If you're a data owner looking for more control over how your data is shared, then you might be interested in the recently announced Salesforce Data Studio. The platform connects data owners with marketers looking to reach new customers or better artificial intelligence (AI)-powered ways to reach existing customers.
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Salesforce Data Studio is a standalone product that falls under the Salesforce Marketing Cloud umbrella. The platform can be purchased solely for the purpose of selling and buying data, or it can be added to the Marketing Cloud for integration with Salesforce tools catered to email marketing, mobile marketing, digital advertising, and social content creation, among other use cases.
Here's how Salesforce Data Studio works: Unlike standard data exchanges in which data is purchased without offering provisioning options for sellers, Salesforce created Salesforce Data Studio to provide publishers with the ability to control specific data attributes and know who is able to buy the data, why the data is being purchased, and the length of time the data remains available for use. Salesforce Data Studio leverages Salesforce Einstein's natural language processing (NLP) to deliver search queries that are more precise and reliant on past searches than a search engine lacking artificial intelligence (AI).
"A concern data owners had was that there was no way to control the data to ensure [the buyer] is not doing anything nefarious," said Raji Bedi, Vice President of Product Management at Salesforce Marketing Cloud. "They want to govern specific uses for that data to have the confidence that it's not being used in ways they don't want."
Salesforce has already enlisted many companies to sell data on the Salesforce Data Studio marketplace, including the following: Bazaarvoice, Digital Trends, Fanserv, Gatehouse Media, H Code Media, Kayak, Leaf Group, Penske Media Corporation, Publishers Clearing House, Ranker, Salary.com, Univision, The Enthusiast Network, and Townsquare Media.
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And The Marketer?
Salesforce hasn't designed Salesforce Data Studio solely for the benefit of the seller. The tool is built to let marketers search for specific audiences and customer profiles that might not exist within their own pools of primary data. Simply plug in the kinds of user information you're hoping to purchase and the tool pulls up insights into the available data sets.
"When we started using second-party data, it was quickly clear that the quality and results were more accurate in some areas to that of the third-party data," said Christy Kazlo, Director of Marketing Technology at Conagra Brands, in a statement. Conagra, which owns and operates Hunt's Tomatoes, used the tool to track down "health-minded cooks on popular recipe sites."
In addition to Conagra, numerous marketers have used Salesforce Data Studio to source data, including Anheuser-Busch, Essence, Heineken, Infectious Media, Keurig, and Super Digital.
"Data marketplaces typically provide opaque access to data," said Bedi. "What our customers desire is the ability to understand the origin, fair rights, and usage of that data. Marketers would prefer to have data with more transparency and a deeper understanding of their audience…this means there's a more targeted reach for marketers and more revenue for data publishers."
More Focused Data
Salesforce has recently emphasized its usage of AI via the Einstein engine to provide marketers with instant access to the highest quality data available. In June, the company launched Einstein Account-Based Marketing (ABM), a marketing automation tool designed to provide business-to-business (B2B) marketers with the ability to identify target accounts, marry data between sales and marketing databases, and execute campaigns to each account's primary decision maker. The tool automatically identifies and labels key accounts, increases or decreases lead scores, and pulls in customer relationship management (CRM) and interaction data to help identify similar accounts.
At the end of last year, Salesforce added new features to Marketing Cloud that let marketers monitor customer engagement across any Software-as-a-Service (SaaS)-based tool, including e-commerce and email marketing. The new features functioned like a business intelligence (BI) or data visualization tool by managing an on-demand analytics environment of 20 petabytes (PB).
Announced in September 2016, Salesforce Einstein leverages deep learning, machine learning (ML), predictive analytics, NLP, and image processing technology to process billions of data points, repetitions, and images to help you improve your workflow. All Salesforce customers gain access to Einstein regardless of app or price tier. So, if you're only using Salesforce as your data source or as your helpdesk tool, then you'll still be able to leverage AI to improve service processes. However, the more data you tie into Salesforce, the more helpful Einstein will be.