Predict the Future with Einstein Prediction Builder
In a world where artificial intelligence is reshaping how we make decisions, tools like Salesforce Einstein Prediction Builder are helping mission-driven organizations take their programs to the next level. Whether you’re working to reduce homelessness, increase donor engagement, or improve workforce outcomes, predictive analytics can turn your existing data into actionable insights—and Einstein Prediction Builder makes that process easier, more accessible, and even free to start.
In this guide, we’ll explore what the Einstein Prediction Builder is, how it works, and how nonprofits and government agencies are using it to make more informed, proactive decisions. We'll also explain how Salesforce Einstein Prediction Builder fits into the broader suite of Einstein tools, and how Provisio can help you get started.
Predictive Analytics to Help You Serve Your Clients Better
With all the technological progress that’s been made recently with artificial intelligence, you might be wondering how your organization can use predictive analytics to assess your programs and better serve your clients. I know I’ve used it for less laudable purposes, like creating more attractive computer-generated images of myself for social media or making ChatGPT write my emails when I’m feeling lazy or uninspired. You’re obviously a better person than I am, so here’s some relevant information for you! (I promise that I wrote this with the help of our human data experts, not AI.)Here are some of the questions we hear regularly from human services organizations:
Who might be at risk for becoming homeless again?
Who might be at risk for dropping out of programs?
Who will remain employed after 90 days?
Who will be a good first-time donor?
Who will likely be a recurring donor?
How Does Salesforce Einstein Prediction Builder Work?
Einstein Prediction Builder works by analyzing patterns in your Salesforce data. Let’s say you’re using assessments like the VI-SPDAT or Arizona Self-Sufficiency Matrix (ASSM) to evaluate housing stability or client needs. These assessments—combined with historical outcomes logged by case managers (like dates of program completion, service exits, or donation behavior)—give Einstein the raw data it needs to train a model.
The prediction process includes:
Defining the Prediction Goal – What do you want to predict? For example, “Will this individual exit the program early?”
Choosing the Object – Select a Salesforce object that contains the data relevant to your prediction (e.g., Contact, Case, or custom objects).
Training the Model – Einstein will use your historical data to identify patterns and correlations related to your goal.
Scoring New Records – Once trained, the model will automatically score new records, helping you assess risk or opportunity in real time.
Organizations often find they already have the data needed to get started—they just need to identify a meaningful outcome to focus on.
Predictive Analytics Made Practical
One option for you is to implement Salesforce’s Einstein Prediction Builder. This application comes with one free prediction and can be used for forecasting or prediction. Yes, I said free! Einstein Prediction Builder can be used with assessments, such as the VI-SPDAT, the most commonly used tool for housing risk and prioritization for housing services, or the Arizona Self-Sufficiency Matrix (ASSM). When you complete these assessments, it gives Einstein a lot of data to work with. An assessment combined with the historical data that case managers enter (like the date someone dropped out of a program) gives Einstein what it needs to predict. We can provide you with more details and suggestions, but you just have to decide, “What do I want to determine?” and “Do I have the data to do so?” You can look at multiple factors, such as whether an individual is a Senior, Disabled, or Homeless to determine whether the person is at risk for not completing a program. On the more positive side, what combination of factors will make them more likely to succeed?
Beyond Prediction: The Einstein Suite of Tools
Einstein Prediction Builder is not your only option. Einstein Next Best Action will surface recommendations on the screen, either based on an Einstein Prediction or logic that's added manually; so, for example, if someone wants to cancel their service, Einstein Prediction Builder can figure out what offer is likely to entice them to stay, and then Einstein Next Best Action displays that offer on the screen to the user. Other products, like Einstein for Sales or Einstein for Service, basically use Einstein under the hood and present automatic calculations and forecasts to users, so they're not as customizable, but they're already set up for different industries. Einstein Discovery and CRM contains all of the above, plus Tableau predictions. It's the most comprehensive, and it also features a "find insights" option where, instead of you needing to tell the system what to predict (like in Einstein Prediction Builder), it will automatically look for things and then give you the option to adopt them.
Real-World Use Cases for Human Services and Nonprofits
Here are some of the most common ways we’ve seen Salesforce Einstein Prediction Builder used by nonprofit and public sector organizations:
Homeless Services: Predict which individuals are most at risk of becoming homeless again after a program exit.
Employment Programs: Forecast which participants are most likely to remain employed after 90 days, based on their background, services received, and engagement level.
Donor Engagement: Identify first-time donors who are most likely to give again, enabling you to personalize follow-ups and retention strategies.
Program Completion: Determine who is at risk of not completing a training or support program—and intervene early to support them.
By shifting from reactive to proactive, organizations can make better use of limited resources, reduce dropout or recidivism rates, and increase long-term impact.
How Provisio Helps You Implement Predictive Intelligence
At Provisio, we specialize in helping mission-driven organizations get the most out of Salesforce. Our team of human services data experts works with nonprofits and government agencies to implement Salesforce Einstein Prediction Builder in a way that’s grounded in real-world outcomes and aligned with your goals.
We’ll help you:
Identify prediction opportunities within your current programs
Evaluate your existing data readiness
Build and train your first model
Interpret and apply predictions to improve services and outreach
We’ve worked with organizations across housing, workforce development, public health, and more to leverage predictive analytics in a meaningful way—without overwhelming internal teams or requiring deep technical expertise.
Ready to Predict What’s Next?
Einstein tools, like Salesforce Einstein Prediction Builder, allow organizations to be more proactive in supporting vulnerable individuals and improving your programs and services. Interested? At Provisio, we’re committed to helping nonprofit and government organizations harness AI in a way that’s ethical, effective, and impactful.
Let’s build the future together. Contact Provisio today to schedule a consultation and discover how Einstein Prediction Builder can transform your programs. We have a team of data experts ready to help you determine what would work best for you. I predict they will be incredibly helpful! Click here to connect with us!
FAQs
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Salesforce Einstein Prediction Builder is a tool that lets you create custom AI-powered predictions using your existing Salesforce data—no coding or data science expertise required. It helps organizations forecast outcomes like client risk, donor behavior, or program success.
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Yes, every Salesforce org includes one free prediction with Einstein Prediction Builder. Additional predictions may require a Salesforce Einstein license depending on your needs and subscription.
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You’ll need historical data stored in Salesforce that relates to the outcome you want to predict. This could include assessments, form submissions, donation records, or service interactions.
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Prediction accuracy depends on the quality and volume of your historical data. During setup, Einstein provides insights into model performance and lets you test predictions before going live.
