Comparing AI tools in Salesforce Einstein and Dynamics 365

Both Salesforce with Einstein and Microsoft with Dynamics 365 are offering AI capabilities that promise to improve your customer service, sales pipeline and business processes. Here’s a look at the new AI features, what’s available now and why you’ll need them in the future.

Machine learning features have the potential to transform your marketing and customer support, but they’ve been out of reach for most companies. Now both Microsoft and Salesforce are building them into their cloud CRM tools, putting AI within the grasp of most enterprises.

The idea is to democratize the benefits of machine learning for businesses that don’t have data science expertise. “For the vast majority of companies, it’s too hard,” Einstein general manager John Ball tells CIO.com.

“To do data science, you have to have data, you have to collect and manage it and then you have to do some data wrangling. Then you have to hire a scarce data scientist, you have to build predictive models, you have to refresh them,” Ball says. “You have to have infrastructure that’s trusted and secure to run those models on and you have to maintain it. And then you have to actually take the recommendations and put those in the context of business users.”

Putting AI tools into the CRM makes them immediately useful. There are tools that can predict which leads will turn into opportunities and which opportunities will close and become customers. And there are tools that can offer suggestions to sales reps and marketers, from nudging them to follow up on opportunities they’ve been neglecting, to detecting when a competitor is mentioned, to predicting when a customer will open an email or unsubscribe from a marketing campaign, to helping you craft an email that will appeal to the person you need to reach.

Some of this will be fairly general. For example, when Salesforce does lead scoring, Ball explains, “if an email is @yahoo.com then it’s probably not a good lead.” Some of is much more specific: The British brewery Marstons is using Customer Insights in Dynamics 365 to put customer details, from their favorite beers to whether they have unused vouchers, drawn from Facebook and TripAdvisor as well as its CRM on the handheld devices of pub staff. With that personalized information, the brewer is hoping to sell an extra meal and drink a day in each of its 550 venues.

AI features compared

At first glance, the AI features in Salesforce and Dynamics are similar. Dynamics builds intelligence into the standard workflow, while Salesforce has specific tools in its different offerings.

Salesforce’s Sales Cloud has Predictive Lead Scoring, designed to suggest which leads are most likely to convert; you could use that to route better opportunities to more experienced sales staff. Opportunity Insights alert you when a deal is looking stronger or weaker, spot mentions of competitors in the conversation that might mean the deal is under threat, and even suggest if you’re talking to someone who won’t have the authority to close the deal.

Predictive Scoring in Marketing Cloud tells you how likely it is that a customer will engage with the email you’re sending them, coaches you on what language to use and even tries to send the message at the time recipients are most likely to look at it. Predictive Audiences will divide potential customers up into audience segments based on their predicted behavior, like disappointed customers you can win back, selective subscribers who look for specific products, loyalists you can rely on and window shoppers you need to appeal to directly.

Relationship Insights in Dynamics 365 offers many of the same features, automatically capturing information from emails you send and receive in Office 365 to fill in opportunities, doing lead scoring and sentiment analysis and showing you the health of relationships and the strength of opportunities, as well as risks to deals like competitors showing up in the conversation, and suggesting the next best action. Bubble charts show the health of your relationships with customers as well as how large the customers are, to help you prioritize. You get alerts for customers who want to meet you as well as for opportunities that are going stale, among other smart notifications.

As you work in Dynamics, it fills in fields automatically with predicted information, like forecasting demand and inventory — and even suggesting when you should order more inventory and which other products you should restock at the same time — and suggesting products to cross sell and upsell

Salesforce Commerce Cloud will create the kind of personalized product recommendations large ecommerce sites have; it can also personalize the order products are shown in and even what shows up in searches. Commerce Insights will suggest correlations to explain purchases, including the channel you reach people on, whether they buy after opening a specific email or even their email domain.

Dynamics 365 also uses machine learning to suggest products based on wish lists, click patterns and past orders. It can also personalize for each customer the information that's shown about a product.

Salesforce Service Cloud Recommended Case Classification automatically fills in key fields so cases can be routed to the right staff. Recommended Responses highlight the information service staff should use when responding, and Predictive Close Times will predict how long it will take to resolve an issue. Similarly, Community Cloud will recommend specific experts, articles and topics, and if a post doesn’t get a response, Automated Service Escalation automatically creates a support incident. That’s similar to Dynamics’ pre-emptive service feature, and there are scenarios in Microsoft’s Azure ML service to built models that suggest relevant Knowledge Base articles and case studies.

And the Einstein features in Analytics Cloud are broadly similar to the Customer Insights tool in Dynamics 365. Both let you pick measures and KPIs, like cost and profitability, and see correlations and insights. The Salesforce tools produce Word and PowerPoint documents of the customer journey; Customer Insights uses Power BI visualizations to show KPIs, insights and actions — and you can integrate them into custom apps like the one Marstons built for its staff.

When can you get these features?

Salesforce focused heavily on the Einstein AI features in the Customer Success Platform at its October Dreamforce conference, but it had actually launched them a month earlier. That doesn’t mean you can actually use them right now; some are ready, some are still in development and they nearly all come out of Salesforces’ recent acquisition spree in this area.

“Some Einstein solutions, like the recommendation engine based on technology from Demandware (acquired in June) are currently or will be soon available. So are machine learning-based data discovery and analysis services leveraging technologies from DemandCore (acquired in September),” Charles King, principal analyst at Pund-IT, tells CIO.com. “But it is also clear that more advanced services and solutions won't be available until Salesforce more thoroughly integrates those acquired technologies, a process that could take several months.” 

Automated Community Case Escalation and Recommended Experts, Files and Groups are available now in Community Cloud Einstein, and they’re included in the Community Cloud license. Product Recommendations in Commerce Cloud Einstein is also ready to use and is included in the Commerce Cloud licence. Smart Data Discovery (based on another acquisition, BeyondCore) in Analytics Cloud Einstein is also available now, but you pay extra (by the volume of data and number of users), and you need at least 10,000 rows of data to get reliable results so this is definitely intended for larger businesses.

The PredictionIO server is already available, and it’s free, although you’ll need far more machine learning expertise to build tools on that. Similarly, you can sign up for the Predictive Vision and Sentiments developer services, which are in beta (Salesforce acquired MetaMind in April), but while it’s easy to drag and drop images into a web page to train your own deep learning model, selecting the right training set and evaluating how good the model is for the problems you want it to solve takes more machine learning experience.

The Einstein features in Sales Cloud, like Predictive Lead Scoring and Opportunity Insights, and Marketing Cloud’s predictive email content (pricing based on the size of your mailing list) will be the next to show up. These are being built by Salesforce using technologies that came with its acquisitions of ExactTarget and Heroku. Commerce Cloud will get Commerce Insights soon, and Predictive Sort for products will come sometime in 2017. Also not yet available are Predictive Wave Apps in Analytics Cloud, the Service Cloud predictive tools, and IoT Cloud Predictive Device Scoring, Recommend Best Next Actions, and Automated IoT Rules Optimization.

Salesforce is pushing Einstein as a platform service layer in its Customer Success Platform. So far, it’s a discrete set of useful tools, only some of which are ready to use.

In contrast, most of Microsoft’s intelligent features have either been available for some time or are ready for the November launch of Dynamics 365, King points out. “Microsoft's Dynamics 365 with AI is the result of the company unifying its ERP and CRM solutions, an effort announced in the summer of 2015. The Customer Insights cloud service is notable in that it allows customers to combine data from internal and external sources (including Microsoft partners Facebook and TripAdvisor). It can be used as a standalone service but also works with any external CRM tool with open APIs. Another solution — Relationship Insights — is built on the Cortana Intelligence Suite, which includes a recommendation engine, sentiment analysis and even facial recognition features.”

Smart notifications through the Cortana assistant are currently in preview, as long as Cortana is available in your country, initially in English (support for other languages is in development).

If you want to do predictive maintenance or remote monitoring, Microsoft has had preconfigured solutions for those in its Azure IoT Suite and Cortana Intelligence Suitefor over a year (the latter was initially called the Cortana Analytics Suite), and you can extend and customize those. Dynamics 365 includes IoT support for field service, and the predictive and prescriptive maintenance features will soon be incorporated as well.

The Cortana Intelligence Suite includes some of the 22 developer APIs already available in Microsoft Cognitive Services, like the voice recognition and natural language understanding APIs that fast food chain McDonald’s is using to turn what customers say at the drive-through window into an order. There are already partner apps based on these services, like Veripark’s tool for suggesting your next best action, available in Microsoft’s App Source store.

And if you want to build your own machine learning systems to extend what you do with Dynamics, the Azure Machine Learning Studio is a drag and drop environment with dozens of machine learning modules and solutions for everything from fraud detection to sensor data analytics, so you can start from scratch or adapt existing tools. It might seem a long way from CRM, but when you think of it as part of a digital business, it looks like more of a continuum. And that might give Microsoft the advantage in the long run.

For example, Microsoft is currently has in trial an intelligent customer support agent that uses machine learning. The support bot will suggest Knowledge Base articles that might fix the problem a customer describes in the chat. If that doesn’t solve the problem, the customer can type in more details or ask to be handed over to one of the 2,000 human agents in the pilot. The human agent gets a summary of the session so the customer doesn’t have to enter all the details again, and the support bot also learns from the solution the human agent suggests. Microsoft isn’t making that system available as a product — yet — but it’s something that would be a great tool for the Dynamics 365 service in the future.

“At this point, Salesforce seems to be taking a broader and more granular approach to CRM processes and functionalities,” King says. “But, while ambitious, its Einstein platform and services will take time to mature and achieve the full range of features the company envisions. Microsoft's Dynamics 365 with AI is the result of a multi-year process, and appears to be the more mature platform and solution set. More importantly, Dynamics 365 with AI is just one of what will eventually become a host of Microsoft AI-based solutions and services designed to enhance business processes. Salesforce's Einstein may eventually deliver a deep view and reach into CRM, but Microsoft is taking a far broader view of the implications and opportunities for using AI technologies in business.” 

1 2 Page 1
Page 1 of 2
Discover what your peers are reading. Sign up for our FREE email newsletters today!