At DreamForce, Salesforce Shows Its Acquisitions Are Paying Off

SAN FRANCISCO — Salesforce.com kicked off its annual Dreamforce user conference earlier this week by introducing the next generation of its Customer Success Platform, including the release of Quip to supercharge productivity; Salesforce Einstein to make every customer interaction smarter; and advancements in the Salesforce1 Mobile App, Salesforce Platform, and IoT Cloud.

Alex Dayon, president and chief product officer at Salesforce, called these products examples of Salesforce’s “unprecedented innovation,” noting that they deliver “new levels of intelligence, speed, mobility, productivity, and connectivity across the Salesforce Customer Success Platform."

Amid all the new releases, most of the attention was on Einstein, Salesforce’s new artificial intelligence (AI) capability. With Einstein, Salesforce is embedding AI into just about every piece of the Salesforce platform, enabling users to get closer to their customers, discover relevant insights, predict future behavior, proactively recommend best next actions, and even automating tasks.

Einstein can leverage the data in Salesforce—customer data; activity data from Chatter, email, calendar and ecommerce; social data streams such as tweets and images; and even IoT signals—from participating customers to train predictive models. Those AI predictive models can be customized automatically for individual customers, and they learn, self-tune, and get smarter based on every relevant interaction and additional piece of data.

Marc Benioff, Salesforce’s chairman and CEO, said in his keynote Oct. 4 that the world is “on the march toward AI” and, as a result, he expects Einstein to eventually play a role in everything Salesforce does.

Parker Harris, Salesforce’s chief technology officer and cofounder, touted Einstein’s ability to quickly capture and analyze data, saying companies will be able to use it to “change the way they do business forever.”

Einstein is being incorporated into all eight of Salesforce’s cloud platforms (covering sales, service, marketing, commerce, communities, analytics, IoT and app development), so expectations are naturally very high.

Scott Horn, chief marketing officer at [24]7, a customer engagement solutions provider, posits that the launch of Einstein means that AI is no longer a novelty but is poised to become a key part of mainstream business workflows.

“From better purchase recommendations, to smarter customer service that predicts what a consumer is actually trying to do, AI promises to fundamentally transform entire businesses and industries,” he says. “Einstein is a sign of the true potential of AI—as a supplement to human intuition. By turning cold-calling into warm-calling, this is an opportunity for artificial intelligence to prove itself as a truly productive counterpart to the human mind.

“And the applications for this technology go well beyond sales. AI is bringing automation to customer service, which will bring major benefits to consumers. For the first time, businesses can now understand and act on consumer intent, meaning that consumers will no longer have to repeat information or be bombarded with irrelevant information.”

Shawn Belling, vice president of product development at CloudCraze, provider of a B2B commerce solution native to Salesforce, calls Einstein “groundbreaking new technology.”

“The move toward AI-enabled CRM affects how decisions are made within organizations and how to sell. Instead of focusing efforts around selling to a single decision maker in a company, AI can analyze CRM data to equip businesses with the tools to personalize messages to multiple decision makers in real time,” he says. “This adds overall value to customers by enhancing efficiency and driving revenue through better business processes and available insights.”

Predrag Jakovljevic, principal analyst at Technology Evaluation Center (TEC), believes Einstein “should eventually be a powerful, pervasive AI layer within the Salesforce Customer Engagement platform.”

“It can be used in sales to make recommendations on what leads to follow, in service to recommend to an agent a next-best-action, in marketing to determine what marketing content to display to the customer and what actions to take based on customer behavior, and in commerce to determine what personalized items to display to the customer, how to follow up a cart abandonment, etc.,” he says.

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