Salesforce announced today a new search tool for its Customer Relationship Management (CRM) software. Enterprise customers will run more than one billion searches a month with Einstein Search, giving it the potential to increase user productivity by 50%, said Will Breetz, vice president of product for search at Salesforce.

CRM software works with an organization’s interactions with current and potential employers. CRM systems can be used across a variety of industries including customer service, sales, business development, marketing, recruiting, or any business that relies on external customer interactions.

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Enterprise search engines have previously lagged in the following three key areas, Breetz noted:

1. Diverse user base with a diverse set of goals

When customers use search bars on ecommerce sites, they are always searching for items to purchase. “But with enterprise search users have such divergent goals that you can’t make those sort of assumptions,” Breetz said. “People on your sales, service, and marketing teams (not to mention everyone else in the organization) are trying to accomplish very different things. Historically it’s been difficult to tailor search to all these divergent needs with one tool.”

2. Siloed and dissimilar data

“In consumer search, the company building the Search feature usually owns the data (or it’s public data), so they can create one single consistent data structure and optimize it for Search,” Breetz said. “But in the enterprise, you can have tens or hundreds of thousands of customers all customizing their data model in different ways depending on their business. And then of course the data is siloed across customers, so you can’t benefit from the wisdom of the crowds like in consumer search.”

3. Data privacy has limited the progress of enterprise search engines

Enterprise search engines must keep customer data secure, meaning CRM providers can’t necessarily follow typical machine learning practices. Salesforce keeps customers’ data secure, “because of this, we can’t and don’t look at customer data, meaning we can’t rely on traditional machine learning techniques,” Breetz said.

Einstein Search claims to overcome all of those problems, starting with personalized results. Every search in Einstein Search is personalized to each user, using advanced data mining and machine learning techniques, while also anonymizing user information.

Einstein Search will make searching within a CRM system a seamless as searching on Google, as noted in the press release. This search engine is able to process natural language queries such as “my open opportunities in New York,” making the search faster and simpler.

These updates have the potential to reduce clicks and page loads by 50% on frequently-accessed tasks. The tool shows relevant information, with customizable actions in the search results, reducing multiple manual clicks down to one search.

“If a user does a search for an account, we’ll use personalization to put the right accounts for them at the top of the search results, leveraging things like their preferred account geography, account industry, etc.” Breetz said. “That alone will save them time versus them having to scroll through long lists of results to find the result they want.”

The Einstein Search will be available to the public next year, but is currently in the pilot stages. Sign up for the pilot program here.

For more, check out Salesforce talks about its Einstein Analytics product for financial services and new tools to combat AI bias on TechRepublic.

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