-company and help enterprises adapt their go-to-market strategy accordingly.

Salesforce also said that it is adding a new Einstein Copilot for Sales Actions to the Sales Cloud, which is targeted at making sellers more productive. This will automatically generate prioritized agendas and to-do lists for sellers when they begin their shift, it said. It could even be used to generate information such as summaries of top leads and new accounts, enabling sellers to send personalized follow-up emails to customers and prospects based on call data, Salesforce said.

Updates to Service Cloud

In order to help enterprises engaged in field service, Salesforce is enhancing its Data Cloud offering to deliver new capabilities to its Service Cloud.

One of the new capabilities is the Asset Health Score that uses an integration of real-time data from an asset, such as enterprise resource planning (ERP) or enterprise asset management (EAM) through Data Cloud to calculate an asset’s overall health and performance.

With this feature, field service-oriented enterprises can define a criteria to trigger a workflow when an asset needs attention, the company said, adding that if required the workflow can include a feature to create a work order for a technician to repair the asset.

The Asset Health Score can now also be passed on to technicians via the Field Service Mobile App, which was previewed in April last year.

By looking at the health scores of other assets while they are on site, technicians may also be able to take preventive action, avoiding the need for additional visits, Salesforce said.

Saleforce is also adding the ability to automate the management of asses remotely.

Along with these capabilities, Salesforce is shipping an AI training model inside Service Cloud. This can identify common issues based on current asset data and service history of similar assets and predict when an asset will fail, and why, the company said.

These kind of insights can help enterprises ensure maximum uptime of an asset, increase its lifespan, and drive higher service margins, it said.

Finally, it is adding an analytics tool, Field Service Intelligence, that provides out-of-the-box dashboards to maintain asset-related KPIs. “Plus, since Data Cloud works with any third-party system, companies can make decisions based on a comprehensive and accurate representation of the business,” the company said.

Vector database in Data Cloud becomes generally available

To underpin enterprises’ own AI copilots, Salesforce is finally making generally available the vector database inside Data Cloud that it showcased in December, allowing them to combine structured and unstructured data from multiple locations in a way that AI models can use.

“Integrated into the Einstein 1 Platform, Data Cloud’s vector database ingests, stores, unifies, indexes, and allows semantic queries of unstructured data to take advantage of knowledge across all applications,” the company said in a statement.This enables the company’s copilots to deliver more accurate responses, it added. Potential applications include using the Einstein Copilot to respond to sales calls faster in a personalized manner, and uncovering new sales, service opportunities.