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What are the most interesting features of Salesforce Einstein and how to leverage them

Has your organization taken advantage of the recent advances in machine decision making? The industry is being disrupted by Machine Learning. More and more, machines are generating insights at scale instead of humans. A Woodside Capital Partners Paper predicts that revenue generated by AI will reach between $25-40 Billion annually by 2025 [1].

Salesforce, a leading CRM provider, has taken advantage of this by developing Salesforce Einstein. It provides quick, machine-generated insights to predict outcomes, make recommendations, and automate tasks. Salesforce Einstein has several use cases across Sales Cloud, Marketing Cloud, and Service Cloud. These tools are only available Salesforce Lightning.

In Sales Cloud, the main feature to look forward to is Predictive Lead Scoring. Lead Generators often guess or use gut feels to decide which leads are likeliest to convert. Predictive Scoring gives data-driven insights that help them make better decisions. This makes the platform not just a data storage center, but a revenue generator. Leads are scored from 1-99 based on a number of factors. For example, a lead with an invalid phone number is less likely to convert. Better lead scoring means better conversion, and ultimately a better bottom line for the organization.

Einstein sends Automated Reminders to follow up with unresponsive customers. It can be hard predicting how long to re-message someone who is unresponsive. However, Einstein has been trained across many records to optimize the waiting times for sending reminders. These reminders are also available in Salesforce1, so your agents can respond on the go. Agents no longer have to take a chunk of time out their day to manage their contacts, meaning more time is actually nurturing leads and accounts.

Eliminating manual data entry has also been a goal for Salesforce. Many sales reps report the need to focus on the customer and less on recording every detail of the interactions. Einstein automatically captures activities and sends notifications to the reps’ email and calendar.

Opportunity Insights are another huge area where Einstein adds value. Einstein creates predictions based on customer sentiment, prospect engagement, and competitor involvement throughout your customer interaction. For example, a history of service issues would decrease the probability an opportunity would close. News about corporate budget cuts and increases also factor into Einstein’s algorithms, and can be displayed in your sidebar.

Einstein scans the news for you to deliver Account Insights so your agents don’t have to do it manually. When you view an Account on Salesforce with Einstein, important insights from the news will automatically pop up. For example, Apple may have lots of

Mergers & Acquisition related activity, indicating that it is expanding and will have more budget to spend. You can use this data to drive better decision-making

In Marketing Cloud, Machine Learning helps give better overall insight into customers using data on past behavior. This translates into recommendation into how to structure campaigns, deliver the right message, and how to allocate your time to engage with customers.

Marketing Cloud scans the web and social media for sentiment insights to give a picture of the general vibe of the company. This is available in multiple languages, so you can breakdown data based on language. Based on this data, you can route leads to the right agents.

Predictive Scoring in Marketing Cloud can give you the right analytics to determine who, what and when you run your campaigns. Predictive Scoring insights can recommend which products to put on your email campaigns. You can also see predictions of which audiences would be best to target. And based on the data, you can automate email deliveries to the subscribers who seem likeliest to engage.

Service Cloud will also integrate Einstein’s Machine Learning. For example, you will be able to recommend a case classification. This means cases are automatically defined based on user history and trends. Cases related to a product’s known defects are automatically routed to agents with instructions on how to handle the issue. This improves agent productivity and efficiency, providing faster, more efficient customer services. Ultimately, the goal is to raise customer satisfaction scores such as customer satisfaction ratings (CSAT), Net Promoter Scores (NPS) and Customer Effort Scores (CES).

So what can you do right now? Einstein also includes a Predictive Vision Service API which classifies images. This is often used as the “Hello World” of Machine Learning. You can try this at The tutorial will guide you in using the API to classify images.

Call your Salesforce account manager to explore options for making Einstein made available to your organization. Currently it is available as a paid license, so it won’t come free with your current edition. Your Salesforce representative can help draw out a custom plan for your organization.

With Einstein, Salesforce is bringing AI to the masses. With better, near-instant insights, normal user agents will be able to leverage the power of AI to make better decisions. Eventually, CRM will not just be tracking data and letting humans make the important decisions, but ultimately driving value in the sales process itself.


“Artificial Intelligence: The Ultimate Technological Disruption Ascends” Woodstock Capital Partners, January 2017

“Take a Tour of Salesforce Einstein”, inc., 2016,