Creating a predictive sales model with Salesforce Einstein Discovery helps sales teams forecast deals and focus on high-potential leads using data insights. This tool sifts through your CRM data to spot patterns, guiding you toward smarter decisions. No coding skills are needed, just your Salesforce data and a clear process.
This guide breaks down how to build a predictive sales model in simple steps. From setting up data to putting predictions into action, you’ll learn how to boost sales efficiency. Whether you’re new to Salesforce or a pro, these steps will help you use Einstein Discovery to drive revenue.
What Is a Predictive Sales Model?
A predictive sales model analyzes past data to forecast future results, like which deals will close or how much revenue they’ll bring. In Salesforce Einstein Discovery, it processes CRM data to think about deal size, lead source, or industry to uncover trends.
This shifts sales from guesswork to strategy. For instance, it might show email leads close 12% faster than phone leads. By prioritizing high-win opportunities, teams save time and boost success rates. The model integrates directly into Salesforce, fitting seamlessly into your daily work.
Predict Deals Using Einstein Discovery
With Salesforce Einstein Discovery, you can analyze past sales data to identify winning opportunities. Build data-driven models to guide your team toward better decisions and higher close rates. It’s easy to set up and integrates seamlessly with your CRM. Start building smarter sales strategies now.
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What Do You Need to Start with Einstein Discovery?
Before building your model, ensure your Salesforce setup is ready. Here’s what’s required:
- Salesforce Edition: Sales Cloud Unlimited or an Einstein Discovery add-on license.
- User Permissions: Get the “Einstein Discovery Editor” role through Setup > Permission Sets.
- Data Size: At least 400 records with clear outcomes (e.g., closed-won or closed-lost deals). Einstein handles up to 20 million rows.
- CRM Analytics: Enable this to manage datasets.
Since it’s cloud-based, no special hardware is needed. Check with your Salesforce admin to confirm these settings.
How Do You Prepare Data for a Predictive Sales Model?
Good data is key to accurate predictions. In CRM Analytics Studio, create a dataset from Salesforce objects like Opportunities or Accounts. Include fields such as Amount, Stage, Close Date, Lead Source, and Industry.
Focus on recent data (last two years) with clear outcomes. Clean out duplicates and fill in missing fields to avoid errors. For deeper insights, add related data like Account details using dataflows. Limit predictors to 10-20 fields for clarity.
Preview the dataset to ensure it captures your sales process. Save it as a CRM Analytics dataset to use for modeling.
Building Your Predictive Sales Model
Here’s how to create your model in Einstein Discovery:
- Go to CRM Analytics Studio: Start with “Create Story” or “New Model.”
- Pick Your Dataset: Select the dataset you prepared.
- Set the Goal: Choose what to predict, like “Will Close” (yes/no) or “Sales Amount.”
- Select Predictors: Include fields like Deal Size or Region that impact results.
- Train the Model: Einstein processes the data in 10-30 minutes.
After training, check the model’s accuracy (aim for 70% or higher). Review insights, like which factors drive wins, and adjust predictors if needed. Retrain for better results.
Build Sales Models with Einstein Discovery
Turn your CRM data into powerful insights using Salesforce Einstein Discovery. Create a predictive sales model to pinpoint high-value deals, save time, and increase revenue. No coding needed, just your Salesforce data and a few clicks to get started. Take control of your sales process today.
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How Can You Test Your Predictive Sales Model?
Testing ensures your model works in real sales scenarios. Einstein provides a dashboard with metrics like:
- Precision: How often predicted wins actually close.
- Recall: The share of true wins the model catches.
- Lift: How much better prioritized deals perform compared to random ones.
Use holdout data (a reserved subset) to test accuracy. Try “what-if” scenarios, like changing deal terms, to see their effect. Check for biases, like uneven results by region, using Einstein’s alerts. Compare predictions to past sales data. If accuracy drops below 65%, refine your data or predictors.
Putting Your Predictive Sales Model to Work
Once your model is ready, make it part of your sales process. In Einstein Discovery, click “Deploy” and choose integration options:
- Opportunity Records: Add a prediction field showing scores like “80% chance to close.”
- Lightning Pages: Use App Builder to add the “Einstein Predictions” component.
- Forecasting: Link to Sales Cloud’s forecasting tools for pipeline views.
Test with a small group of reps first. Track performance via Salesforce logs to ensure predictions stay accurate.
Tips for a Strong Predictive Sales Model
To get the most from your model, follow these practices:
- Update Data Often: Refresh datasets monthly for relevant predictions.
- Work with Sales Teams: Pick outcomes and predictors with rep input.
- Start Focused: Target one goal, like small-business deals, before expanding.
- Check for Fairness: Use Einstein’s bias detection to ensure equitable results.
- Measure Impact: Track win rate improvements (often 10-20%) to show value.
Advanced users can explore custom algorithms with Bring Your Own Model (BYOM), but Einstein’s native tools work well for most.
Why Choose Salesforce Einstein Discovery for Sales Predictions?
Salesforce Einstein Discovery makes predictive analytics easy, even without technical skills. It blends seamlessly with your CRM, turning data into insights that sharpen your sales strategy. By focusing on high-value deals, you close more with less effort.
Ready to start? Open CRM Analytics Studio, upload your dataset, and build your first predictive sales model. With clear predictions, your sales pipeline becomes a roadmap to success. Contact OzaIntel for expert guidance on optimizing your Salesforce Einstein setup.
