Salesforce Bolsters Einstein AI With Heavy-Duty Data Management

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The rise of artificial intelligence (AI) and Big Data are two sides of the same evolving equation for businesses. In the customer relationship management (CRM) space, that means platforms such as Salesforce are collecting and storing massive amounts of contextual data, and then running all manner of analytics, predictive modeling, and machine learning (ML) algorithms on it to unlock new kinds of business insights.

Today at its Salesforce World Tour stop in New York, the company began to roll back the curtain on how its AI and data layers will work together. Salesforce announced new AI, audience segmentation, and targeting features for Marketing Cloud based on its recent acquisition of data management platform Krux. The company's new Marketing Cloud features, available today, add more data-driven advertising tools and an Einstein Journey Insights dashboard for monitoring end-to-end customer engagement in everything from e-commerce to email marketing.

Salesforce unveiled its Einstein AI platform this year, baking predictive algorithms, machine and deep learning, as well as other data analysis features throughout its Software-as-a-Service (SaaS) cloud. Einstein is essentially an AI layer between the data infrastructure underneath and the Salesforce apps and services on top. The CRM giant is no stranger to big money acquisitions, most recently scooping up Demandware for $2.8 billion and making a play for LinkedIn before Microsoft acquired it. The Krux acquisition gives Salesforce a new, data-driven customer engagement vector.

"We're working to apply AI to all our applications," said Eric Stahl, Senior Vice President of Marketing Cloud. "In Marketing Cloud, Krux now gives us the ability to do things like predictive journeys to help the marketer figure out which products to recommend. We can do complex segmentation, inject audiences into various ad networks, and do large-scale advertising informed by Sales Cloud and Service Cloud data."

As Salesforce and Krux representatives demonstrated Krux and how it fits into the Marketing Cloud, the data management platform acted more like a business intelligence (BI) or data visualization tool than a CRM or marketing platform. Chris O'Hara, head of Global Data Strategy at Krux, talked about the massive quantities of data the platform manages, including an on-demand analytics environment of 20 petabytes (PB)—the entire internet archive is only 15 PB.

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"This is our idea of democratizing data for business users who don't have a PhD in data science," said O'Hara. You can use Krux machine-learned segments to find out something you don't know about your audience, or do a pattern analysis [screenshot above] to understand the attributes of those users that correlate greatly. We're hoping to use those kinds of signals to power Einstein and do things like user scoring and propensity modeling.

The Einstein Journey Insights feature is designed to analyze "hundreds of millions of data points" to identify an optimal customer conversion path. In addition to its Krux-powered Marketing Cloud features, Salesforce also announced a new conversational messaging service called LiveMessage this week for its Salesforce Service Cloud. LiveMessage integrates SMS text and Facebook Messenger with the Service Cloud console for interactions between customers and a company's helpdesk bots.

The more intriguing implications here are what Salesforce might do with massively scaled data infrastructure like Krux beyond the initial integration. According to O'Hara, in addition to its analytics environment, Krux also processes more than more than 5 billion monthly CRM records and 4.5 million data capture events every minute, and maintains a native device graph of more than 3.5 billion active devices and browsers per month. Without getting into specifics, Salesforce's Stahl said there will be far more cross-over between Krux data management and Einstein AI to come. In the data plus AI equation, the potential here is exponential scale.

Article Salesforce Bolsters Einstein AI With Heavy-Duty Data Management compiled by Original article here

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