At Dreamforce, Salesforce rolled out a set of Einstein Voice capabilities which will be launching in the coming months. New services include Einstein Call Coaching for sales, Service Cloud Voice, and Einstein Voice Skills for developers and Salesforce admins.
Service Cloud Voice provides an integrated console which unifies, phone, digital channels and CRM data in real-time. The service also performs real-time voice-to-text transcription allowing Einstein to offer recommended responses, support content, and next best actions. Service Cloud Voice will enter its pilot phase in February with a June GA date.
“Voice is a huge shift for the industry and will be as impactful in businesses as it’s been in our homes. With Einstein, Salesforce is bringing the power of voice to every business, giving everyone an intelligent, trusted guide at work.”
Salesforce Chief Product Officer Bret Taylor
During an insurance claims call, for example, Einstein
would recognize the nature of the claim and pull up the policyholder’s coverage
specific to the claim, delivering a faster and superior customer experience.
Next best actions such as additional riders or cross-selling
opportunities are presented to the rep. During its beta, State Farm
closed cases 31% faster.
80% of consumers stated that speed is the most
important element in delivering an “amazing customer experience.”
Finally, the call notes are automatically transcribed
for the rep, allowing him or her to quickly move on to the next support call.
“Einstein is specifically designed for simplicity.
It’s designed for Salesforce Admins or Developers to be able to set up
for a Salesforce user to be able to understand, and, as a result, folks that
use Einstein get real results,” said VP of Einstein Products Marco Casalaina.
“So, how can you become successful with Einstein? It all starts
with a question. You need to formulate a question that makes sense for
Questions could be which opportunities will convert,
which customers will drop, will a researcher engage with my email, or will the
customer buy this item?
Einstein Voice Skills will be in beta in February with
a 2021 general availability. Voice Skills will allow admins and
developers to deploy custom voice apps across the Salesforce Customer 360
Platform. For example, a technician can call up a customer’s service
history while en route.
“Each app is purpose-built for the specific needs and
processes of each role. Plus, admins can also control how the information will
be read back to the user, including the ability to offer next steps or
follow-up tasks within the response, and which channels and devices that the
skill is accessible on, such [as] smart speakers or phones,” said Salesforce.
Salesforce has been teasing voice services since the last Dreamforce when they launched Einstein Voice Assistant which supports routine Salesforce CRM functions such as creating or updating customer records, getting personalized daily briefings, and exploring dashboards. This year, they announced Einstein Call Coaching, Service Cloud Voice for transcription and AI-powered recommendation services, and Einstein Voice Skills.
Einstein Call Coaching is currently in pilot and should be generally available as a Sales Cloud High Velocity Sales (SEP) service in June. Call Coaching utilizes natural language processing against call transcripts. Managers view “insights and trends within conversational data.” NLP tags keywords, alerts managers about spikes in competitor mentions, and monitors pricing discussions and objection handling. Managers can then focus their coaching based upon individual rep needs.
“Companies with dynamic sales coaching programs see
28% higher win rates, unbelievable results. And Einstein call coaching is
your coach. This is an AI feature that can process audio clips to serve
up those key moments for this type of coaching,” said Sarah Patterson, SVP of
Being able to track keywords, discussion topics, and
competitors should prove highly valuable for one-on-one and team coaching
sessions and broader analytics. Sales reps often fail to record
competitor and objection details (or they are trapped in notes). Even
when custom fields are set up to capture these details, they are often weakly
populated. Being able to track objections and competitor discussions provides
improved coaching and product road mapping input. This is far better than
querying sales reps to be told that they lost on price or aren’t sure who won
Product tracking and objections also assist with
gathering early intelligence following a product launch. Are the sales
reps balking at discussing the new offering, unable to handle objections for
which they weren’t trained, or tripping on a missing feature that should have
been included in the MVP?
“You launch a new product, but you have no idea
whether your reps are actually comfortable selling it,” said Patterson.
“Well, now you are getting the insight you need to know if they are.
And if they’re not, you can lean in to guide them, to coach them, to help
them. More than this, you can even customize this to look for things that
matter to your business.”
Call Coaching provides “management-level visibility
into key moments during a sales call” allowing the coach to listen to those
moments and how the rep handled them. Those moments are then immediately
available for one-on-one review or group coaching.
Call Coaching Insights include tabs for objection
mentions, product mentions, talk / listen ratios, and custom topics. For
State Farm Insurance (the Dreamforce demo), this includes life events.
Call Coaching conversation trends help identify market
shifts, opportunities for bundled offerings, and emerging competitors.
“73% of managers spend less than 5% of their time coaching their reps, and we wanted to make the most of that time. Einstein Call Coaching helps managers more effectively coach individuals, provides the ability to scale those learnings across teams and gain deeper insights into customer needs and experiences.”
Efrat Rapoport, Director of Product Management, Salesforce Sales Cloud
“Just like athletes can sit down with their coaches
and look at video clips, now sales reps can sit down and listen to audio
clips,” said Patterson.
Call Coaching also supports a library of best-practice call excerpts for new hire training and sales refreshers.
Tomorrow, I will discuss the other voice tools launched at Dreamforce.
On Monday, Radius Intelligence and Leadspace announced their merger and plans to become the “leader in B2B data intelligence.” The firm, which will continue under the Radius brand, is no longer emphasizing predictive analytics.
The predictive analytics market has failed to develop as a standalone segment. According to Radius Chairman Darian Shirazi, the total investment in the space was over $600 million. However, Gartner sized the market at $100 million to $150 million in 2016 revenue, suggesting that the promise of predictive analytics was developing slowly.
In his just released 2018 MarTech Landscape, Scott Brinker removed Predictive Analytics as a segment as machine learning is being integrated broadly across marketing products.
For B2B predictive tools to work, they require high quality reference data sets for initial and ongoing enrichment, but the predictive analytics companies black-boxed their data sourcing. Radius was one of the few exception to this opacity as they were transparent about their data acquisition model (web crawling combined with a customer contributed data model), but most of the other firms have been vague about their data models.
The predictive analytics companies were also slow to offer ABM tools and similar company and contact recommendations. These features are now commonly offered by both predictive analytics companies and sales and marketing intelligence firms such as D&B Hoovers, InsideView, DiscoverOrg, and Zoominfo. What’s more, the sales and marketing intelligence firms have all developed light predictive scoring or ranking tools. While none of these firms approaches Radius or Leadspace in predictive capabilities, they all provide company and contact insights for sales reps, ABM tools for sales and marketing, and integrated data enrichment processes.
The predictive analytics firms also initially black boxed their models, preferring to hide complexity. They have since become more transparent and begun displaying the top reasons for recommendations. However, Salesforce Einstein has provided similar functionality with predictive scores and insights.
Todd Berkowitz of Gartner summed up the situation well.
I’ve been covering the market for B2B predictive marketing analytics for almost four years. A few years ago, predictive lead scoring was all the rage. Then it became about fit and intent models for demand generation and prospecting. Then these tools were used for selecting accounts for large-scale ABM programs. But in the end, the standalone market for these applications never fully reached its potential. Many of the original vendors got acquired for their technology (Fliptop, SalesPredict, Infer and others) and predictive scoring became a standard feature of marketing automation and SFA systems.
Just because the standalone market went away, doesn’t mean there isn’t a lot of value here. In fact, the solutions have essentially moved into two other markets (and you’ll see this reflected in our upcoming Hype Cycle reports). On one end, you have the Data Intelligence for Sales market where predictive and AI-driven solutions are competing with traditional data vendors for demand gen, prospecting, and segmentation use cases. On the other end, you have the broader ABM solutions market where these applications not only help with account selection and planning, but are moving towards engagement and orchestration.
Berkowitz predicted that one or two of the remaining predictive analytics vendors will be acquired in the next six months.
With over 6,000 MarTech companies, the market is quite fragmented. Although the MarTech sector continues to expand, there is already momentum towards consolidation as clients look for broad, integrated functionality instead of many point solutions. For example, marketing and sales departments adopting ABM need a broad set of functionality which includes
AI scoring and recommendations
Real-time, batch, and continuous company and contact enrichment
Data hygiene (e.g. de-duplication, data standardization, and verification services)
Third-party verticalized data enrichment
Website visitor id
Look-a-like company and contact prospecting
Segmentation, TAM, and pipeline analysis
CRM, MAP, and sales engagement connectors
Account social media monitoring
Company and contact intelligence
At this point, nobody offers a full suite of these ABM capabilities for sales and marketing departments.
On Monday, Leadspace and Radius Intelligence announced their merger. The two firms were early entrants into the predictive analytics space, but the market for standalone predictive intelligence services has not developed as predicted. Thus, VCs and private equity companies are sitting on large bets that have yet to pay out.
The merged company will continue under the Radius brand as the “leader in B2B data intelligence.” Leadspace CEO Doug Bewsher will take over as the CEO of the merged firm while Radius founder Darian Shirazi will assume the role of Chairman. The two positioned the merger as a coming together of firms with complementary assets across company (Radius) and people (Leadspace) intelligence.
“Radius and Leadspace as one company will deliver a standout go-to-market platform with the best data, artificial intelligence and integrations at its core… What’s truly exciting is that our mission remains the same. Radius will be the nucleus that powers data and intelligence across all B2B applications, channels, and users — now built on The Global Network of Record.”
Radius Intelligence Statement to Customers
Both Leadspace and Radius have edged closer to prospecting and data enrichment than other predictive vendors. Leadspace has long offered contact enrichment and prospecting, even appearing in a 2015 SiriusDecisions report on Contact Data Management. Meanwhile, Radius has built its own database of US company and contact data which it named “The Network of Record” and positioned as the “single source of truth for account data.” The Radius database spans 18 million US companies and 25 million contacts with verified emails and direct dials. Radius also offers digital ad targeting.
Radius is positioning itself as being at the center of B2B predictive analytics, B2B Audience Management, and B2B data management. However, several of the data solution vendors also offer advertising solutions including Infogroup and Dun & Bradstreet. (Source: Radius Intelligence)
The new Radius will help sales and marketing teams “find the right data on the right buyers, and reach those buyers across any channel.” Revenue teams will have access to the “industry’s most comprehensive data intelligence solution.” Features include account and people targeting, data management, ABM execution, and integrations with Salesforce, Microsoft Dynamics, Marketo, Eloqua (Oracle Marketing), and Pardot (Salesforce).
Shirazi is positioning the company as an Einstein competitor with expanded assets to compete against Salesforce. “We’re excited about this because it will create the largest number of customers, largest revenue base and really provide a company that is at scale in B2B data and intelligence,” said Shirazi. “The only other major player in this space we believe is Salesforce Einstein, and we’re excited to really give them a run for their money.”
Shirazi provided the following list of planned enhancements to be rolled out over the next year:
Master Data. Master Growth
Extend reach and accuracy as The Network of Record unites with Leadspace’s proprietary, real-time virtual database sourcing
Take complete control of data governance with added data dashboard functionality
Enhance data matching and append for contacts, as well as lead-to-account matching features
Real Intelligence. Real Buyers
Strengthen targeting on individual decision makers in both the U.S. and international markets
Access enhanced segmentation, scoring, and insights on contacts
Leverage features from two effective sales intelligence tools
Scale Channels. Scale Revenue
Expand audience reach with the largest deterministic reach of any platform
Source more contacts with even higher accuracy and contactability rates
Connect more channels with more seamless integrations and partners
Shirazi describes Radius as the next “backbone go-to-market platform.” The combined assets “will enable marketing, sales, revenue ops, and customer insights teams to finally address their data gaps and conquer their targeting challenges. We will create a standout solution in a crowded, fragmented space of point-solutions where customers are forced to stitch together multiple products or change vendors every year.”
Back in 2015, Radius Intelligence had a market value of $500 million and funding of $107.6 million. Leadspace never disclosed a valuation, but it received $59 million in funding with a $21 million Series C in December.
LinkedIn lists 100 Leadspace employees and 160 Radius employees.
The merged company has over 200 customers including Sam’s Club, Hewlett Packard, Microsoft, Comcast, MetLife, and American Express. Both firms maintain “innovation centers” in San Francisco and Israel.
I attended the Salesforce World Tour Event in Boston yesterday and came away a bit underwhelmed. I’ve attended it for the past four or five years, so that may be part of the reason I didn’t stay for the full day.
In attending, I had several topics top of mind:
What is the future of Data.com? Will it be phased out and when? If they are attriting 30% of their revenue this year (a Dun & Bradstreet estimate), how are they guiding their customers to AppExchange solutions in lieu of Data.com?
How is Einstein being infused into their Sales Cloud? How are they ensuring that Einstein Insights are based on accurate and timely data?
What is the future of SalesforceIQ CRM technology (it is being decommissioned in 23 months)?
Meeting with Sales and Marketing Intelligence vendors on the floor.
I stopped by several of their sales and platform booths, but nobody had any answers on Data.com. This is the second year in a row in which there was no mention of data or the future of B2B prospecting, data enrichment, or sales intelligence at the event. Salesforce has never been much of a data company. They botched Data.com from Jigsaw acquisition through decommission. A few months after announcing a detailed roadmap at Dreamforce, they cancelled their Dun & Bradstreet content partnership in early 2017.
But if you are going to build analytics into your platform, license the iconic Einstein name for it, and tout it as an enabling technology for all of your clouds, then maybe you should have a strategy for ensuring that Einstein Insights are based upon quality data.
I did get to see a quick demo of Einstein Insights for the Sales Cloud. It provides lead scoring with recommendations so a sales rep can see whether a lead is likely to convert (or other goals) and review the top reasons for the score. It even goes so far as to recommend additional contacts but fails to justify those names. It appeared the names were mined using the SalesforceIQ technology, but all that was demonstrated was the name — no title, level, or reason to reach out to that individual. Salesforce is on the right track here but needs to expand its explanations for lead scores to its contact recommendations.
As to sales and marketing intelligence, there was only one vendor on the floor — Zoominfo. They were demonstrating their new Clean and Complete services for Salesforce. Clean provides batch account, contact, and lead record enrichment while Complete provides account, contact, and lead record appends during data entry and batch upload. Due to the depth of the Zoominfo database, the Complete service has an 80% account match rate and a 65% contact match rate.
Both services support custom mapping. Pricing is based upon record volume.
The keynote lacked the energy of prior years when Keith Block, COO, performed the duties. While Sarah Franklin, EVP of Developer Relations did a fine job, Block is from Boston and made sure the event was localized. Missing this year were sports heroes (e.g. Tom Brady, Bill Belichick) and the Drop Kick Murphys. If you want to wake up a 10:00 AM keynote, the Drop Kicks and their Irish punk are a great way to do so.
I’m a sailor peg
And I’ve lost my leg
Climbing up the top sails
I’ve lost my leg!
I’m shipping up to Boston, whoa…
“I’m Shipping up to Boston,” Drop Kick Murphys
There was a presentation on Year Up (an inner city business training program) with a local success story, but the 75 minutes were basically rehashed Dreamforce partner videos and content with a focus on B2C. Even the B2B example, 21st Century Fox, was equally a promo for “Dead Pool 2” and other Fox properties as it was a demo of Quip and its marketing and project management tools. The distributor relations aspect of the story was a bit light.
So let’s bring back Keith Block next year and expand the exhibition space. The Hynes Exhibitor Floor was too crowded, too hot, and too noisy.
I don’t mean to grouse. Salesforce is a terrific company. They have a strong social mission, a market leading product, and an ability to keep things fun. It’s just that this year didn’t match prior Boston events, and the company has diversified into so many clouds and capabilities that the Sales Cloud and Sales Partner solutions get crowded out.
The theme of this year’s Dreamforce was The Fourth Industrial Revolution. Following after revolutions driven by steam, electricity, and information technology, the fourth industrial revolution blurs the “physical and digital worlds” creating a wave of “innovation in technology” which is transforming the economy, society, and lives while creating new jobs, industries, and opportunities. This next wave is based upon intelligence. Elements include IoT, 3D printing, biotech, robotics, autonomous vehicles, nanotechnology, and quantum computing.
“This is what we call the fourth industrial revolution,” said Salesforce CEO Marc Benioff. “There’s all these amazing new technologies, things like autonomous vehicles and artificial intelligence and nanotechnology and mobile computing and all these things are really hitting at once. And companies are really transforming themselves and bringing all these new technologies in really to connect with their customers in new ways.”
Thus, elevators loaded with sensors now communicate back to the manufacturer and predict failures, calling for service prior to trapping people. Likewise, with tires, “if the tire blows, nobody knows; but in the future, if the [smart] tire blows, everybody knows.” So, firms like Kone (elevators) and Michelin (tires) are now B2B2C companies. In the future, if a tire is about to blow, it will communicate to the autonomous vehicle to pull over.
“Every company is getting closer to their customers. We’ve been talking about this for years. It doesn’t matter if you’re a B2B company or a B2C company, everybody’s becoming a B2B2C company.”
Salesforce and its customers are “delivering personalized one-to-one engagement at scale,” said Stephanie Buscemi, EVP of Product Marketing. This is done “declaratively, with clicks and not code.” Through the Salesforce Data Management Platform, ads are customized and delivered cross-device, allowing companies to redisplay ads or present new advertisements to their customers and prospects.
Benioff cited a series of companies providing customer service and support through Salesforce platforms including Louis Vuitton, Marriot, Coca-Cola, T-Mobile, Adidas, and Ducati Motorcycles.
“Behind all these things…behind everything is a customer. And that’s what all of us do. We are working to connect with our customers in an incredible new way.”
Simplified customization, development, and branding were emphasized during the keynote. A set of customizable products provide a “smarter, more personalized Salesforce”:
MyTrailhead service supports custom branding, content, and learning paths that allows firms to onboard and train employees on desktops and phones. Tools include quizzes, reference links, trails, and badges. Salesforce Trailhead content is also available.
MyEinstein provides an artificial intelligence layer driven declaratively by “clicks, not code” supporting “smarter capabilities including bots.”
MyLightning customization provides an app builder with custom pages, a Lightning theming and design system, Lightning Flow, Components, and Bolts which operate automatically on both desktops and phones. Designers will have access to dynamic components which are conditionally displayed.
MySalesforce branded “mobile apps without code” can be uploaded to the Google Play and App Store.
MyIoT supports native integration capturing real-time events, business rule automation, and low-code orchestration.
Based upon customer feedback, SFDC has shifted from IoT as a separate platform to an integrated feature of the CRM platform which also operates “declaratively without code.”
Benioff admitted that the Fourth Industrial Revolution is creating concerns and wondered whether it is “uniting us or dividing us. Are we more connected or somehow less connected?”
He also asked whether there is more or less equality in the World.
“There is this stress being created by this fourth industrial revolution. Yes, we have this promise of this new connected World. But what is it doing to us? And what are other actors doing around the World using these technologies? Are they changing our society? Are they changing our elections? What are they doing with this technology?”
Benioff is looking at the Trailblazers attending Dreamforce as the Customer Innovators, Technology Disruptors, and Global Shapers to ensure that the next wave is directed in a positive direction. “You have all these new tools at your fingertips, these incredible new technologies, but you are doing some amazing things in the World. You are changing your companies. You are steering this technology in the right direction. I’m so confident in who you are. I’m so confident in what’s in your hearts and where we are all going.”
Benioff noted that most technology is generally neutral in it effect upon society. It is therefore incumbent upon technologists, developers, and companies to deploy technology in a socially responsible manner which promotes greater equality. Benioff called for companies to fight for equality through equal pay, investing in schools, and opposing discriminatory laws. He also noted that it is the poor who are most hurt by environmental degradation and proudly stated, “we are a net zero cloud.”
Benioff was also proud to have founded and led the leading CRM with an 18.1% market share (2016 IDC) nearly double that of Oracle (9.4%). Salesforce has the top solutions for sales (34.2%), service (33.7%), marketing (9.9%), and Platform-as-a-Service. Within the marketing cloud, Salesforce claims to offer the leading Data Management Platform and commerce Platform.
What’s more, the firm is on track to be the fastest enterprise software company to hit $12.5 billion in revenue. They hit $10 billion this year and have FY19 guidance of $12.5 billion in year 20.
One of the issues facing businesses and policymakers is an increasing skills gap. Benioff proposed MyTrailhead as one of the tools to help address the problem of workers across many industries and skill levels. MyTrailhead provides a customized, branded training platform.
TechCrunch complained that this year’s Dreamforce lacked drama as it lacked new initiatives such as the social enterprise, artificial intelligence, and IoT. “They are a company that embraces the cutting edge, but this year lacked that kind of big announcement,” complained enterprise reporter Ron Miller. To be fair, though, the company has rolled out a series of new platforms, clouds, and acquisitions over the past few years. A year with few fireworks is not necessarily a year without forward progress for Lightning, Quip, Einstein, Trailhead, and platform customization.
The conference remains a monster with 170,000 registered participants joining in San Francisco and millions of online views.
A few weeks ago, Salesforce announced its new Artificial Intelligence (AI) functionality called Einstein. The new features promise to provide improved decision making based upon predictive scores and recommendations to sales, marketing, service, and other functions. Likewise, Microsoft announced yesterday that they have formed a dedicated AI group working on infusing Microsoft products with intelligent capabilities.
However, as AI and Predictive Analytics become key technologies for companies, it is important to remember the old GIGO maxim:
Garbage In, Garbage Out
These tools simply won’t work well if your information is inaccurate, out of date, or incomplete. Best case, bad data results in weak predictions that aren’t trusted. Worst case, they provide a false confidence that wastes resources and misdirects corporate activities.
John Bruno, an analyst at Forrester, described this problem well in a recent blog:
The future analytics-driven sales processes is bright, but the path ahead is not without its challenges. Current and potential Salesforce customers should be mindful that intelligent recommendations require a large volume of quality data. If poor data goes in, poor recommendations will come out. Cleansing data and iterating the fine-tuning of recommendations will be vital to long-term success. Another major hurdle is adoption. Many sellers still lack trust in “intelligent” recommendations. You will need to handhold these sellers until they form trust. This means starting with small recommendations and scaling from there.
The good news is that many of the sales intelligence companies are now offering data hygiene services for lead, contact, and account records. The processing can be performed via CRM or MAP connectors or by uploading files to their cloud services. The vendors match sales and marketing files against their reference datasets and then augment the files with firmographics, biographics, technographics, etc. Matching can be done both in real-time to support both list uploads and web forms and via batch processing to support on going maintenance of corporate data.
While no company and contact database is 100% accurate, they are far more accurate than most marketing automation platforms and CRMs. Furthermore, they have better field fill rates, standardized values (important for segmentation and analytics), and more rapid update cycles.
The predictive analytics companies are also beginning to provide enrichment services.
In the late 1980’s, when my career was first beginning, I worked on a technology helpdesk for an insurance agency automation system (Aetna’s Gemini platform). Many of the calls were routine with an easily road mapped set of resolution steps. So the firm decided to invest in artificial intelligence (AI) and began interviewing its most seasoned experts to identify the problem resolution path.
After several months of development, an AI module would be unveiled that walked the user through problem resolution. It was basically a set of if-then-else and case statements providing pre-coded branching logic. Support reps started with a category and were walked through a set of questions to ask and resolution steps to convey over the phone.
The solution was expensive and lacked the ability to learn. Thus, if new problems arose or the problem resolution changed due to new hardware or software being introduced, the rules no longer applied.
It was far from intelligent. Heck, I’d coded a twenty-questions game in a first semester programming class that was more intelligent than the service. At least my Q&A game had the ability to learn new questions to ask without requiring an expensive consultant.
Finally, it was only used by new hires as much of the routine steps were just that — routine.
Solutions like this quickly proved that Artificial Intelligence wasn’t intelligent and after a few years, the term AI fell from favor and returned to the realm of sci-fi killer robots.
Nearly three decades later, the term AI is once again being rolled out. But now it does convey an impressive level of intelligence which makes our devices feel smart. It’s why we call them smartphones. They are able to leverage vast amounts of data and make decisions in the blink of an eye. Whether it is asking Siri a question or having Google map the best route to a location subject to current traffic patterns and transportation mode, we expect our devices to be intelligent.
AI represents a massive change in technology. You might call it a “paradigm shift” or “disruption” or we could just stick with “massive change.” What we’re trying to say is, AI is kind of a big deal. And just like the arrival of the personal computer, cloud computing, and the mobile smartphone, AI is going to fundamentally change the way things work, forever.
So it was with a smile that I saw the term AI being used by Salesforce in positioning their new Einstein service. Each year at Dreamforce, CEO Marc Benioff discusses a new underlying technology or cloud. Most recently it has been Lighting (UI and workflows), Wave (analytics), and the Internet of Things Cloud. At Dreamforce 2016, it is Einstein, their artificial intelligence platform to assist with sales, marketing, and service.
Salesforce presents AI simply as
Lots of data + cloud computing + good data models = smarter machines
So while much of this technology has been provided as consumer applications for over a decade, businesses have been lagging behind when the scope goes beyond a mobile app or e-commerce portal.
Shouldn’t the full transactional and service history be available to help understand past purchases, preferences, and potential cross-sell and upsell opportunities?
Wouldn’t we want it delivered no matter the touch point?
That is the type of intelligence that Einstein is looking to bring to Salesforce customers. Einstein is “the world’s first comprehensive artificial intelligence platform for CRM. I’ve never been more excited about the innovation happening at Salesforce,” said Benioff.
Einstein is available both programmatically (for developers) and “declaratively for non-coders,” said Benioff. It is integrated directly into the SFDC platform and available across all of the clouds. For example, an Einstein widget displays a set of insights identifying competitor news, recommended actions, and account intelligence.
Einstein builds models with no coding or initial training by users. For example, the system is able to determine which trigger events are important to sales reps and surface news about competitors without asking “who are your competitors?” The system also can make recommendations concerning high-scoring leads based upon both fit (firmographics, biographics) and behavior (e.g. recent viewing of a demo).
Not only does the system recommend activity, but it then offers recommended email copy including a proposed call time.
The platform is built on a series of recent acquisitions including RelateIQ (rebranded SaleforceIQ), MetaMind, Implisit, PreductionIO, and TempoAI. The firm now has a team of 175 data scientists “stitching together this amazing platform,” said Benioff.
“The new platform will “democratize artificial intelligence” and “make every company and every employee smarter, faster and more productive,” continued Benioff. “This is going to be a huge differentiator and growth driver going forward as it puts us well ahead of our CRM competition once again.”
The new platform infuses their sales, cloud, and marketing platforms with AI capabilities for “anyone” regardless of their role or industry. According to Salesforce, Einstein lets employees “use clicks or code to build AI-powered apps that get smarter with every interaction.”
Einstein is positioned as having your own data scientist focused on applying AI to customer relationships. Einstein has access to a broad set of intelligence including CRM data, email, calendar, social, ERP, and IoT to “deliver predictions and recommendations in context of what you’re trying to do. In some cases, it even automates tasks for you. So you can make smarter decisions with confidence and focus more attention on your customers at every touch point.”
Several predictive analytics companies used the launch to shout, “hey wait, we’ve already mastered AI for sales and marketing.” LeadSpace CEO and former Salesforce CMO Doug Bewsher stated, “B2B marketers need a complete solution that works across multiple channels, in their existing marketing stack.”
“Bad data is the Achilles heel of AI,” continued Bewsher. “AI is only as good as the data available to it. Marketers who want to get the full benefit of AI need to address their data problems first, or they’ll see the same diminishing returns as with traditional marketing automation.”
Shashi Upadhyay, CEO at Lattice Engines was a bit more diplomatic in welcoming Einstein. “After having led the market for several years, we are really excited to see the mainstream attention shifting towards AI-based solutions for marketing and sales. The Einstein announcement from Salesforce is a great step forward, as it will serve to educate the market and signal that predictive solutions are here to stay.”