Salesforce Unveils 'Einstein' - AI Platform To Enhance Customer Relationship Management

Sep 21, 2016, 01:19
Salesforce Unveils 'Einstein' - AI Platform To Enhance Customer Relationship Management

Community Cloud: Recommended Experts, Articles, and Topics; Automated Service Escalation; Newsfeed Insights to highlight the predicted most relevant content. The company will discuss about the new software in its next month-scheduled annual user conference in San Francisco. 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. Founded by former Oracle executive Marc Benioff, the company signed a 9-year partnership with Oracle in 2013 to use Oracle Linux, Oracle Exadata, Oracle Database, and the Java platform to power its applications and SaaS platform. When it announced an Internet of Things cloud last year - when IoT was itself flavor the year - it caused some raised eyebrows, but Salesforce recognized that devices and sensors would be giving signals that its users could collect to understand customers and markets better. According to a press release, the group will focus on delivering "cutting-edge, breakthrough AI research across deep learning, natural language processing and computer vision to Salesforce's product and engineering teams".

The Commerce Cloud now features personalized product recommendations; a predictive sort capability, which delivers personalized sort and search results based on likelihood of engagement; and the commerce insights tool, which utilizes product purchase correlations to assist retailers in merchandising and store planning.

The Salesforce Einstein platform will add analytics and insights to the overall workflow of customers using salesforce products, making it fully automated.

The first, he said, "consists of localized insights based upon Einstein learning from individual companies' data sets".

MetaMind founder and now Salesforce chief scientist Richard Socher is heading up the new research unit.

Predictive Lead Scoring uses lead source techniques to analyse lead data such as standard fields like industry, job title, custom fields, web click and email leads, enabling Einstein's machine learning functions to improve the predictive score so sales staff can hone in on the most important leads. The company employs about 175 data scientists. While we're inching closer to the goal of AI brain mapping, the next era of AI will be more about imbuing the software and applications we use every day with deep learning, machine learning, predictive analytics, and natural language processing (NLP). "There aren't enough data scientists in the world to build models".

Salesforce is trying to embed AI capabilities across every Salesforce Cloud. It will also be providing its customers with predictive vision, sentiment and modeling services that third-party developers can include within their own apps.

Salesforce is betting that a new research arm can grow Einstein features and AI knowledge. An example of this is "Predictive Lead Scoring" which will rank sales leads that has the most potential to turn into a closed deal. "The combination of AI and Salesforce CRM has been a game-changer, empowering our marketing organization to intelligently engage with fans through timely campaigns and relevant recommendations that transform the customer experience". The whole point of Einstein say Salesforce, is to create a layer that enhances the user experience until we eventually reach a point where AI technology is so pervasive that users won't even notice when a feature is powered by AI.

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