How Predictive Routing works
Learn how Predictive Routing scores agents to find the best match between agent and interaction for the KPI you want to optimize.
What Predictive Routing does[edit source]
Your environment provides a rich source of historical data about your agents, customers, interactions, and interaction outcomes. Predictive Routing (GPR) ingests this data in a systematic way, then uses it to score your agents for each interaction. Agent scores indicate how well each agent should be able to resolve the customer's need in a way that optimizes whichever metric you are trying to improve. The machine learning component ensures that GPR continuously improves scoring accuracy based on outcome data from previous interaction-agent matchups.
How Predictive Routing works[edit source]
Predictive Routing (GPR) consists of three components: the GPR Core Platform (deployed in Pure Engage cloud), Data Loader, and the URS Strategy Subroutines. Data Loader uploads your data to the Core Platform. The Core Platform enables you to create view your data, create and maintain predictors and models, and score agents. It also provides the GPR web application and the GPR API. The URS Strategy Subroutines integrate into your routing solution, where they submit interaction details to the Core Platform for agent scoring in relation to that interaction, and then route the interaction based on the scoring response.