Lately, there has been a ton of press around Salesforce Agentforce.  Rightly so - autonomous agents are the future and will eventually be utilized by almost every company. However, that’s just one use-case for Artificial Intelligence (AI).  It’s also not the only AI product released by Salesforce.

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There is also a suite of Salesforce Einstein AI products. It gets confusing given that there are many products with the “Einstein” moniker, but the one that Everpeak is particularly excited about is Einstein for Sales.  Specifically, it is an ideal tool for B2B companies to use for propensity modeling.

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What is Einstein for Sales?

Formerly known as Einstein GPT, Einstein for Sales is built into the Salesforce platform but also accessible via API. Think of Salesforce Einstein for Sales as a set of AI-powered features embedded within the Sales Cloud. You don't directly call an "Einstein for Sales API" to get lead scores, for example. Instead, you use Salesforce's standard data APIs (SOAP or REST) to query the Lead and Opportunity objects, where Einstein's scores are stored as fields.

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Therefore, while not a discrete API, the intelligence and data provided by Einstein for Sales are accessible programmatically through the broader Salesforce API ecosystem.

What Einstein for Sales is NOT is a pre-configured, ready to go product that you build yourself (ala Agentforce). This is what makes it so powerful. Like Claude or OpenAI, it can be customized, harnessing the Salesforce AI power for your specific use-case.

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What is Propensity Modeling?

Propensity modeling is a statistical technique used to predict the likelihood of a specific outcome or behavior for individual entities, such as customers, prospects, or even events. It leverages historical data and various predictive variables to assign a probability score to each entity, indicating how likely they are to exhibit the target behavior. This behavior could range from making a purchase, churning (leaving a service), or even defaulting on a loan. By quantifying these probabilities, organizations can gain valuable insights into their audience and make more informed decisions.

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Historically, propensity modeling has been powered by the advances in machine learning. AI opens up an entirely new realm of possibilities for predicting behaviors.

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Propensity Modeling with Einstein for Sales

There is an native Lead Score field within Sales Cloud that Einstein for Sales can be used to compute. This is a step forward, but it misses the larger picture. A Lead Score should be informed by the past customer data.

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• Which of my leads look the most like my idea customer?
• In addition, which of my customers are most likely to be open to a cross-sell or up-sell?
• Which of my customers is the most likely to churn?
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This is propensity modeling. To utilize Einstein for Sales to only provide a half-informed Lead Score seems a huge miss.  It’s like owning a Ferrari and never driving above 25 mph.

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There is so much more under the hood of Einstein.

Contact Us for a test drive.

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