Create and test predictors and models

Predictors and models are key objects to create and optimize predictive routing.

• Predictors enable you to analyze various factors that might affect a specific metric. For example, you might check how the matching between customer and agent languages, ages, genders, and locations affect the NPS score.
• Models are built on a predictor and include the same target metric. Each model has a subset of the agent and customer features present in the dataset. The Feature Analysis report helps you to identify the features with the strongest impact on the target metric. You can create multiple models for the same predictor, each with a different set of features selected.

Related documentation:

• How Predictive Routing works

About predictor and model creation

Before proceeding to create predictors, make sure you have used Data Loader to upload the following data.

Note: You cannot score agents without including Customer Profile features in your predictor.

• Customer Profile schema
• One or more interactions datasets
• Agent Profile schema

After you upload data, Genesys recommends you to evaluate your data using the Feature Coverage tab on the AI Monitoring window, which helps you create and train effective predictors and models.