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Quick Start

To use Genesys Predictive Routing (GPR), you'll need to install and configure the following products and components:

Install

  1. Install any Genesys components that aren't already part of your environment. You'll need:
  2. Install Genesys Predictive Routing, which consists of the following components:

Configure

To complete your setup of Predictive Routing, configure the following components:

  1. Set the desired values for the AI Core Services and Agent State Connector configuration options.
    You can use configuration options to:
    • Set the login parameters and access URLs for the AI Core Services and the Agent State Connector.
    • Set the KPI criteria to decide what makes for a better match.
  2. To configure how the match between interactions and agents is determined, see Strategy Subroutines Integration.

Import Data

Using the Predictive Routing interface, you import a dataset that is available in CSV format. A dataset is a collection of raw event data. The primary purpose of a dataset is to be the source of Predictor data.

  • Predictive Routing automatically analyzes the data and creates a schema, identifying the various types of data you are importing.
  • You can adjust the schema during the import process.
  • After the dataset has been imported, you can append additional data as long as it is consistent with the schema that has already been established.

Create Predictors and Models

Predictors are based on the dataset information that you have imported and that has been analyzed into a schema.

  • A Predictor defines a view on that underlying dataset. It can select from some or all of the data in the dataset; you can use a predictor with multiple datasets.
  • A Model is based on a Predictor, and uses the same target metric or KVP as that Predictor. You can configure multiple Models for each Predictor. These Models can use different selections of the features available in the underlying dataset. Models are the objects actually used to perform agent scoring and interaction matchups.

As you configure a Predictor, you can choose which metric you want to work with, what kinds of situations you want to evaluate, and other parameters, constructing a way to determine the Next Best Action in the specified situation, based on the possible actions available at that time. As you gather more data, you can add that new data to your dataset, and have the Predictor test against the actual results coming in, enabling you to refine how successful your Predictor is.

Reporting and Analysis

You can report on various parameters, such as:

  • The success of your predictors.
  • The results of A/B testing.
  • The factors affecting a KPI you are trying to influence.

Reports are available through the following reporting applications:

This page was last modified on December 20, 2018, at 07:43.

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