by twieberneit | Sep 25, 2019 | Analysis, Blog |
The News Last week Salesforce announced Einstein Search, an enhancement of the search mechanisms that are already available in its applications. As usual you can read the announcement online or below. Salesforce wants to release three main issues with Einstein Search: The diverse interests and objective of users of enterprise search make it hard to be as good as a consumer search as delivered by Google or Bing, or the other consumer search engines, especially if in an ecommerce environment. In an enterprise setting, objectives can vary between closing a deal or solving a case, or creating new campaigns. This creates hidden complexities. There are no safe assumptions. Data is residing in different silos and frequently not linked. Further, there is no one size fits it all as Salesforce as an application normally is customized to suit an individual customer’s needs Third, the data simply does not belong to Salesforce, with the consequence that Salesforce cannot look into the data, even not with the objective of improving search. This makes it impossible to use traditional machine learning approaches. As per now Einstein Search is in a private beta stadium with only a few customers using it. General availability is planned for 2020 but limited to customers on Unlimited, Enterprise, or Performance Edition plans with 150 or more active licenses for the Sales or Service Cloud. So far the implementation of Einstein Search covers the top 5 searched objects: accounts, opportunities, contacts, cases and leads, but is intended to support further objects. According to Will Breetz, VP of product management for Einstein Search at Salesforce, Einstein Search is...
