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What Are the Key Features of Salesforce's Model Builder?
Today on the Salesforce Admins Podcast, it's another deep dive with Josh Birk as he talks to Bobby Brill, Senior Director of Product for Einstein Discovery.
Join us as we chat about how you can use Model Builder to harness the power of AI with clicks, not code.
You should subscribe for the full episode, but here are a few takeaways from our conversation with Bobby Brill.
What is Model Builder?Bobby started his career at Salesforce in Customer Success before working on Wave Analytics. These days, he's the Senior Director of Product for Einstein Discovery, and he's here to talk about what Model Builder can do for your business.
If you have Data Cloud, then you already have access to Model Builder via the Einstein Studio Tab. With it, you can create predictive models with clicks, not code, using AI to look through your data and generate actionable insights. As Bobby says, the AI isn't really the interesting part—it's how you can use it as a tool to solve your business problems.
BYOM - Build Your Own ModelIn traditional machine learning, models are trained on data to identify successful and unsuccessful trends, which is fundamental for making accurate predictions. For example, if you want to create an opportunity scoring model, you need to point it to the data you have on which leads converted and which leads didn't pan out.
Model Builder lets you do just that, building your own model based on the data in your org. What's more, it fits seamlessly into the structures admins already understand. We can put our opportunity scoring model into a flow to sort high-scoring leads into a priority queue. And we can do all of this with clicks, not code.
Building a predictive model that's good enoughEinstein's LLM capabilities offer even more possibilities when it comes to using your data with Model Builder. You can process unstructured texts like chats or emails to do something like measure if a customer is becoming unhappy. And you can plug that into a flow to do something to fix it.
One thing that Bobby points out is that building a model is an iterative process. If you have 100% accuracy, you haven't really created a predictive model so much as a business rule. As long as the impact of a wrong decision is manageable, it's OK to build something that's good enough and know that it will improve over time.
There's a lot more great stuff from Bobby about how to build predictive models and what's coming next, so be sure to listen to the full episode. And don't forget to subscribe to hear more from the Salesforce Admins Podcast.
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Connect with Bobby: https://www.linkedin.com/in/bobbybrill/
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Published on 1 year, 4 months ago