Rajneesh Kumar
Rajneesh Kumar 7 September 2017
Categories B2B, B2C, Technology

Turbocharge Your Customer Relationship Management with Salesforce Einstein

Picture this: You have a personal data scientist at your service, that enables AI capabilities into your apps, helps you with predictions and suggestions, discovers relevant insights automatically, advises next best course of action, automates tasks, and all that proactively. Reminiscent of Microsoft office assistant, (à la Albert Einstein) the world’s most familiar genius walking out of a door?

Well, Salesforce Einstein is much more than that. It’s the world’s #1 CRM doubling up as world’s smartest CRM too. An all encompassing, built into Salesforce platform, that enables you to build AI-powered apps, and have smarter communication with your customers.

Here’s an inside view on how AI is revolutionizing customer success.


Salesforce Einstein is an integrated set of AI technologies for CRM that’s data ready. In other words, it doesn’t require any special data preparation; just putting the data in Salesforce does it for you. Salesforce Einstein is also production ready; it means that DevOps isn’t required either. Besides, Einstein is multitenant, so the right model fits your company automatically.

Einstein can make you much sharper and predictive w.r.t. your customers. Einstein AI tools are built-in across the platform—for instance, commerce cloud comes with product recommendations, analytics cloud has data discovery, community cloud has automated community case escalation, etc. So, no matter which Salesforce service you’re opting for Einstein AI will contribute to your success.


With Einstein, Salesforce intends to make sense of the vast reams of data, unravel insights, suggest next best action, automate manual time-consuming tasks that mars people’s productivity. Three most common and benefits emerging out of AI in CRM are:

  • PREDICTIVE SCORING – Every prospect gets a score, which tells you about the probability whether, for instance, it will convert or not. You also get the reasons behind the score. These reasons are factored on the basis of industry the prospect is from, etc., which contribute to the likelihood of the conversion.
  • RECOMMENDATIONS – The ubiquitous suggestions that retail buyers are used to is a fine example of recommendations. But, it goes further than that. For instance, it can recommend you which white paper should be mailed to your prospect, to improve the probability of closing a deal.
  • FORECASTING – Predicting the future value of, let’s say a real estate investment or a stock portfolio is possible with Einstein. For instance, if you’re a Sales Manager, AI can help you forecast your quarterly bookings better.


A spreadsheet is a spreadsheet is a spreadsheet, that anyone can make sense of, sort data based on several factors, cull out information. Then what makes machine learning so special? For starters, it examines the past data to make sense of the factors that forecasts most probable scenarios by itself. But, it doesn’t stop at that. It keeps altering its predictions according to the new incoming information. Machine learning lets computer systems build on customer data, operating on not only what’s been programmed but also by adjusting to changes. As the quantity of data increases, the answers get more coherent and lucid.

Einstein doesn’t just work from Salesforce data columns, but also from the information it analyzes in your customer mail trails. It’ll tell you of the probability of an email being opened by your receivers.


In Wikipedia’s words: “Deep learning is a part of a broader family of machine learning methods based on learning data representations, as opposed to task-specific algorithms.”

Deep learning allows you to create multiple layers of neutral networks (sets of algorithms to identify patterns) and train them. The top layer of the network trains itself on specific features and passes them down to the next layer, which in turn, adds other features and passes it further to the next layer and so forth. Deep learning goes beyond machine learning in identifying intricate patterns among huge sets of data and simultaneously enhancing their own accuracy while they’re at it. Salesforce Einstein enables marketers with deep learning to know more about their customer’s likes and preferences. With businesses generating a plethora of images, voice data, texts, and other communication, deep learning can do the unimaginable.


According to the Bank of America Merrill Lynch, by 2020, AI solutions will have an estimated market of $153 billion. The way businesses gather, digest and analyze data has reached exponential proportions. Employing AI in CRM can help companies overcome various challenges related to data, infrastructure, expertise and go from strength to strength, effortlessly.

With businesses becoming inextricably linked with Data Science, serious advancements are afoot in the world that connects them, to an extent that it’s hard to see business leaders talking meaningfully about one without mentioning the other.

The original post is published here.

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