This week’s annual Dreamforce conference was the coming out party for Salesforce Einstein, the artificial intelligence technology that the company is embedding in customer relationship applications.
Previewed last month, Salesforce Einstein is designed to give users of the company’s cloud CRM platform quick customer insights and predictive capabilities about things like best sales prospects, hottest markets and product sales performance that would normally require a data scientist or a third party program to set up.
“We are in this incredible new world of artificial intelligence where everything is getting smarter,” Salesforce CEO Mark Benioff said in his keynote here October 5. “We can see a world coming where Salesforce has AI built into every core of the platform. We have a hundred of the world’s top AI experts working on this … Our job is to make the complex simple.”
“For companies who aren’t really used to making use of smarter data for sales and marketing decisions Einstein is a great starting point. And the [user interface] is fantastic in part because of the simplicity,” Berkowitz told eWEEK in an email.
“But in other respects there isn’t a lot there. The predictive lead scoring isn’t utilizing a lot of external data sources you’d need to do it in the marketing automation platform and it’s not nearly as sophisticated as standalone solutions,” Berkowitz said.
Salesforce cofounder Parker Harris joined Benioff on stage to elaborate on the work that went into creating Einstein and the importance of it not being a separate product. “We built it into the Salesforce platform with your data, with all the apps you love, Sales Cloud, Service Cloud, Marketing Cloud. With Einstein everyone’s a data scientist.”
He then introduced Shubha Nadar, director of data science at Salesforce, who led the team that developed Einstein.
Nadar said she led a team of only “five people in a basement” at Salesforce working on the project initially. She then walked through a scenario of how a typical user would benefit from Einstein. It starts with Einstein’s ability to gather information from calendars, email, and social networks.
“Before you needed a group of data engineers to gather it all, now you just push a button and Einstein works behind the scenes, learning patterns and making predictions,” she said.
In the demo she showed Einstein surfacing a sales opportunity from the data it collected from an article where a competitor is mentioned. “Einstein found that even though I didn’t mention who my competitors are,” said Nadar.
Einstein also presented someone categorized as a high lead at an electronics enterprise company. “Again, I never told Einstein I sold to electronic enterprise companies, but Einstein figured it out from the data.”
She also noted that Einstein can rank prospects by a lead score based on which ones are most likely to convert to buyers. This helps sales people who otherwise might not have a standard or an efficient way of ranking hundreds of leads. They might for example simply rank them by industry or even alphabetically.
Quip combines documents, spreadsheets, task lists and team chat in one experience that Salesforce calls a “living document.” A new Quip Lightning component is designed to let teams link, access and create Quip documents, spreadsheets and tasks directly from within Salesforce.
The advantage is that rather than sending these documents and files via email, teams can work on these living documents in real time, just as you can in Web-based apps like Google Docs.
“Everyone loves spreadsheets and word processors, but we don’t like emailing them (the related files) around,” said Benioff. “We want to collaborate around spreadsheets and documents.”
Originally published on eWeek
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