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How to Create a Differentiated Customer Experience with Salesforce Einstein

How to Create a Differentiated Customer Experience with Salesforce Einstein

For those of us who didn’t get a chance to be at this year’s Dreamforce, they can check out the daily highlights in our Dreamforce blog series. The Dreamforce’17 was packed as every other year, there were many sessions on Einstein, in fact too many for us to attend, so we had to do like everyone else, Prioritize! I will try to summarize the features and road map discussions we experienced at DF’17 for you in this blog to give you an idea that how Salesforce Einstein will help you shape a differentiated customer experience.

But before we jump into the features, we’ve been asked by a few of our customers about the difference in Einstein and Einstein Analytics which was a term introduced at this year’s Dreamforce. Einstein Analytics is the new name for Wave Analytics which would sit under Einstein. We hope this clarifies the confusion few of us had because of the change of names

Personalizing at scale is precisely the idea behind two “myEinstein” capabilities announced at Dreamforce. Also announced were two Einstein Analytics capabilities. All four capabilities are coming to the portfolio next year. Here’s what was promised for your business:

1- Einstein Prediction Builder:

Plenty of Salesforce customers are using or considering machine-learning-based Einstein capabilities. But at Dreamforce 2017 we were told that some 80% of the customer data in Salesforce is tied to custom fields and objects. There should be no surprise that the top request among Salesforce customers was for customizable, as well as pre-built, Einstein insights, predictions and recommendations.

Einstein Prediction Builder is a no-code capability designed to enable non-data-scientists to develop predictions using custom fields. Use cases are limitless, but popular use cases could include cross-sell/up-sell, churn and CSAT. Prediction Builder will be powered by the same machine-learning data pipeline that handles millions of Einstein predictions per day, but it will be opened up, starting with a February 2018 beta release and likely June 2018 general release to custom fields and objects in Salesforce.

2- Einstein Bots:

Einstein Bots, a second My Einstein feature, will couple Salesforce language capabilities with Salesforce data and the Salesforce workflow engine to power automated customer-service agents. The idea is to handle the bulk of the simple, frequent service cases, such as user password resets, while leaving the long tail of complex and infrequent service inquiries to human agents.

As with Prediction Builder, Einstein Bot development will be a no-code proposition. It will start with point-and-click selections and workflow setup and uploading of spreadsheets of sample customer service interactions text to train the language model. Beta release is expected in February 2018 with generally availability to follow in June 2018. The Bots will start with text-based interaction, but voice-based interaction is likely to follow.

3- Einstein Data Insights:

This new Einstein Analytics (formerly Wave) capability provides deeper insights into standard Salesforce reports from the Sales Cloud, Service Cloud and, eventually, other clouds. Powered by the same engine behind Einstein Discovery, Einstein Data Insights will automatically surface important trends, changes over time and even data-quality problems within standard reports, displaying a combination of visualizations and textual explanations.

Users will press a button embedded on a standard report and the visualizations and textual explanations will appear on the right side of the screen (as displayed in the image above). This capability is also expected to see beta launch in February 2018 with general availability next June 2018.

4- Einstein Data Explorer Feature:

This capability, which will be included with Einstein Analytics, will let you have “a conversation with your data,” says Salesforce, by typing in questions in plain English. Behind the scenes, keyword driven interpretation will help you drill down on dashboards and visualizations to better understand not just what happened by why it happened. You could drill down on a total figure, for example, by typing “amount by product.” Or you could analyze performance by typing in “lost deals by product.” This feature is expected to be generally available in February 2018.

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Please get in touch to find out more details on how we can help transform your business with Salesforce Einstein AI platform. We would be happy to offer a free consultation and also share more details and features of the Salesforce platform that can help grow your business by empowering you with predictive intelligence that helps make smarter decisions based on your data.

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