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Sanjna Parulekar, Salesforce’s Senior Product Marketing Manager for Salesforce Einstein has lived in and around tech her whole life. As both of Sanjna’s parents had careers in tech, Sanjna felt she was destined to follow a similar career path. Fast forward to today when destiny has become reality. Sanjna is currently working with Salesforce Einstein helping to bring to life the influence it has on A.I., CRM, and the world. It comes without surprise that Sanjna is most excited for the future of voice technology, especially considering everything Salesforce is doing with its innovative Einstein Voice Assistant. Sanjna describes the jaw-dropping intricacies of the Einstein Voice Assistant and how it’s going to change the way people do business, view sales, and close deals through the power of A.I. and A.I. personalization.
Best Advice for A.I. Skeptics: “There is very much a human plus A.I. augmentation story that is really, really strong.”
- Salesforce Einstein and its influence on CRM and A.I.
- Thinking about your customer’s customer
- A.I. personalization’s impact
Sanjna’s excitement of technology
Growing up in San Jose, California, so close to the heart of Silicon Valley, Sanjna says it’s pretty hard to not be excited about tech. Both of Sanjna’s parents worked in technology, so from Sanjna’s perspective, it was a natural evolution to also turn technology into a career.
“When I entered the workforce, the artist formerly known as big data, which has now become A.I., was sort of in Vogue. And big data evolved into machine learning. And I realized that there were so many different amazing applications of AI across healthcare and finance and there really is an application for everyone. And that’s really what has kept me excited about this field and why I continue to be in it.”
Einstein is Salesforce’s brand for all things A.I. And as the Senior Product Marketing Manager, Sanjna’s responsible for signaling Einstein and the power that A.I. brings to the whole customer 360 platform that Salesforce has. It’s a difficult job because the common knowledge around A.I. leaves people confused or put off by the complexities behind how A.I. actually works.
Sanjna and her team are focusing their efforts on extracting the complex connotations of A.I. and implementing code-free features that provide value without having the customer worry about anything going on behind the scenes.
When Einstein was launched four years ago, Salesforce centered its attention on one thing, A.I. for CRM. Salesforce’s user base is made up of CRM users and different lines of business. “So that’s sales, service, marketing, commerce and IT. And so for Einstein, we’ve really focused on bringing features to market that help those lines of business,” Sanjna describes. Salesforce cares about these little details of their customer’s day, that in the long-run, make their day more productive, more efficient, and allow the customer of their customers to have better relationships.
Many people correlate A.I. with job replacement, a dystopian, scary future, and other terrifying consequences. Sanjna points out that Salesforce believes that none of that is happening in the near term at all. “There is very much a human plus A.I. augmentation story that is really, really strong,” Sanjna argues.
“One of my favorite things about Einstein is that any type of organization, whether it’s a large enterprise or a small nonprofit, can use A.I. to optimize their business or connect with their customers or clients in a new way.”
Personalization and A.I.
Sanjna explained that there are important personalization elements of A.I. that Salesforce has built in order to create a more effective and even empathetic relationship between customers and the people they serve.
She gives an example of a non-profit working to help students get through school.
“They’re using Einstein to help them engage with students in a better way,” Sanjna explained. “They’re bringing in email data and case data (case notes) and they’re using Einstein language, which analyzes natural language using a technology called natural language processing (NLP) and they’re picking up key things that might be indicators that this kid might drop out of school. For example if Susie says, ‘Hey, my mom and I have recently lost our housing and I won’t be able to go to my school in the next week,’ an A.I. workflow is picking up the sentiment and intent of that text and automatically creating a case for a caseworker to pick up the phone, call Susie, make sure she’s okay, and find her alternative housing.”
Apps being built on the Salesforce Platform
Salesforce has an impressive platform that allows for admins and developers to build apps without any prior knowledge or advanced degrees in programming. All you need to build an app is to know what your problem is and have an idea on how to solve it.
An example of this is an API called Einstein Vision, which does object detection and image recognition. Sanjna explains that Einstein Vision can be used for a variety of different things. An example she uses is if you were to take a photo of a fridge to see if it matches a predetermined planogram you had for your company’s fridge. She continues, “…on the backend, we’ve trained a deep learning algorithm and it’s trained this neural network to recognize that you have a Cola here and a lemon soda there and that you might need to switch those. The planogram can be based on color and the feature of the bottle. And maybe there’s a traditional plastic bottle next to a glass bottle or things like that.
One of Sanjna’s favorite apps is called the “Einstein Voice Assistant,” which is using voice data to increase productivity for salespeople.
“We built the Einstein Voice Assistant to bring in voice data to streamline the sales process,” Sanjna explained. “So now our customers can open the Salesforce mobile app, they can choose the Einstein Voice Assistant and they can dictate their notes into the app, and on the backend, we’re doing voice to text. This is nothing earth-shattering, though. You’ve been able to do that for a long time. But the really cool part is that we’re using natural language processing to understand the sentiment, the intent and the context of those notes that are being transcribed. And then we’re bringing that data into the appropriate records into Salesforce for the customer.”