Our Best Practices section includes thought-leadership, technical guidance, and step-by-step tutorials written by our internal experts, such as our Operational Excellence Group (OEG). Don't be afraid to comment and ask questions!
The following example describes how a stacked chart can be used to display a consistent color distinction between a client company and comparative companies within an industry. Anne’s Boutique is selected as the client company from the line item list selector Select My Company and presented in charts in royal blue color.…
Introduction The following document describes the steps needed to automate integration between cloud data sources and Predictive Insights using CloudWorks. In the document, we will use Amazon S3 integration as an example, but other cloud data sources are also supported. For simplicity, account data will be referred to, but…
Introduction Predictive Insights model performance tracking can be broken out into model tracking and model performance evaluation. The goal for both is to ensure that the model is performing as expected after being in use and is still relevant for the business use case it was built for. To so do involves looking at the…
What is a Model Refresh? Predictive Insights (PI) leverages machine learning models to help users target their total addressable market more intelligently. The machine learning model uses historical account data alongside PI data to build knowledge on how to rank your accounts. Over time, the data set can change and the…
Model evaluation is the operation through which users can estimate the expected performance of a Predictive Insights (PI) predictive model and assess its effectiveness. Since predictions and account prioritization can play an important role in your sales programs or other business initiatives, model evaluation is key and…
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