Partners Eager To Learn More At Dreamforce About Salesforce's Roadmap For Upgrading Its Einstein Intelligence Platform
At last year's Dreamforce conference, Salesforce introduced partners to Einstein, a broad platform for infusing artificial intelligence across the cloud-computing giant's product portfolio.
Now that Einstein is a year old, partners headed to Dreamforce 2017 next week in San Francisco are eager to learn more about how Salesforce's AI capabilities have matured, and if they will soon see a broader toolset making Einstein a more agile, customizable, and powerful solution to bring to customers.
As market demand for artificial intelligence heats up, Salesforce looks like it will not disappoint. An entire day of Dreamforce, Tuesday is packed with AI and Einstein sessions, and the technology will be a centerpiece of an on-stage discussion Wednesday between Salesforce CEO Marc Benioff and IBM CEO Ginni Rometty.
Solutions architects at SpringML, a Salesforce implementer with a strong focus on machine learning, will be educating peers on how customers are adopting machine learning in the Einstein Theater at Dreamforce, while also hoping to learn more themselves about the direction of Salesforce's intelligence portfolio.
"Beyond just the basic APIs, and the announcements they've made to date, we're looking forward to seeing the depth of their machine learning and AI offering," Charles Landry, CEO of the consultancy based in Pleasanton, Calif., told CRN.
Questions include how Salesforce is making it easier to embed Einstein into core applications, how Einstein solutions will appear on the recently revamped AppExchange marketplace, and how consulting partners will be enabled to leverage the platform to deliver industry-specific solutions.
Landry also wants to hear more about how IBM's Watson cognitive computing platform will integrate with Einstein, a topic that should be discussed in depth by Benioff and Rometty.
Latane Conant, chief marketing officer at Appirio, a Salesforce integrator based in Indianapolis, told CRN that with a day devoted almost exclusively to artificial intelligence, she expects to hear a lot at Dreamforce about Salesforce's evolving capabilities around the technology.
"It's a hot topic right now, and rightly so," Conant said. "AI is going to play a huge role in pushing marketing technology to the next level in creating true one-to-one customer journeys."
Artificial intelligence, of which machine learning is a central component, had a breakout year in 2016, with most major cloud providers innovating and launching products that made major strides in democratizing that long-promised technology.
However, now that Salesforce's solution has spent some time in the hands of real-world customers, partners have a better sense of how Einstein needs to evolve to continue penetrating that market.
"Einstein has come a long way since its release a year ago," said Kai Hsiung, chief growth officer at Silverline, a Salesforce partner based in New York City.
But there's still a lot that can be done to make the solution more valuable to customers, Hsiung said, and he wants to learn more at Dreamforce about coming upgrades, particularly in facilitating sales projections.
"They're going to say Einstein is going to be released with forecasting in the next year," Hsiung said.
The capability would evaluate historical data, apply it to the customer's pipeline, and "spit out a forecast," he said. "It's something I'm looking forward to since everybody struggles with forecasting. That's something that's worthy of talking to the customers about."
Customers, be they media, retail, consumer goods, energy, or tech companies, want to take the data in their CRM and external systems and leverage machine learning to predict sales, Landry, of SpringML, also told CRN.
"You can see the pace of progress really picking up, moving beyond this initial phase of hype and romance with machine learning and into the early days of practical use cases, with the right toolsets to enable it, drive business in marketing, services and sales, or operational capabilities with IoT implementations," Landry said.
Salesforce Service Cloud users are looking to Einstein to help manage and service customers better by delivering predictions on what tickets will be challenging to deal with as opposed to run-of-the-mill, and what cases need to be escalated sooner. On the marketing side, Salesforce's AI technology can be used to analyze campaigns and predict revenue outcomes, evaluate the effectiveness of messaging and integrate that with social channels, Landry said.
In recent months, SpringML has seen several customer engagements to deliver those types of capabilities, Landry said.
But to really tackle the market opportunity, especially across specific verticals, Einstein needs to extend beyond the initial capabilities launched last year with more-prevalent capabilities partners can embed into core applications, Landry said.
"We are expecting, and optimistic, to hear about Einstein capabilities that are customizable to the depths and requirements of the customer," Landry said. "What we're really excited to see are what are the customizable components, and the APIs they're going to release, that enable partners such as ourselves to build custom solutions."
SpringML does a lot of work for the medical device industry, and for those customers, "the generic just won't fit," Landry said. Generic artificial intelligence "just won't serve the customer as well as customized solutions purposed for them to adapt data from their custom objects."
Salesforce partners also tell CRN they are looking to learn more about efforts to accelerate adoption of the Lightning platform for developing next-generation user interfaces because Lightning's development impacts Einstein's market potential.
The Lightning framework was introduced two years ago to make it easier for partners to enhance and customize user interfaces without writing code.
Einstein only works inside Lighting, as Salesforce partner Bluewolf, owned by IBM, explained in a recent blog post.
Most new customers deploy Lightning. But many of the legacy ones still haven't migrated to that user interface, which undercuts their ability to leverage Einstein.
Salesforce's channel has been trying to develop programs to encourage and facilitate migrations, but legacy customers aren't moving as fast as many, including Salesforce, had hoped, mainly because doing so "is more than a weekend effort," one Salesforce partner, who asked not to be named in this article, told CRN.
The time requirements of Lightning migration projects and the inherent disruptions to business as they proceed have slowed the platform refresh.
"You have to answer the Lightning question before you can answer the Einstein question," that partner said.