Salesforce ships Artificial Intelligence for CRM

The Service cloud will gain new capabilities such as case classification and predictive close times, while Analytics Cloud and IoT Cloud will gain functionality like predictive analytics, smart data discovery, recommendations and automated rules optimization. AI, and especially math-heavy deep learning, are “too complex for the vast majority”, said Bull. Data science resources are scarce, modeling is hard, and going the “last mile” to surface actual recommendations is especially demanding. Dubbed Salesforce Lightning Bolt, the framework is created to integrate with the company’s existing CRM platform more easily than other frameworks for customer sites. “Companies will be able to leverage Salesforce Bolt solutions to deploy robust, next-generation communities, portals and more with just a few clicks, making it easier than ever to connect with customers in new ways”.

Additionally, a Salesforce Research group is being launched, charged with developing new deep learning, natural language processing and computer vision applications for the company’s products. In the Commerce Cloud it’s doing e-commerce product recommendations and personalized predictive search, meaning product search results modeled off their individual profile.

Salesforce has announced that it has combined artificial intelligence technology in its software for salespeople.

According to Salesforce, developers too will be able to build applications on top of the clouds using their own code or Einstein extensions. Salesforce users will start seeing Einstein panels and pop-ups in their various cloud products. Salesforce’s AI research group will be run by Richard Socher, chief scientist at the company. The other functions include marketing, commerce, community, analytics, IoT and app-building. After acquiring a long list of startups developing cognitive computing or AI technologies and assembling a team of 175 data scientists, it’s ready to demonstrate what Einstein looks like beyond a cartoon version of the world’s most famous German scientist.

The technology draws on recent Salesforce acquisitions including MetaMind.

“The great thing about machine learning is you can actually measure it”, Salesforce’s general manager of Einstein, John Ball, said at a press briefing held last week.

AI techniques such as natural language processing and deep learning already touch many parts of life.

Ball said that Einstein is built into customer success platform “to surface those insights in context for business users”.

Ellison, meanwhile, took a direct shot at Salesforce in June, saying Oracle could become the first cloud company to get to $10 billion in annual revenue, a goal Benioff has made public many years ago. For example, it powers the Predictive Lead Scoring feature, which analyzes industry and engagement information.

Salesforce is betting that a new research arm can grow Einstein features and AI knowledge. Surely, Salesforce is courting developers with predictive vision services, customized projections, sentiment analysis and modeling.

Marketing Cloud Einstein now includes Predictive Scoring which will score every customer’s likelihood to engage with an email, Predictive Audiences which will build custom audience segments based on predicted behaviours and Automated Send-time Optimisation which will predict the optimal time to deliver messages based on past customer behaviour. The news comes at a time of increased interest and efforts to use AI to enhance business applications.

As for Einstein’s initial integrations, they are meant to assist, rather than replace, sales, service, and marketing employees who use Salesforce.

The roles played by Einstein will vary by service, but in most cases the aim is to add predictive and analytics capabilities to existing Salesforce services.