Salesforce Einstein is here. The technical media outlets have lauded its arrival for a while, but not really taken the time to explain what it is or how it will benefit users. If you’re relatively new to Salesforce or to the concept of SaaS, you’re probably feeling a little confused. Let Nadcoms explain not only what it is, but how this upgrade could potentially help your business.
An Overview of Salesforce Einstein
Announced in September 2016 and rolled out in March 2017, Salesforce Einstein is an AI or Artificial Intelligence framework. Developed for the Salesforce Customer Success Platform, it is now available across all main cloud products. It’s the first of its kind for CRM (Customer Relationship Management) aiming to enable the easier process of data and aid better decision-making for users.
Its main aim is to provide those responsible for marketing and sales with more comprehensive information about customers and to ensure it is the most up-to-date information available. The main advantage data acquired through Einstein helps users avoid several well-known headaches with the Salesforce package. One advantage is that they help organisations predict the position of a customer in the sales process.
Until the arrival of Einstein, AI has been prohibitively expensive and too complex. Not only has Salesforce made AI available at an affordable price, it’s reduced that previous complexity. It is now scalable for everyone – small and large businesses alike. It is expected to become the new standard for future Cloud SaaS.
Explaining Service Cloud Einstein
Einstein is available for many of the Cloud modules of Salesforce. One of the most important and wide-scale is the Service Cloud. The main advantage to Einstein for the Service Cloud is the speedy processing of customer service issues. The AI keeps track of individualised product and customer issues, automatically processing specific instructions to agents. New insights help your customers find the right answers at the right time, potentially increasing your conversion rate. Thanks to these improvements, businesses such as yours may offer a superior customer service experience with predictive and intelligent processing, resulting in a happier and more efficient customer experience.
As far as your employees are concerned, the machine-learning framework of Salesforce Einstein means greater prediction accuracy, more confident decision-making and faster resolution times. It’s all thanks to big data and smarter analytics.
Explaining Sales Cloud Einstein
More formally known as the Einstein High-Velocity Sales Cloud, it is an exciting addition to the Salesforce family. It empowers employees primarily concerned with sales, delivering everything they should need to improve sales performance and analytics all from a central location – the Lightning Sales Console. It’s possible for anybody to identify the highest quality leads and pursue them. This has been a problem area for many years: man hours wasted on poor quality leads that go nowhere. With these pipeline improvements, sales will increase.
- The Lead Scoring system ranks potential leads in terms of quality, making intelligent predictions
- Activity Capture allows connection to your calendar and other systems so Salesforce can grab data and compile it, improving customer information quality
- Users may now modify console so the Salesforce system looks and works how you need it to work
A Practical Use
“So what?” you may say. “AI has been around for years and, each time, fails to deliver. What is so different now?” And the truth is, you are right, AI has never really been a practical solution. But in this age of information, online tracing, powerful analytics, mass connectivity and the sheer power of technology, AI is able to thrive.
For example, take the demonstration used at this years World Tour in London. A firm who sells and fits solar panels to roofs decided to use Einstein to help qualify the customers as viable Solar panel customers. They found that there were two main reasons why deals fell through, and it was on these deals where most of their sales reps times were lost (Potentially 1-2 hours per lost sale). For a customer to be viable for a Solar panel there were two key pieces of criteria that they wanted Einstein to qualify against:
- The roof of their house must be pitched and not flat
- Ideally the pitched side of the roof will be South-facing. (if not, the energy produced would be less)
Using Einstein, the firm was able to simply enter a post code and house number in to salesforce. Einstein takes this information, searches for the property on google maps, and pulls back the image of the ‘street view’. This is where it gets very interesting. Einstein can then analyse the picture itself to determine if the roof is pitched. That’s right, it is intelligent enough to analyse key pieces of information within an image. It is also able tell which direction the pitched side of the roof is facing and use a simple calculation to determine the power they are likely to produce per solar panel. And all of this is analysed and fed to the sales person instantly.
I don’t think I need to highlight the benefit of giving a sale rep up to 2 hours back per sale. Add to that, the customer’s experience and being provided a personalised estimate at the point of first call and they were on to a winner.
Just this one use case excites all of us at Nadcoms for the future and potential of AI and specifically Einstein.