Feb 27, 2024
Einstein prediction builder – Exploring Einstein AI and Advanced Analytics

Einstein Prediction Builder is a powerful tool within the Salesforce Einstein platform that enables users to create custom predictions for specific business use cases. It simplifies the process of predictive analytics by automating most technical aspects, such as algorithms, parameter tuning, and infrastructure management. In the context of advanced analytics, Einstein Prediction Builder’s capabilities streamline the process of building, analyzing, and deploying machine learning models, resulting in deeper insights and better decision-making.

Advanced analytics goes beyond traditional business intelligence to discover deeper insights, make predictions, or generate recommendations using techniques such as data mining, machine learning, pattern matching, forecasting, visualization, semantic analysis, and more. Einstein Prediction Builder’s capabilities align with advanced analytics as it involves the use of machine learning to make predictions based on historical data and analyze the performance of these predictions to drive better business outcomes.

The Einstein Prediction Builder simplifies the entire prediction workflow by breaking it down into six steps: defining the use case, identifying the data that supports the use case, creating the prediction, reviewing and iterating the prediction, monitoring the prediction, and deploying and using the prediction.

The following steps can be used when implementing predictions with Einstein Prediction Builder:

  1. Define your use case.

The process begins by identifying a business outcome that needs improvement, such as increasing lead conversion rates, improving customer satisfaction scores, or reducing churn.

  1. Identify the data that supports your use case.

With a clear use case, users can frame their prediction using the “Avocado Framework”, which helps segment the data, identify examples of outcomes, and distinguish between historical data for training and new data for making predictions.

  1. Create your prediction.

Einstein Prediction Builder’s wizard enables users to set up predictions quickly by selecting the data object, specifying the question to be answered (binary or numeric), configuring positive and negative examples, and selecting the fields to be included or excluded from the analysis.

  1. Review, iterate and enable your prediction.

Once the prediction is created, a scorecard is generated that provides information on the quality of the prediction. Users can review and revise their prediction based on the scorecard metrics and insights, remove any potential biases, and enable the prediction.

  1. Monitor your prediction.

After enabling the prediction, it is recommended to let it run for a period of time behind the scenes so that its performance can be assessed on new data. Users can verify the model’s accuracy using Salesforce reports or by utilizing the Einstein Prediction Builder Model Accuracy Template.

  1. Deploy and use your prediction.

Finally, the prediction can be integrated into the business processes using list views, lightning components, Process Builder, or Einstein Next Best Action strategies. Monitoring KPIs, performing a phased rollout, and periodically reviewing the model’s assumptions and performance are essential for success.
In summary, Einstein Prediction Builder simplifies the complex process of creating machine learning models and applying advanced analytics concepts to deliver actionable insights. By streamlining the prediction workflow, users can quickly generate predictions, analyze their performance, and efficiently integrate them into business processes. This tool makes advanced analytics more accessible and easier to use for driving better business decisions.

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