What Einstein Means for Salesforce Admins


This week we are honored to be speaking to product marketer, Ayori Selassie, about Salesforce Einstein. Ayori’s passion for her work with Salesforce is infectious and invigorating. As Ayori says, “I freaking love my job!”

We are so excited to hear what she has to say about Salesforce Einstein — an exciting advancement in artificial intelligence for companies. Ayori has been with Salesforce for quite some time and will explain what Einstein is all about. Join us as she shares her passion for artificial intelligence and explains exactly how every industry can use Einstein to its advantage.

You should subscribe for the full episode, but here are a few takeaways from our conversation with Ayori:

Introducing Einstein

Salesforce Einstein is artificial intelligence for everyone and every business. It is vastly different from traditional lead scoring, which relies more on a rules-based and formula fields logic. Einstein signifies machine-learning and as Ayori says, “the difference between machine learning and rules is, rules don’t learn.”

She also admits that Einstein is a little mysterious in how it works. Meaning, “right now it is a feature. You turn on the predictive lead score and all of a sudden, after the models have generated, you’ve got scores popping into your leads telling you which are the best for your agents to follow up with.”

Traditional lead scoring versus Einstein

If you already have a system in place, she recommends that you compare whatever existing lead scoring you’re currently using to that of Einstein. “Do an AB test,” she advises. She goes on to explain that you can use agents who are utilizing the traditional predictive lead scoring as well as agents who are fully prioritizing their day based on what Einstein suggests, and then make the comparison from there to see how you feel about the results.

Biased Data

Ayori has the notion that “dirty in is dirty out” and “you can’t get insights out of dirty data.” Nowadays, we have the capability to manage large volumes of data and to keep it clean and organized. However, having “clean” data doesn’t necessarily mean that you’ve collected the right data, after all “our machines are only as good as the data we feed it.”

We are humans, and therefore, we’re naturally biased. We need to understand the importance of processes and best practices for data capturing to ensure that what we collect will give us a fuller picture so as to avoid harmful biases. “We’re working with teams right now to be able to establish these processes and to make sure that we can share them with our customers. It’s something I’m particularly passionate about.”

Artificial Intelligence and the future of human jobs 

Many people are afraid that AI will take away their jobs. However, this technology is actually making us more respected than ever. As Ayori says, “it’s making your executive-level functioning more valuable than ever. It’s making your creative thinking more valuable than ever.” She goes on to say that if people stopped reacting to the minor routine things that are driving them crazy every day, then they can use some of that creative energy to solve new kinds of problems, to envision new kinds of solutions, and to find new ways of engaging their customers.

“You get to be part of leading and ushering artificial intelligence into a state where it is transformative for people’s lives and we’re creating a better state of society.”


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